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Computer Networking Dissertation Topics

Published by Carmen Troy at January 5th, 2023 , Revised On August 16, 2023

A dissertation is an essential aspect of completing your degree program. Whether you are pursuing your master’s or are enrolled in a PhD program, you will not be awarded a degree without successfully submitting a thesis. To ensure that your thesis is submitted successfully without any hindrances, you should first get your topic and dissertation outline approved by your professor. When approving, supervisors focus on a lot of aspects. However, relevance, recency, and conciseness of your topic play a huge role in accepting or rejecting your topic.

As a computer networking student, you have a variety of networking topics to choose from. With the field evolving with each passing day, you must ensure that your thesis covers recent computer networking topics and explores a relevant problem or issue. To help you choose the right topic for your dissertation, here is a list of recent and relevant computer networking dissertation topics.

2022 Computer Networking Dissertation Topics

Topic 1: an evaluation of the network security during machine to machine communication in iot.

Research Aim: The research aims to evaluate the network security issues associated with M2M communication in IoT.

 Objectives:

  • To evaluate the factors affecting the network security of IoT devices.
  • To determine the methods for increasing data integrity in M2M communication against physical tampering and unauthorised monitoring.
  • To evaluate the network security issues associated with M2M communication in IoT and offer suitable recommendations for improvement.

Topic 2: An analysis of the cybersecurity challenges in public clouds and appropriate intrusion detection mechanisms.

Research Aim: The aim of the research is to analyse the cybersecurity challenges in public clouds and the appropriate intrusion detection mechanisms.

Objectives:

  • To analyse the types of cybersecurity threats impacting public clouds.
  • To determine some of the competent intrusion detection techniques that can be used in cloud computing.
  • To investigate the cybersecurity challenges in public clouds and offer mitigating with appropriate intrusion detection techniques.

Topic 3: Investigating the impact of SaaS cloud ERP on the scalability and cost-effectiveness of business.

Research Aim: The research aims to investigate the impact of SaaS cloud ERP on the scalability and cost-effectiveness of business.

  • To analyse the benefits of SaaS ERP over traditional ERP.
  • To evaluate the characteristics of SaaS architecture in cloud computing and determine its varieties.
  • To investigate how SaaS cloud ERP impacts business scalability and cost-effectiveness.

Topic 4: An evaluation of the requirements of cloud repatriation and the challenges associated with it.

Research Aim: The research aims to evaluate the requirements of cloud repatriation in organisations and the associated challenges

  • To analyse the key factors of cloud repatriation.
  • To determine the challenges associated with cloud repatriation from public clouds.
  • To evaluate the need for cloud repatriation in organisations and the associated complexities

Topic 5: An examination of the security mechanisms in decentralised networks and the ways of enhancing system robustness

Research Aim: The research aims to investigate the security mechanisms in decentralised networks and the ways of enhancing system robustness.

  • To analyse the concept of decentralised networks and understand its difference from centralised networks.
  • To analyse the security mechanisms in decentralised networks for determining how it offers visibility and traceability.
  • To investigate the security mechanisms in decentralised networks and how system robustness can be increased for better privacy and security.

Computer Networking Dissertation Topics for 2021

Exploring the importance of computer networking in today’s era.

Research Aim: Even though computer networking has been practised for a few years now, its importance has increased immensely over the past two years. A few main reasons include the use of technology by almost every business and the aim to offer customers an easy and convenient shopping experience. The main aim of this research will be to explain the concepts of computer networking, its benefits, and its importance in the current era. The research will also discuss how computer networking has helped businesses and individuals perform their work and benefit from it. The research will then specifically state examples where computer networking has brought positive changes and helped people achieve what they want.

Wireless Networks in Business Settings – An Analysis

Research Aim: Wireless networks are crucial in computer networking. They help build networks seamlessly, and once the networks are set up on a wireless network, it becomes extremely easy for the business to perform its daily activities. This research will investigate all about wireless networks in a business setting. It will first introduce the various wireless networks that can be utilized by a business and will then talk about how these networks help companies build their workflow around it. The study will analyze different wireless networks used by businesses and will conclude how beneficial they are and how they are helping the business.

Understanding Virtual Private Networks – A Deep Analysis of their Challenges

Research Aim: Private virtual networks (VPN) are extremely common today. These are used by businesses and individuals alike. This research aims to understand how these networks operate and how they help businesses build strong and successful systems and address the challenges of VPNs. A lot of businesses do not adopt virtual private networks due to the challenges that they bring. This research will address these challenges in a way that will help businesses implement VPN successfully.

A Survey of the Application of Wireless Sensor Networks

Research Aim: Wireless sensor networks are self-configured, infrastructure-less wireless networks to pass data. These networks are now extremely popular amongst businesses because they can solve problems in various application domains and possess the capacity to change the way work is done. This research will investigate where wireless sensor networks are implemented, how they are being used, and how they are performing. The research will also investigate how businesses implement these systems and consider factors when utilizing these wireless sensor networks.

Computer Network Security Attacks – Systems and Methods to Respond

Research Aim: With the advent of technology today, computer networks are extremely prone to security attacks. A lot of networks have security systems in place. However, people with nefarious intent find one way to intrude and steal data/information. This research will address major security attacks that have impacted businesses and will aim to address this challenge. Various methods and systems will be highlighted to protect the computer networks. In addition to this, the research will also discuss various methods to respond to attacks and to keep the business network protected.

Preventing a Cyberattack – How Can you Build a Powerful Computer Network?

Research Aim: Cyberattacks are extremely common these days. No matter how powerful your network is, you might be a victim of phishing or hacking. The main aim of this research will be to outline how a powerful computer network can be built. Various methods to build a safe computer network that can keep data and information will be outlined, and the study will also highlight ways to prevent a cyberattack. In addition to this, the research will talk about the steps that should be taken to keep the computer network safe. The research will conclude with the best way and system to build a powerful and safe computer network.

Types of Computer Networks: A Comparison and Analysis

Research Aim: There are different types of computer networks, including LAN, WAN, PAN, MAN, CAN, SAN, etc. This research will discuss all the various types of computer networks to help readers understand how all these networks work. The study will then compare the different types of networks and analyze how each of them is implemented in different settings. The dissertation will also discuss the type of computer networks that businesses should use and how they can utilize them for their success. The study will then conclude which computer network is the best and how it can benefit when implemented.

Detecting Computer Network Attacks by Signatures and Fast Content Analysis

Research Aim: With technological advancement, today, many computer network attacks can be detected beforehand. While many techniques are utilized for detecting these attacks, the use of signatures and fast content analysis are the most popular ones. This research will explore these techniques in detail and help understand how they can detect a computer network attack and prevent it. The research will present different ways these techniques are utilised to detect an attack and help build powerful and safe computer networks. The research will then conclude how helpful these two techniques are and whether businesses should implement them.

Overview of Wireless Network Technologies and their Role in Healthcare

Research Aim: Wireless network technologies are utilised by several industries. Their uses and benefits have helped businesses resolve many business problems and assisted them in conducting their daily activities without any hindrance. This networking topic will help explore how wireless network technologies work and will talk about their benefits. This research aims to find out how wireless technologies help businesses carry out their daily routine tasks effortlessly. For this research, the focuas will be the healthcare industry. The study will investigate how wireless network technology has helped the healthcare sector and how it has benefited them to perform their daily tasks without much effort.

Setting up a Business Communication System over a Computer Network

Research Aim: Communication is an essential aspect of every business. Employees need to communicate effectively to keep the business going. In the absence of effective communication, businesses suffer a lot as the departments are not synchronized, and the operations are haphazard. This research will explore the different ways through which network technologies help conduct smooth and effective communication within organizations. This research will conclude how wireless networks have helped businesses build effective communication systems within their organization and how they have benefited from it. It will then conclude how businesses have improved and solved major business problems with the help of these systems.

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How to find computer networking dissertation topics.

To find computer networking dissertation topics:

  • Follow industry news and emerging technologies.
  • Investigate unresolved networking challenges.
  • Review recent research papers.
  • Explore IoT, cybersecurity, cloud computing.
  • Consider real-world applications.
  • Select a topic aligned with your expertise and career aspirations.

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134. Vishrant Tripathi, Nick Jones, Eytan Modiano, Fresh-CSMA: A Distributed Protocol for Minimizing Age of Information, IEEE Journal on Communications and Networks, 2024.

133. Bai Liu, Quang Nguyen, Qingkai Liang, Eytan Modiano, Tracking Drift-Plus-Penalty: Utility Maximization for Partially Observable and Controllable Networks, IEEE/ACM Transactions on Networking, 2024.

132. Xinzhe Fu, Eytan Modiano, Optimal Routing to Parallel Servers with Unknown Utilities – Multi-armed Bandit With Queues, IEEE/ACM Transactions on Networking, January 2022.

131. Bai Liu, Qingkai Liang, Eytan Modiano, Tracking MaxWeight: Optimal Control for Partially Observable and Controllable Networks, IEEE/ACM Transactions on Networking, August 2023.

130. Xinzhe Fu, Eytan Modiano, Joint Learning and Control in Stochastic Queueing Networks with unknown Utilities, Proceedings of the ACM on Measurement and Analysis of Computing Systems, 2023.

129. Vishrant Tripathi, Rajat Talak, Eytan Modiano, Information Freshness in Multi-Hop Wireless Networks, IEEE/ACM Transactions on Networking,” April 2023.

128.  Xinzhe Fu, Eytan Modiano, “ Learning-NUM: Network Utility Maximization with Unknown Utility Functions and Queueing Delay ,”  IEEE/ACM Transactions on Networking,” 2022.

127.  Bai Liu, Qiaomin Xie, Eytan Modiano,  " RL-QN: A Reinforcement Learning Framework for Optimal Control of Queueing Systems ,"  ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS), 2022.

126. Xinzhe Fu and E. Modiano,  “ Elastic Job Scheduling with Unknown Utility Functions ,” Performance Evaluation, 2021.

125. Bai Liu and E. Modiano, “ Optimal Control for Networks with Unobservable Malicious Nodes ,”  Performance Evaluation, 2021.

124. Vishrant Tripathi, Rajat Talak, Eytan Modiano, " Age Optimal Information Gathering and Dissemination on Graphs ,”  Transactions on Mobile Computing, April 2021.

123.  Xinyu Wu, Dan Wu, Eytan Modiano, “ Predicting Failure Cascades in Large Scale Power Systems via the Influence Model Framework, ”  IEEE Transactions on Power Systems, 2021.

122.   Roy D. Yates, Yin Sun, D. Richard Brown III, Sanjit K. Kaul, Eytan Modiano and Sennur Ulukus, “ Age of Information: An Introduction and Survey, ”  Journal on Selected Areas in Communications, February 2021.

121.   Jianan Zhang, Abhishek Sinha, Jaime Llorca, Anonia Tulino, Eytan Modiano, “ Optimal Control of Distributed Computing Networks with Mixed-Cast Traffic Flows ,”  IEEE/ACM Transactions on Networking, 2021.

120.   Thomas Stahlbuhk, Brooke Shrader, Eytan Modiano, " Learning Algorithms for Minimizing Queue Length Regret ,”  IEEE Transactions on Information Theory, 2021.

119.   Thomas Stahlbuhk, Brooke Shrader, Eytan Modiano, “ Throughput Maximization in Uncooperative Spectrum Sharing Networks ,”  IEEE/ACM IEEE/ACM Transactions on Networking, Vol. 28, No. 6, December 2020.

118.   Thomas Stahlbuhk, Brooke Shrader, Eytan Modiano, “ Learning algorithms for scheduling in wireless networks with unknown channel statistics ,” Ad Hoc Networks, Vol. 85, pp. 131-144, 2019.

117.   Rajat Talak, Eytan Modiano, “ Age-Delay Tradeoffs in Queueing Systems ,”  IEEE Transactions on Information Theory, 2021.

116.   Rajat Talak, Sertac Karaman, Eytan Modiano, " Improving Age of Information in Wireless Networks with Perfect Channel State Information ,”  IEEE/ACM Transactions on Networking, Vol. 28, No. 4, August 2020.

115.   Igor Kadota and Eytan Modiano, “ Minimizing the Age of Information in Wireless Networks with Stochastic Arrivals ,” IEEE Transactions on Mobile Computing, 2020.

114.   Rajat Talak, Sertac Karaman, Eytan Modiano, “ Optimizing Information Freshness in Wireless Networks under General Interference Constraints ,”  IEEE/ACM transactions on Networking, Vol. 28, No. 1, February 2020.

113.   X. Fu and E. Modiano, " Fundamental Limits of Volume-based Network DoS Attacks ," Proceedings of the ACM on Measurement and Analysis of Computing Systems, Vol. 3, No. 3, December 2019. 

112.   Rajat Talak, Sertac Karaman, Eytan Modiano, “ Capacity and Delay Scaling for Broadcast Transmission in Highly Mobile Wireless Networks ,” IEEE Transactions on Mobile Computing, 2019.

111.   Abhishek Sinha and Eytan Modiano, “ Throughput-Optimal Broadcast in Wireless Networks with Point-to-Multipoint Transmissions , IEEE Transactions on Mobile Computing, Vol. 19, No. 9, September 2020.

110.   Yu-Pin Hsu, Eytan Modiano, Lingjie Duan, “ Scheduling Algorithms for Minimizing Age of Information in Wireless Broadcast Networks with Random Arrivals ,”  IEEE Transactions on Mobile Computing, Vol. 19, No. 12, December 2020.

109.   Xiaolin Jiang, Hossein S. Ghadikolaei, Gabor Fodor, Eytan Modiano, Zhibo Pang, Michele Zorzi, Carlo Fischione, " Low-latency Networking: Where Latency Lurks and How to Tame It ,”  Proceedings of the IEEE, 2019.

108.   Jianan Zhang, Edmund Yeh, Eytan Modiano, “ Robustness of Interdependent Random Geometric Networks ,” IEEE Transactions on Network Science and Engineering, Vol. 6, No. 3, July-September 2019.

107.   Qingkai Liang, Hyang-Won Lee, Eytan Modiano, “ Robust Design of Spectrum-Sharing Networks ,” IEEE Transactions on Mobile Computing, Vol. 18, No. 8, August 2019.

106.   A. Sinha, L. Tassiulas, E. Modiano, “ Throughput-Optimal Broadcast in Wireless Networks with Dynamic Topology ,”  IEEE Transactions on Mobile Computing, Vol. 18, No. 5, May 2019.

105. Igor Kadota, Abhishek Sinha, Eytan Modiano, “ Scheduling Algorithms for Optimizing Age of Information in Wireless Networks With Throughput Constraints ,”  IEEE/ACM Transactions on Networking, August 2019.

104.   Igor Kadota, Abhishek Sinha, Rahul Singh, Elif Uysal-Biyikoglu, Eytan Modjano, “ Scheduling Policies for Minimizing Age of Information in Broadcast Wireless Networks ,” IEEE/ACM Transactions on Networking, Vol. 26, No. 5, October 2018.

103.   Jianan Zhang and Eytan Modiano, “ Connectivity in Interdependent Networks ,”  IEEE/ACM Transactions on Networking, 2018.

102.   Qingkai Liang, Eytan Modiano, “ Minimizing Queue Length Regret Under Adversarial Network Models ,” Proceedings of the ACM on Measurement and Analysis of Computing Systems, Volume 2, Issue 1, April 2018, Article No.: 11, pp 1-32. (same as Sigmetrics 2018).

101.   A. Sinha and E. Modiano, “ Optimal Control for Generalized Network Flow Problems ,”  IEEE/ACM Transactions on Networking, 2018.

100.   Hossein Shokri-Ghadikolaei, Carlo Fischione, Eytan Modiano  “ Interference Model Similarity Index and Its Applications to mmWave Networks ,”  IEEE Transactions on Wireless Communications, 2018.

99.   Matt Johnston, Eytan Modiano, “ Wireless Scheduling with Delayed CSI: When Distributed Outperforms Centralized, ’ IEEE Transactions on Mobile Computing, 2018.

98.   A. Sinha, G. Paschos, E. Modiano, “ Throughput-Optimal Multi-hop Broadcast Algorithms ," IEEE/ACM Transactions on Networking, 2017.

97.   Nathan Jones, Georgios Paschos, Brooke Shrader, Eytan Modiano, " An Overlay Architecture for Throughput Optimal Multipath Routing ,” IEEE/ACM Transactions on Networking, 2017.

96.   Greg Kuperman, Eytan Modiano, “ Providing Guaranteed Protection in Multi-Hop Wireless Networks with Interference Constraints ,” IEEE Transactions on Mobile Computing, 2017.

95.   Matt Johnston, Eytan Modiano, Isaac Kesslassy, “ Channel Probing in Opportunistic Communications Systems ,”  IEEE Transactions on Information Theory, November, 2017.

94.   Anurag Rai, Georgios Paschos, Chih-Ping Lee, Eytan Modiano, " Loop-Free Backpressure Routing Using Link-Reversal Algorithms ", IEEE/ACM Transactions on Networking, October, 2017.

93.   Matt Johnston and Eytan Modiano, “" Controller Placement in Wireless Networks with Delayed CSI ,” IEEE/ACM Transactions on Networking, 2017.

92.   Jianan Zheng, E. Modiano, D. Hay, " Enhancing Network Robustness via Shielding ,”  IEEE Transactions on Networking, 2017.

91.   M. Markakis, E. Modiano, J.N. Tsitsiklis, “ Delay Analysis of the Max-Weight Policy under Heavy-Tailed Traffic via Fluid Approximations ,” Mathematics of Operations Research, October, 2017.

90.   Qingkai Liang and E. Modiano, “ Survivability in Time-Varying Graphs ,”  IEEE Transactions on Mobile Computing, 2017.

89.   A. Sinha, G. Paschos, C. P. Li, and E. Modiano, “ Throughput-Optimal Multihop Broadcast on Directed Acyclic Wireless Networks ," IEEE/ACM Transactions on Networking, Vol. 25, No. 1, Feb. 2017.

88.   G. Celik, S. Borst, , P. Whiting , E. Modiano, “ Dynamic Scheduling with Reconfiguration Delays ,”  Queueing Systems, 2016.

87.  G. Paschos, C. P. Li, E. Modiano, K. Choumas, T. Korakis, “ In-network Congestion Control for Multirate Multicast ,”   IEEE/ACM Transactions on Networking,  2016.

86.   H. Seferoglu and E. Modiano, “ TCP-Aware Backpressure Routing and Scheduling ,” IEEE Transactions on Mobile Computing, 2016.

85.   H. Seferoglu and E. Modiano, “ Separation of Routing and Scheduling in Backpressure-Based Wireless Networks ," IEEE/ACM Transactions on Networking, Vol. 24, No. 3, 2016.

84.   M. Markakis, E. Modiano, J.N. Tsitsiklis, “ Delay Stability of Back-Pressure Policies in the presence of Heavy-Tailed Traffic ,”  IEEE/ACM Transactions on Networking, 2015.

83.   S. Neumayer, E. Modiano,  “ Network Reliability Under Geographically Correlated Line and Disk Failure Models ,” Computer Networks, to appear, 2016.

82.   S. Neumayer, E. Modiano, A. Efrat, “ Geographic Max-Flow and Min-Cut Under a Circular Disk Failure Model ,” Computer Networks, 2015.

81.   Marzieh Parandehgheibi, Hyang-Won Lee, Eytan Modiano, Survivable Path Sets:  A new approach to survivability in multi-layer networks ,”  IEEE Journal on Lightwave Technology, 2015.

80.   G. Kuperman, E. Modiano, A. Narula-Tam, “ Network Protection with Multiple Availability Guarantees ,” Computer Networks, 2015.

79.   G. Kuperman, E. Modiano, A. Narula-Tam, “ Analysis and Algorithms for Partial Protection in Mesh Networks ,” IEEE/OSA Journal of Optical Communications and Networks, 2014.

78.   Krishna Jagannathan, Mihalis Markakis, Eytan Modiano, John Tsitsiklis, " Throughput Optimal Scheduling over Time-Varying Channels in the presence of Heavy-Tailed Traffic ,” IEEE Transactions on Information Theory, 2014.

77.   Chih-Ping Li and Eytan Modiano, “ Receiver-Based Flow Control for Networks in Overload ," IEEE/ACM Transactions on Networking, Vol. 23, No. 2, 2015.

76.   Matthew Johnston, Hyang-Won Lee, Eytan Modiano, “ A Robust Optimization Approach to Backup Network Design with Random Failures ,” IEEE/ACM Transactions on Networking, Vol. 23, No. 4, 2015.

75.   Guner Celik and Eytan Modiano, “ Scheduling in Networks with Time-Varying Channels and Reconfiguration Delay ," IEEE/ACM Transactions on Networking, Vol. 23, No. 1, 2015.

74.   Matt Johnston, H.W. Lee, E. Modiano, “ Robust Network Design for Stochastic Traffic Demands ," IEEE Journal of Lightwave Technology, 2013.

73.   Mihalis Markakis, Eytan Modiano, John Tsitsiklis, “ Max-Weight Scheduling in Queueing Networks With Heavy-Tailed Traffic, ” IEEE/ACM Transactions on Networking, 2014.

72.   Kayi Lee, Hyang-Won Lee, Eytan Modiano, " Maximizing Reliability in WDM Networks through Lightpath Routing ,”  IEEE ACM Transactions on Networking, 2014.

71.   Krishna Jaggannathan and Eytan Modiano, “ The Impact of Queue Length Information on Buffer Overflow in Parallel Queues ,”  IEEE transactions on Information Theory, 2013.

70.   Krishna Jagannathan, Ishai Menashe, Gil Zussman, Eytan Modiano, “ Non-cooperative Spectrum Access - The Dedicated vs. Free Spectrum Choice ,” IEEE JSAC, special issue on Economics of Communication Networks & Systems, to appear, 2012.

69.   Guner Celik and Eytan Modiano, “ Dynamic Server Allocation over Time Varying Channels with Switchover Delay ," IEEE Transactions on Information Theory, to appear, 2012.

68.   Anand Srinivas and Eytan Modiano, " Joint Node Placement and Assignment for Throughput Optimization in Mobile Backbone Networks ,” IEEE JSAC, special issue on Communications Challenges and Dynamics for Unmanned Autonomous Vehicles, June, 2012.

67.   Guner Celik and Eytan Modiano, “ Controlled Mobility in Stochastic and Dynamic Wireless Networks ," Queueing Systems, 2012.

66.   Krishna Jagannathan, Shie Mannor, Ishai Menache, Eytan Modiano, “ A State Action Frequency Approach to Throughput Maximization over Uncertain Wireless Channels ,” Internet Mathematics, Vol. 9, Nos. 2–3: 136–160.

65.   Long Le, E. Modiano, N. Shroff, “Optimal Control of Wireless Networks with Finite Buffers ,” IEEE/ACM Transactions on Networking, to appear, 2012.

64.   K. Jagannathan, M. Markakis, E. Modiano, J. Tsitsiklis, “Queue Length Asymptotics for Generalized Max-Weight Scheduling in the presence of Heavy-Tailed Traffic,” IEEE/ACM Transactions on Networking, Vol. 20, No. 4, August 2012.

63.   Kayi Lee, Hyang-Won Lee, Eytan Modiano, “ Reliability in Layered Networks with Random Link Failures, ” IEEE/ACM Transactions on Networking, December 2011.

62.   Krishna Jagannathan, Eytan Modiano, Lizhong Zheng, “ On the Role of Queue Length Information in Network Control ,” IEEE Transactions on Information Theory, September 2011.

61.   Hyang-Won Lee, Long Le, Eytan Modiano, “ Distributed Throughput Maximization in Wireless Networks via Random Power Allocation, ” IEEE Transactions on Mobile Computing, 2011.

60.   Sebastian Neumayer, Gil Zussman, Rueven Cohen, Eytan Modiano, " Assessing the Vulnerability of the Fiber Infrastructure to Disasters, " IEEE/ACM Transactions on Networking, December 2011.

59.   Kayi Lee, Eytan Modiano, Hyang-Won Lee, “ Cross Layer Survivability in WDM-based Networks ,” IEEE/ACM Transactions on Networking, August 2011.

58.   Emily Craparo, Jon How, and Eytan Modiano, “Throughput Optimization in Mobile Backbone Networks,” IEEE Transactions on Mobile Computing, April, 2011.

57.   Hyang-Won Lee, Kayi Lee, and Eytan Modiano, “Diverse Routing in Networks with Probabilistic Failures,” IEEE/ACM Transactions on Networking, December, 2010.

56.   Guner Celik, Gil Zussman, Wajahat Khan and Eytan Modiano, “MAC Protocols For Wireless Networks With Multi-packet Reception Cabaility ,” IEEE Transactions on Mobile Computing, February, 2010.

55.   Atilla Eryilmaz, Asuman Ozdaglar, Devavrat Shah, and Eytan Modiano, “Distributed Cross-Layer Algorithms for the Optimal Control of Multi-hop Wireless Networks,” IEEE/ACM Transactions on Networking, April 2010.

54.   Murtaza Zafer and Eytan Modiano, “Minimum Energy Transmission over a Wireless Channel With Deadline and Power Constraints ,” IEEE Transactions on Automatic Control, pp. 2841-2852, December, 2009.

53.   Murtaza Zafer and Eytan Modiano, “A Calculus Approach to Energy-Efficient Data Transmission with Quality of Service Constraints,” IEEE/ACM Transactions on Networking, 2009.

52.   Anand Srinivas, Gil Zussman, and Eytan Modiano, “Construction and Maintenance of Wireless Mobile Backbone Networks,” IEEE/ACM Transactions on Networking, 2009.

51.   Andrew Brzezinski, Gil Zussman, and Eytan Modiano, “Distributed Throughput Maximization in Wireless Mesh Networks Via Pre-Partitioning,” IEEE/ACM Transactions on Networking, December, 2008.

50.   Amir Khandani, Eytan Modiano, Jinane Abounadi, Lizhong Zheng, “Reliability and Route Diversity in Wireless Networks,” IEEE Transactions on Wireless Communications, December, 2008.

49.   Alessandro Tarello, Jun Sun, Murtaza Zafer and Eytan Modiano, “Minimum Energy Transmission Scheduling Subject to Deadline Constraints,” ACM Wireless Networks, October, 2008.

48.   Murtaza Zafer, Eytan Modiano, “Optimal Rate Control for Delay-Constrained Data Transmission over a Wireless Channel,” IEEE Transactions on Information Theory, September, 2008.

47.   Andrew Brzezinski and Eytan Modiano, “Achieving 100% Throughput In Reconfigurable IP/WDM Networks,” IEEE/ACM Transactions on Networking, August, 2008.

46.   Michael Neely, Eytan Modiano and C. Li, “Fairness and Optimal Stochastic Control for Heterogeneous Networks,” IEEE/ACM Transactions on Networking, September, 2008.

45.   Amir Khandani, Jinane Abounadi, Eytan Modiano, Lizhong Zheng, “Cooperative Routing in Static Wireless Networks,” IEEE Transactions on Communications, November 2007.

44.   Murtaza Zafer, Eytan Modiano, “Joint Scheduling of Rate-guaranteed and Best-effort Users over a Wireless Fading Channel,” IEEE Transactions on Wireless Communications, October, 2007.

43.   Krishna Jagannathan, Sem Borst, Phil Whiting and Eytan Modiano, “Scheduling of Multi-Antenna Broadcast Systems with Heterogeneous Users,” IEEE Journal of Selected Areas in Communications, September, 2007.Amir Khandani, Jinane

42.   Anand Ganti, Eytan Modiano, and John Tsitsiklis, “Optimal Transmission Scheduling in Symmetric Communication Models with Intermittent Connectivity, ” IEEE Transactions on Information Theory, March, 2007.

41.   Michael Neely and Eytan Modiano, “Logarithmic Delay for NxN Packet Switches Under Crossbar Constraints,” IEEE/ACM Transactions on Networking, November, 2007.

40.   Jun Sun, Jay Gao, Shervin Shambayati and Eytan Modiano, “Ka-Band Link Optimization with Rate Adaptation for Mars and Lunar Communications,”   International Journal of Satellite Communications and Networks, March, 2007.

39.   Jun Sun and Eytan Modiano, "Fair Allocation of A Wireless Fading Channel: An Auction Approach" Institute for Mathematics and its Applications, Volume 143: Wireless Communications, 2006.

38.   Jun Sun, Eytan Modiano and Lizhong Zhang, “Wireless Channel Allocation Using An Auction Algorithm,” IEEE Journal on Selected Areas in Communications, May, 2006.

37.   Murtaza Zafer and Eytan Modiano, "Blocking Probability and Channel Assignment for Connection Oriented Traffic in Wireless Networks," IEEE Transactions on Wireless Communications, April, 2006.

36.   Alvin Fu, Eytan Modiano, and John Tsitsiklis, "Optimal Transmission Scheduling over a fading channel with Energy and Deadline Constraints" IEEE Transactions on Wireless Communications, March,2006.

35.   Poompat Saengudomlert, Eytan Modiano and Rober Gallager, “On-line Routing and Wavelength Assignment for Dynamic Traffic in WDM Ring and Torus Networks,” IEEE Transactions on Networking, April, 2006.

34.   Li-Wei Chen, Eytan Modiano and Poompat Saengudomlert, "Uniform vs. Non-Uniform band Switching in WDM Networks," Computer Networks (special issue on optical networks), January, 2006.

33.   Andrew Brzezinski and Eytan Modiano, "Dynamic Reconfiguration and Routing Algorithms for IP-over-WDM networks with Stochastic Traffic," IEEE Journal of Lightwave Technology, November, 2005

32.   Randall Berry and Eytan Modiano, "Optimal Transceiver Scheduling in WDM/TDM Networks," IEEE Journal on Selected Areas in Communications, August, 2005.

31.   Poompat Saengudomlert, Eytan Modiano, and Robert G. Gallager, “Dynamic Wavelength Assignment for WDM All-Optical Tree Networks,” IEEE Transactions on Networking, August, 2005.

30.   Ashwinder Ahluwalia and Eytan Modiano, "On the Complexity and Distributed Construction of Energy Efficient Broadcast Trees in Wireless Ad Hoc Networks," IEEE Transactions on Wireless Communications, October, 2005.

29.   Michael Neely, Charlie Rohrs and Eytan Modiano, "Equivalent Models for Analysis of Deterministic Service Time Tree Networks," IEEE Transactions on Information Theory, October, 2005.

28.   Michael Neely and Eytan Modiano, "Capacity and Delay Tradeoffs for Ad Hoc Mobile Networks," IEEE Transactions on Information Theory, May, 2005.

27.   Li-Wei Chen and Eytan Modiano, "Efficient Routing and Wavelength Assignment for Reconfigurable WDM Networks with Wavelength Converters," IEEE/ACM Transactions on Networking, February, 2005. Selected as one of the best papers from Infocom 2003 for fast-track publication in IEEE/ACM Transactions on Networking.

26.   Michael Neely and Eytan Modiano, "Convexity in Queues with General Inputs," IEEE Transactions on Information Theory, May, 2005.

25.   Anand Srinivas and Eytan Modiano, "Finding Minimum Energy Disjoint Paths in Wireless Ad Hoc Networks," ACM Wireless Networks, November, 2005. Selected to appear in a special issue dedicated to best papers from Mobicom 2003.

24.   Michael Neely, Eytan Modiano and Charlie Rohrs, "Dynamic Power Allocation and Routing for Time-Varying Wireless Networks," IEEE Journal of Selected Areas in Communication, January, 2005.

23.   Chunmei Liu and Eytan Modiano, "On the performance of additive increase multiplicative decrease (AIMD) protocols in hybrid space-terrestrial networks," Computer Networks, September, 2004.

22.   Li-Wei Chen and Eytan Modiano, "Dynamic Routing and Wavelength Assignment with Optical Bypass using Ring Embeddings," Optical Switching and Networking (Elsevier), December, 2004.

21.   Aradhana Narula-Tam, Eytan Modiano and Andrew Brzezinski, "Physical Topology Design for Survivable Routing of Logical Rings in WDM-Based Networks," IEEE Journal of Selected Areas in Communication, October, 2004.

20.   Randall Berry and Eytan Modiano, "'The Role of Switching in Reducing the Number of Electronic Ports in WDM Networks," IEEE Journal of Selected Areas in Communication, October, 2004.

19.   Jun Sun and Eytan Modiano, "Routing Strategies for Maximizing Throughput in LEO Satellite Networks,," IEEE JSAC, February, 2004.

18.   Jun Sun and Eytan Modiano, "Capacity Provisioning and Failure Recovery for Low Earth Orbit Satellite Networks," International Journal on Satellite Communications, June, 2003.

17.   Alvin Fu, Eytan Modiano, and John Tsitsiklis, "Optimal Energy Allocation and Admission Control for Communications Satellites," IEEE Transactions on Networking, June, 2003.

16.   Michael Neely, Eytan Modiano and Charles Rohrs, "Power Allocation and Routing in Multi-Beam Satellites with Time Varying Channels," IEEE Transactions on Networking, February, 2003.

15.   Eytan Modiano and Aradhana Narula-Tam, "Survivable lightpath routing: a new approach to the design of WDM-based networks," IEEE Journal of Selected Areas in Communication, May 2002.

14.   Aradhana Narula-Tam, Phil Lin and Eytan Modiano, "Efficient Routing and Wavelength Assignment for Reconfigurable WDM Networks," IEEE Journal of Selected Areas in Communication, January, 2002.

13.   Brett Schein and Eytan Modiano, "Quantifying the benefits of configurability in circuit-switched WDM ring networks with limited ports per node," IEEE Journal on Lightwave Technology, June, 2001.

12.   Aradhana Narula-Tam and Eytan Modiano, "Dynamic Load Balancing in WDM Packet Networks with and without Wavelength Constraints," IEEE Journal of Selected Areas in Communications, October 2000.

11.   Randy Berry and Eytan Modiano, "Reducing Electronic Multiplexing Costs in SONET/WDM Rings with Dynamically Changing Traffic," IEEE Journal of Selected Areas in Communications, October 2000.

10.   Eytan Modiano and Richard Barry, "A Novel Medium Access Control Protocol for WDM-Based LANs and Access Networks Using a Master-Slave Scheduler," IEEE Journal on Lightwave Technology, April 2000.

9.   Eytan Modiano and Anthony Ephremides, "Communication Protocols for Secure Distributed Computation of Binary Functions," Information and Computation, April 2000.

8.   Angela Chiu and Eytan Modiano, "Traffic Grooming Algorithms for Reducing Electronic Multiplexing Costs in WDM Ring Networks," IEEE Journal on Lightwave Technology, January 2000.

7.   Eytan Modiano, "An Adaptive Algorithm for Optimizing the Packet Size Used in Wireless ARQ Protocols," Wireless Networks, August 1999.

6.   Eytan Modiano, "Random Algorithms for Scheduling Multicast Traffic in WDM Broadcast-and-Select Networks," IEEE Transactions on Networking, July, 1999.

5.   Eytan Modiano and Richard Barry, "Architectural Considerations in the Design of WDM-based Optical Access Networks," Computer Networks, February 1999.

4.   V.W.S. Chan, K. Hall, E. Modiano and K. Rauschenbach, "Architectures and Technologies for High-Speed Optical Data Networks," IEEE Journal of Lightwave Technology, December 1998.

3.   Eytan Modiano and Anthony Ephremides, "Efficient Algorithms for Performing Packet Broadcasts in a Mesh Network," IEEE Transactions on Networking, May 1996.

2.   Eytan Modiano, Jeffrey Wieselthier and Anthony Ephremides, "A Simple Analysis of Queueing Delay in a Tree Network of Discrete-Time Queues with Constant Service Times," IEEE Transactions on Information Theory, February 1996.

1.   Eytan Modiano and Anthony Ephremides, "Communication Complexity of Secure Distributed Computation in the Presence of Noise," IEEE Transactions on Information Theory, July 1992.

Other Papers

5.  Eytan Modiano, "Satellite Data Networks," AIAA Journal on Aerospace Computing, Information and Communication, September, 2004.

4.  Eytan Modiano and Phil Lin, "Traffic Grooming in WDM networks," IEEE Communications Magazine, July, 2001.

3.  Eytan Modiano and Aradhana Narula, "Mechanisms for Providing Optical Bypass in WDM-based Networks," SPIE Optical Networks, January 2000.

2.  K. Kuznetsov, N. M. Froberg, Eytan Modiano, et. al., "A Next Generation Optical Regional Access Networks," IEEE Communications Magazine, January, 2000.

1.  Eytan Modiano, "WDM-based Packet Networks," (Invited Paper) IEEE Communications Magazine, March 1999.

Conference Papers

246. Xinyu Wu, Dan Wu, Eytan Modiano, “ Overload Balancing in Single-Hop Networks With Bounded Buffers ,” IFIP Networking, 2022.

245.  Xinzhe Fu, Eytan Modiano, “ Optimal Routing for Stream Learning Systems ,”  IEEE Infocom, April 2022.

244.  Vishrant Tripathi, Luca Ballotta, Luca Carlone, E. Modiano, “ Computation and Communication Co-Design for Real-Time Monitoring and Control in Multi-Agent Systems ,”  IEEE Wiopt, 2021.

243. Eray Atay, Igor Kadota, E. Modiano, “ Aging Wireless Bandits: Regret Analysis and Order-Optimal Learning Algorithm ,”  IEEE Wiopt 2021.

242. Xinzhe Fu and E. Modiano,  “ Elastic Job Scheduling with Unknown Utility Functions ,” IFIP Performance, Milan, 2021.

241. Bai Liu and E. Modiano, “ Optimal Control for Networks with Unobservable Malicious Nodes ,”  IFIP Performance, Milan, 2021.

240. Bai Liu, Qiaomin Xie,  Eytan Modiano, “ RL-QN:  A Reinforcement Learning Framework for Optimal Control of Queueing Systems ,”  ACM Sigmetrics Workshop on Reinforcement Learning in Networks and Queues (RLNQ), 2021.

239. Xinzhe Fu and E. Modiano,  “ Learning-NUM: Network Utility Maximization with Unknown Utility Functions and Queueing Delay ,  ACM MobiHoc 2021.  

238. Vishrant Tripathi and Eytan Modiano,  “ An Online Learning Approach to Optimizing Time-Varying Costs of AoI ,”  ACM MobiHoc 2021. 

237.   Igor Kadota, Muhammad Shahir Rahman, and Eytan Modiano, " WiFresh: Age-of-Information from Theory to Implementation ,”  International Conference on Computer Communications and Networks (ICCCN), 2021.

236. Vishrant Tripathi and Eytan Modiano, “ Age Debt: A General Framework For Minimizing Age of Information ,”  IEEE Infocom Workshop on Age-of-Information, 2021.

235. Igor Kadota, Eytan Modiano, “ Age of Information in Random Access Networks with Stochastic Arrivals ,” IEEE Infocom, 2020.

234. Igor Kadota, M. Shahir Rahman, Eytan Modiano, Poster: Age of Information in Wireless Networks: from Theory to Implementation , ACM Mobicom, 2020.

233. Xinyu Wu, Dan Wu, Eytan Modiano, “ An Influence Model Approach to Failure Cascade Prediction in Large Scale Power Systems ,” IEEE American Control Conference, July, 2020.

232. X. Fu and E. Modiano, " Fundamental Limits of Volume-based Network DoS Attacks ," Proc. ACM Sigmetrics, Boston, MA, June 2020.

231. Vishrant Tripathi, Eytan Modiano, “ A Whittle Index Approach to Minimizing Functions of Age of Information ,” Allerton Conference on Communication, Control, and Computing, September 2019.

230. Bai Liu, Xiaomin Xie, Eytan Modiano, “ Reinforcement Learning for Optimal Control of Queueing Systems ,” Allerton Conference on Communication, Control, and Computing, September 2019.

229. Rajat Talak, Sertac Karaman, Eytan Modiano, “ A Theory of Uncertainty Variables for State Estimation and Inference ,” Allerton Conference on Communication, Control, and Computing, September 2019.

228. Rajat Talak, Eytan Modiano, “ Age-Delay Tradeoffs in Single Server Systems ,” IEEE International Symposium on Information Theory, Paris, France, July, 2019.

227. Rajat Talak, Sertac Karaman, Eytan Modiano, “ When a Heavy Tailed Service Minimizes Age of Information ,” IEEE International Symposium on Information Theory, Paris, France, July, 2019.

226. Qingkai Liang, Eytan Modiano, “ Optimal Network Control with Adversarial Uncontrollable Nodes ,” ACM MobiHoc, Catania, Italy, June 2019.

225. Igor Kadota, Eytan Modiano, “ Minimizing the Age of Information in Wireless Networks with Stochastic Arrivals ,” ACM MobiHoc, June 2019.

224. Maotong Xu, Jelena Diakonikolas, Suresh Subramaniam, Eytan Modiano, “ A Hierarchical WDM-based Scalable Data Center Network Architecture ,” IEEE International Conference on Communications (ICC), Shanghai, China, June 2019.

223. Maotong Xu, Min Tian, Eytan Modiano, Suresh Subramaniam, " RHODA Topology Configuration Using Bayesian Optimization

222.   Anurag Rai, Rahul Singh and Eytan Modiano, " A Distributed Algorithm for Throughput Optimal Routing in Overlay Networks ,”  IFIP Networking 2019, Warsaw, Poland, May 2019.

221.   Qingkai Liang and Eytan Modiano, " Optimal Network Control in Partially-Controllable Networks ,”  IEEE Infocom, Paris, April 2019.

220.   Xinzhe Fu and Eytan Modiano, " Network Interdiction Using Adversarial Traffic Flows ,”  IEEE Infocom, Paris, April 2019.

219.   Vishrant Tripathi, Rajat Talak, Eytan Modiano, " Age Optimal Information Gathering and Dissemination on Graphs ,”  IEEE Infocom, Paris, April 2019.

218.   Jianan Zhang, Hyang-Won Lee, Eytan Modiano, " On the Robustness of Distributed Computing Networks ,”  DRCN 2019, Coimbra, Portugal, March, 2019.

217.   Hyang-Won Lee, Jianan Zhang and Eytan Modiano, " Data-driven Localization and Estimation of Disturbance in the Interconnected Power System ,”  IEEE Smartgridcomm, October, 2018.

216.   Jianan Zhang and Eytan Modiano, " Joint Frequency Regulation and Economic Dispatch Using Limited Communication ,”  IEEE Smartgridcomm, October, 2018.

215.   Rajat Talak, Sertac Karaman, Eytan Modiano, " Scheduling Policies for Age Minimization in Wireless Networks with Unknown Channel State ,”  IEEE International Symposium on Information Theory, July 2018.

214.   Thomas Stahlbuhk, Brooke Shrader, Eytan Modiano, " Online Learning Algorithms for Minimizing Queue Length Regret ,”  IEEE International Symposium on Information Theory, July 2018.

213.   Rajat Talak, Sertac Karaman, Eytan Modiano, " Distributed Scheduling Algorithms for Optimizing Information Freshness in Wireless Networks ,”  IEEE SPAWC, Kalamata, Greece, June, 2018.

212.   Rajat Talak, Sertac Karaman, Eytan Modiano, " Optimizing Information Freshness in Wireless Networks under General Interference Constraints ,”  ACM MobiHoc 2018, Los Angeles, CA, June 2018.

211.   Thomas Stahlbuhk, Brooke Shrader, Eytan Modiano, " Learning Algorithms for Scheduling in Wireless Networks with Unknown Channel Statistics ,”  ACM MobiHoc, June 2018.

210.   Khashayar Kamran, Jianan Zhang, Edmund Yeh, Eytan Modiano, " Robustness of Interdependent Geometric Networks Under Inhomogeneous Failures ,”  Workshop on Spatial Stochastic Models for Wireless Networks (SpaSWiN), Shanghai, China, May 2018.

209.   Rajat Talak, Sertac Karaman, Eytan Modiano, " Optimizing Age of Information in Wireless Networks with Perfect Channel State Information ,”  Wiopt 2018, Shanghai, China, May 2018.

208.   Abhishek Sinha, Eytan Modiano, " Network Utility Maximization with Heterogeneous Traffic Flows ,”  Wiopt 2018, Shanghai, China, May 2018.

207.   Qingkai Liang, Eytan Modiano, " Minimizing Queue Length Regret Under Adversarial Network Models ,”  ACM Sigmetrics, 2018.

206.   Jianan Zhang, Abhishek Sinha, Jaime Llorca, Anonia Tulino, Eytan Modiano, " Optimal Control of Distributed Computing Networks with Mixed-Cast Traffic Flows ,”  IEEE Infocom, Honolulu, HI, April 2018.

205.   Qingkai Liang, Eytan Modiano, " Network Utility Maximization in Adversarial Environments ,”  IEEE Infocom, Honolulu, HI, April 2018.

204.   Igor Kadota, Abhishek Sinha, Eytan Modiano, " Optimizing Age of Information in Wireless Networks with Throughput Constraints ,”  IEEE Infocom, Honolulu, HI, April 2018.

203.   QIngkai Liang, Verina (Fanyu) Que, Eytan Modiano, " Accelerated Primal-Dual Policy Optimization for Safe Reinforcement Learning ,”  NIPS workshop on “Transparent and interpretable machine learning in safety critical environments,"December 2017.

202.   Rahul Singh, Xueying Guo,Eytan Modiano, " Risk-Sensitive Optimal Control of Queues ,”  IEEE Conference on Decision and Control (CDC), December 2017.

201.   Rajat Talak, Sertac Karaman, Eytan Modiano, " Minimizing Age of Information in Multi-Hop Wireless Networks ,”  Allerton Conference on Communication, Control, and Computing, September 2017.

200.   Abhishek Sinha, Eytan Modiano, " Throughput-Optimal Broadcast in Wireless Networks with Point-to-Multipoint Transmissions ,”  ACM MobiHoc, Madras, India, July 2017.

199.   Rajat Talak, Sertac Karaman, Eytan Modiano, " Capacity and delay scaling for broadcast transmission in highly mobile wireless networks ,”  ACM MobiHoc, Madras, India, July 2017.

198.5 . Y.-P. Hsu, E. Modiano, and L. Duan, " Age of Information: Design and Analysis of Optimal Scheduling Algorithms ,”  IEEE International Symposium on Information Theory (ISIT), 2017.

198.   Qingkai Liang and Eytan Modiano, " Coflow Scheduling in Input-Queued Switches: Optimal Delay Scaling and Algorithms ,”  IEEE Infocom, Atlanta, GA, May 2017.

197.   Jianan Zhang and Eytan Modiano, " Robust Routing in Interdependent Networks ,”  IEEE Infocom, Atlanta, GA, May 2017.

196.   Abhishek Sinha, Eytan Modiano, " Optimal Control for Generalized Network Flow Problems ,”  IEEE Infocom, Atlanta, GA, May 2017.

195.   Rajat Talak*, Sertac Karaman, Eytan Modiano, " Speed Limits in Autonomous Vehicular Networks due to Communication Constraints ,”  IEEE Conference on Decision and Control (CDC), Las Vegas, NV, December 2016.

194.   Marzieh Parandehgheibi*, Konstantin Turitsyn, Eytan Modiano, " Distributed Frequency Control in Power Grids Under Limited Communication ,”  IEEE Conference on Decision and Control (CDC), Las Vegas, NV, December 2016.

193.   Igor Kadota, Elif Uysal-Biyikoglu, Rahul Singh, Eytan Modiano, " Minimizing Age of Information in Broadcast Wireless Networks ,”  Allerton Allerton Conference on Communication, Control, and Computing, September 2016.

192.   Jianan Zhang, Edmund Yeh, Eytan Modiano, " Robustness of Interdependent Random Geometric Networks ,”  Allerton Conference on Communication, Control, and Computing, September 2016.

191.   Abhishek Sinha, Leandros Tassiulas, Eytan Modiano, " Throughput-Optimal Broadcast in Wireless Networks with Dynamic Topology ,”  ACM MobiHoc'16, Paderborn, Germany, July, 2016. (winner of best paper award)

190.   Abishek Sinha, Georgios Paschos, Eytan Modiano, " Throughput-Optimal Multi-hop Broadcast Algorithms ,”  ACM MobiHoc'16, Paderborn, Germany, July, 2016.

189.   Thomas Stahlbuhk, Brooke Shrader, Eytan Modiano, " Throughput Maximization in Uncooperative Spectrum Sharing Networks ,”  IEEE International Symposium on Information Theory, Barcelona, Spain, July 2016.

188.   Thomas Stahlbuhk, Brooke Shrader, Eytan Modiano, " Topology Control for Wireless Networks with Highly-Directional Antennas ,”  IEEE Wiopt, Tempe, Arizona, May, 2016.

187.   Qingkai Liang, H.W. Lee, Eytan Modiano, " Robust Design of Spectrum-Sharing Networks ,”  IEEE Wiopt, Tempe, Arizona, May, 2016.

186.   Hossein Shokri-Ghadikolae, Carlo Fischione and Eytan Modiano, " On the Accuracy of Interference Models in Wireless Communications ,”  IEEE International Conference on Communications (ICC), 2016.

185.   Qingkai Liang and Eytan Modiano, " Survivability in Time-varying Networks ,”  IEEE Infocom, San Francisco, CA, April 2016.

184.   Kyu S. Kim, Chih-Ping Li, Igor Kadota, Eytan Modiano, " Optimal Scheduling of Real-Time Traffic in Wireless Networks with Delayed Feedback ,”  Allerton conference on Communication, Control, and Computing, September 2015.

183.   Marzieh Parandehgheibi, Eytan Modiano, " Modeling the Impact of Communication Loss on the Power Grid Under Emergency Control ,”  IEEE SmartGridComm, Miami, FL, Nov. 2015.

182.   Anurag Rai, Chih-ping Li, Georgios Paschos, Eytan Modiano, " Loop-Free Backpressure Routing Using Link-Reversal Algorithms ,”  Proceedings of the ACM MobiHoc, July 2015.

181.   Longbo Huang, Eytan Modiano, " Optimizing Age of Information in a Multiclass Queueing System ,”  Proceedings of IEEE ISIT 2015, Hong Kong, Jun 2015.

180.   M. Johnston, E. Modiano, " A New Look at Wireless Scheduling with Delayed Information ,”  Proceedings of IEEE ISIT 2015, Hong Kong, June 2015.

179.   M. Johnston, E. Modiano, " Scheduling over Time Varying Channels with Hidden State Information ,”  Proceedings of IEEE ISIT 2015, Hong Kong, June 2015.

178.   M. Johnston and E. Modiano, " Controller Placement for Maximum Throughput Under Delayed CSI ,”  IEEE Wiopt, Mombai, India, May 2015.

177.   A. Sinha, G. Paschos, C. P. Li, and E. Modiano, " Throughput Optimal Broadcast on Directed Acyclic Graphs ,”  IEEE Infocom, Hong Kong, April 2015.

176.   J. Zheng and E. Modiano, " Enhancing Network Robustness via Shielding ,”  IEEE Design of Reliable Communication Networks, Kansas City, March 2015.

175.   H. W. Lee and E. Modiano, " Robust Design of Cognitive Radio Networks ,”  Information and Communication Technology Convergence (ICTC), 2014.

174.   Greg Kuperman and Eytan Modiano, " Disjoint Path Protection in Multi-Hop Wireless Networks with Interference Constraints ,”  IEEE Globecom, Austin, TX, December 2014.

173.   Marzieh Parandehgheibi, Eytan Modiano, David Hay, " Mitigating Cascading Failures in Interdependent Power Grids and Communication Networks ,”  IEEE Smartgridcomm, Venice, Italy, November 2014.

172.   Georgios Paschos and Eytan Modiano, " Throughput optimal routing in overlay networks ,”  Allerton conference on Communication, Control, and Computing, September 2014.

171.   Nathan Jones, George Paschos, Brooke Shrader, Eytan Modiano, " An overlay architecture for Throughput Optimal Multipath Routing ,”  ACM MobiHoc, August 2014.

170.   Matt Johnston, Eytan Modiano, Yuri Polyanskiy, " Opportunistic Scheduling with Limited Channel State Information: A Rate Distortion Approach ,”  IEEE International Symposium on Information Theory, Honolulu, HI, July 2014.

169.   Chih-Ping Li, Georgios Paschos, Eytan Modiano, Leandros Tassiulas, " Dynamic Overload Balancing in Server Farms ,”  Networking 2014, Trondheim, Norway, June, 2014.

168.   Hulya Seferonglu and Eytan Modiano, " TCP-Aware Backpressure Routing and Scheduling ,”  Information Theory and Applications, San Diego, CA, February 2014.

167.   Mihalis Markakis, Eytan Modiano, John Tsitsiklis, " Delay Stability of Back-Pressure Policies in the presence of Heavy-Tailed Traffic ,”  Information Theory and Applications, San Diego, CA, February 2014.

166.   Kyu Soeb Kim, Chih-ping Li, Eytan Modiano, " Scheduling Multicast Traffic with Deadlines in Wireless Networks ,”  IEEE Infocom, Toronto, CA, April 2014.

165.   Georgios Paschos, Chih-ping Li, Eytan Modiano, Kostas Choumas, Thanasis Korakis, " A Demonstration of Multirate Multicast Over an 802.11 Mesh Network ,”  IEEE Infocom, Toronto, CA, April 2014.

164.   Sebastian Neumayer, Eytan Modiano, " Assessing the Effect of Geographically Correlated Failures on Interconnected Power-Communication Networks ,”  IEEE SmartGridComm, 2013.

163.   Marzieh Parandehgheibi, Eytan Modiano, " Robustness of Interdependent Networks: The case of communication networks and the power grid ,”  IEEE Globecom, December 2013.

162.   Matt Johnston, Eytan Modiano, " Optimal Channel Probing in Communication Systems: The Two-Channel Case ,”  IEEE Globecom, December 2013.

161.   Mihalis Markakis, Eytan Modiano, John N. Tsitsiklis, " Delay Analysis of the Max-Weight Policy under Heavy-Tailed Traffic via Fluid Approximations ,”  Allerton Conference, October 2013.

160.   Matthew Johnston, Isaac Keslassy, Eytan Modiano, " Channel Probing in Communication Systems: Myopic Policies Are Not Always Optimal ,”  IEEE International Symposium on Information Theory, July 2013.

159.   Krishna P Jagannathan, Libin Jiang, Palthya Lakshma Naik, Eytan Modiano, " Scheduling Strategies to Mitigate the Impact of Bursty Traffic in Wireless Networks ,”  11th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks Wiopt 2013, Japan, May 2013. (Winner – Best Paper Award).

158.   Hulya Seferoglu and Eytan Modiano, " Diff-Max: Separation of Routing and Scheduling in Backpressure-Based Wireless Networks ,”  IEEE Infocom, Turin, Italy, April 2013.

157.   Chih-Ping Li, Eytan Modiano, " Receiver-Based Flow Control for Networks in Overload ,”  IEEE Infocom, Turin, Italy, April 2013.

156.   Nathan Jones, Brooke Shrader, Eytan Modiano, " Distributed CSMA with Pairwise Coding ,”  IEEE Infocom, Turin, Italy, April 2013.

155.   Greg Kuperman and Eytan Modiano, " Network Protection with Guaranteed Recovery Times using Recovery Domains ,”  IEEE Infocom, Turin, Italy, April 2013.

154.   Greg Kuperman and Eytan Modiano, " Providing Protection in Multi-Hop Wireless Networks ,”  IEEE Infocom, Turin, Italy, April 2013.

153.   Greg Kuperman, Eytan Modiano, Aradhana Narula-Tam, " Network Protection with Multiple Availability Guarantees ,”  IEEE ICC workshop on New Trends in Optical Networks Survivability, June 2012.

152.   Nathaniel Jones, Brooke Shrader, Eytan Modiano, " Optimal Routing and Scheduling for a Simple Network Coding Scheme ,”  IEEE Infocom, Orlando, Fl, March, 2012.

151.   Mihalis Markakis, Eytan Modiano, John Tsitsiklis, " Max-Weight Scheduling in Networks with Heavy-Tailed Traffic ,”  IEEE Infocom, Orlando, Fl, March, 2012.

150.   Guner Celik and Eytan Modiano, " Scheduling in Networks with Time-Varying Channels and Reconfiguration Delay ,”  IEEE Infocom, Orlando, Fl, March, 2012.

149.   Sebastian Neumayer, Alon Efrat, Eytan Modiano, " Geographic Max-Flow and Min-cut Under a Circular Disk Failure Model ,”  IEEE Infocom (MC), Orlando, Fl, March, 2012.

148.   Marzieh Parandehgheibi, Hyang-Won Lee, and Eytan Modiano, " Survivable Paths in Multi-Layer Networks ,”  Conference on Information Science and Systems, March, 2012.

147.   Greg Kuperman, Eytan Modiano, and Aradhana Narula-Tam, " Partial Protection in Networks with Backup Capacity Sharing ,”  Optical Fiber Communications Conference (OFC), Anaheim, CA, March, 2012.

146.   Krishna Jagannathan, Libin Jiang, Eytan Modiano, " On Scheduling Algorithms Robust to Heavy-Tailed Traffic ,”  Information Theory and Applications (ITA), San Diego, CA, February 2012.

145.   M. Johnston, H.W. Lee, E. Modiano, " Robust Network Design for Stochastic Traffic Demands ,”  IEEE Globecom, Next Generation Networking Symposium, Houston, TX, December 2011.

144.   S. Neumayer, E. Modiano, " Network Reliability Under Random Circular Cuts ,”  IEEE Globecom, Optical Networks and Systems Symposium, Houston, TX, December 2011.

143.   H.W. Lee, K. Lee, E. Modiano, " Maximizing Reliability in WDM Networks through Lightpath Routing ,”  IEEE Globecom, Optical Networks and Systems Symposium, Houston, TX, December 2011.

142.   Guner Celik, Sem Borst, Eytan Modiano, Phil Whiting, " Variable Frame Based Max-Weight Algorithms for Networks with Switchover Delay ,”  IEEE International Symposium on Information Theory, St. Petersburgh, Russia, August 2011.

141.   Krishna Jaganathan, Ishai Menache, Eytan Modiano, and Gil Zussman, " Non-cooperative Spectrum Access - The Dedicated vs. Free Spectrum Choice ,”  ACM MOBIHOC'11, May 2011.

140.   Krishna Jagannathan, Shie Mannor, Ishai Menache, Eytan Modiano, " A State Action Frequency Approach to Throughput Maximization over Uncertain Wireless Channels ,”  IEEE Infocom (Mini-conference), Shanghai, China, April 2011.

139.   Guner Celik, Long B. Le, Eytan Modiano, " Scheduling in Parallel Queues with Randomly Varying Connectivity and Switchover Delay ,”  IEEE Infocom (Mini-conference), Shanghai, China, April 2011.

138.   Gregory Kuperman, Eytan Modiano, Aradhana Narula-Tam, " Analysis and Algorithms for Partial Protection in Mesh Networks ,”  IEEE Infocom (Mini-conference), Shanghai, China, April 2011.

137.   Matthew Johnston, Hyang-Won Lee, Eytan Modiano, " A Robust Optimization Approach to Backup Network Design with Random Failures ,”  IEEE Infocom, Shanghai, China, April 2011.

136.   Krishna Jagannathan, Mihalis Markakis, Eytan Modiano, John Tsitsiklis, " Queue Length Asymptotics for Generalized Max-Weight Scheduling in the presence of Heavy-Tailed Traffic ,”  IEEE Infocom, Shanghai, China, April 2011.

135.   Guner Celik and Eytan Modiano, " Dynamic Vehicle Routing for Data Gathering in Wireless Networks ,”  In Proc. IEEE CDC'10, Dec. 2010..***

134.   Long B. Le, Eytan Modiano, Changhee Joo, and Ness B. Shroff, " Longest-queue-first scheduling under the SINR interference model ,”  ACM MobiHoc, September 2010..***

133.   Krishna Jagannathan, Mihalis Markakis, Eytan Modiano, John Tsitsiklis, " Throughput Optimal Scheduling in the Presence of Heavy-Tailed Traffic ,”  Allerton Conference on Communication, Control, and Computing, September 2010..**

132.   Delia Ciullo, Guner Celik, Eytan Modiano, " Minimizing Transmission Energy in Sensor Networks via Trajectory Control ,”  IEEE Wiopt 2010, Avignon, France, June 2010, (10 pages; CD proceedings – page numbers not available).

131.   Sebastian Neumayer and Eytan Modiano, " Network Reliability with Geographically Correlated Failures ,”  IEEE Infocom 2010, San Diego, CA, March 2010, (9 pages; CD proceedings – page numbers not available).**

130.   Long Le, Eytan Modiano, Ness Shroff, " Optimal Control of Wireless Networks with Finite Buffers ,”  IEEE Infocom 2010, San Diego, CA, March 2010, (9 pages; CD proceedings – page numbers not available).

129.   Kayi Lee, Hyang-Won Lee, Eytan Modiano, " Reliability in Layered Network with Random Link Failures ,”  IEEE Infocom 2010, San Diego, CA, March 2010, (9 pages; CD proceedings – page numbers not available).**

128.   Krishna Jagannathan, Eytan Modiano, " The Impact of Queue length Information on Buffer Overflow in Parallel Queues ,”  Allerton Conference on Communication, Control, and Computing, September 2009, pgs. 1103 -1110 **

127.   Mihalis Markakis, Eytan Modiano, John Tsitsiklis, " Scheduling Policies for Single-Hop with Heavy-Tailed Traffic ,”  Allerton Conference on Communication, Control, and Computing, September 2009, pgs. 112 – 120..**

126.   Dan Kan, Aradhana Narula-Tam, Eytan Modiano, " Lightpath Routing and Capacity Assignment for Survivable IP-over-WDM Networks ,”  DRCN 2009, Alexandria, VA October 2009, pgs. 37 -44..**

125.   Mehdi Ansari, Alireza Bayesteh, Eytan Modiano, " Opportunistic Scheduling in Large Scale Wireless Networks ,”  IEEE International Symposium on Information Theory, Seoul, Korea, June 2009, pgs. 1624 – 1628.

124.   Hyang-Won Lee, Eytan Modiano and Long Bao Le, " Distributed Throughput Maximization in Wireless Networks via Random Power Allocation ,”  IEEE Wiopt, Seoul, Korea, June 2009. (9 pages; CD proceedings – page numbers not available).

123.   Wajahat Khan, Eytan Modiano, Long Le, " Autonomous Routing Algorithms for Networks with Wide-Spread Failures ,”  IEEE MILCOM, Boston, MA, October 2009. (6 pages; CD proceedings – page numbers not available).**

122.   Guner Celik and Eytan Modiano, " Random Access Wireless Networks with Controlled Mobility ,”  IEEE Med-Hoc-Nets, Haifa, Israel, June 2009, pgs. 8 – 14.**

121.   Hyang-Won Lee and Eytan Modiano, " Diverse Routing in Networks with Probabilistic Failures ,”  IEEE Infocom, April 2009, pgs. 1035 – 1043.

120.   Kayi Lee and Eytan Modiano, " Cross-layer Survivability in WDM-based Networks ,”  IEEE Infocom, April 2009, pgs. 1017 -1025..**

119.   Krishna Jagannathan, Eytan Modiano, Lizhong Zheng, " On the Trade-off between Control Rate and Congestion in Single Server Systems ,”  IEEE Infocom, April 2009, pgs. 271 – 279.**

118.   Sebastian Neumayer, Gil Zussman, Rueven Cohen, Eytan Modiano, " Assessing the Vulnerability of the Fiber Infrastructure to Disasters ,”  IEEE Infocom, April 2009, pgs. 1566 – 1574.**

117.   Long Le, Krishna Jagannathan and Eytan Modiano, " Delay analysis of max-weight scheduling in wireless ad hoc networks ,”  Conference on Information Science and Systems, Baltimore, MD, March, 2009, pgs. 389 – 394.**

116.   Krishna Jagannathan, Eytan Modiano, Lizhong Zheng, " Effective Resource Allocation in a Queue: How Much Control is Necessary? ,”  Allerton Conference on Communication, Control, and Computing, September 2008, pgs. 508 – 515.**

115.   Sebastian Neumayer, Gil Zussman, Rueven Cohen, Eytan Modiano, " Assessing the Impact of Geographically Correlated Network Failures ,”  IEEE MILCOM, November 2008. (6 pages; CD proceedings – page numbers not available).**

114.   Emily Craparo, Jonathan P. How, and Eytan Modiano, " Simultaneous Placement and Assignment for Exploration in Mobile Backbone Networks ,”  IEEE conference on Decision and Control (CDC), November 2008, pgs. 1696 – 1701 **

113.   Anand Srinivas and Eytan Modiano, " Joint node placement and assignment for throughput optimization in mobile backbone networks ,”  IEEE INFOCOM'08, pp. 1130 – 1138, Phoenix, AZ, Apr. 2008, pgs. 1130 – 1138.**

112.   Guner Celik, Gil Zussman, Wajahat Khan and Eytan Modiano, " MAC for Networks with Multipacket Reception Capability and Spatially Distributed Nodes ,”  IEEE INFOCOM'08, Phoenix, AZ, Apr. 2008, pgs. 1436 – 1444.**

111.   Gil Zussman, Andrew Brzezinski, and Eytan Modiano, " Multihop Local Pooling for Distributed Throughput Maximization in Wireless Networks ,”  IEEE INFOCOM'08, Phoenix, AZ, Apr. 2008, pgs 1139 – 1147.**

110.   Emily Craparo, Jonathan How and Eytan Modiano, " Optimization of Mobile Backbone Networks: Improved Algorithms and Approximation ,”  IEEE American Control Conference, Seattle, WA, June 2008, pgs. 2016 – 2021.**

109.   Atilla Eryilmaz, Asuman Ozdaglar, Devavrat Shah, Eytan Modiano, " Imperfect Randomized Algorithms for the Optimal Control of Wireless Networks ,”  Conference on Information Science and Systems, Princeton, NJ, March, 2008, pgs. 932 – 937.

108.   Anand Srinivas and Eytan Modiano, " Optimal Path Planning for Mobile Backbone Networks ,”  Conference on Information Science and Systems, Princeton, NJ, March, 2008, pgs. 913 – 918.

107.   Kayi Lee and Eytan Modiano, " Cross-layer Survivability in WDM Networks with Multiple Failures ,”  IEEE Optical Fiber Communications Conference, San Diego, CA February, 2008 (3 pages; CD proceedings – page numbers not available).

106.   Andrew Brzezinski, Gil Zussman and Eytan Modiano, " Local Pooling Conditions for Joint Routing and Scheduling ,”  Workshop on Information Theory and Applications, pp. 499 – 506, La Jolla, CA, January, 2008, pgs. 499 – 506.

105.   Murtaza Zafer and Eytan Modiano, " Minimum Energy Transmission over a Wireless Fading Channel with Packet Deadlines ,”  Proceedings of IEEE Conference on Decision and Control (CDC), New Orleans, LA, December, 2007, pgs. 1148 – 1155.**

104.   Atilla Eryilmaz, Asuman Ozdaglar, Eytan Modiano, " Polynomial Complexity Algorithms for Full Utilization of Multi-hop Wireless Networks ,”  IEEE Infocom, Anchorage, AK, April, 2007, pgs. 499 – 507.

103.   Murtaza Zafer and Eytan Modiano, " Delay Constrained Energy Efficient Data Transmission over a Wireless Fading Channel ,”  Workshop on Information Theory and Application, University of California, San Diego, CA, February, 2007, pgs. 289 – 298.**

102.   Atilla Eryilmaz, Eytan Modiano, Asuman Ozdaglar, " Randomized Algorithms for Throughput-Optimality and Fairness in Wireless Networks ,”  Proceedings of IEEE Conference on Decision and Control (CDC), San Diego, CA, December, 2006, pgs. 1936 – 1941.

101.   Anand Srinivas, Gil Zussman, and Eytan Modiano, " Distributed Mobile Disk Cover - A Building Block for Mobile Backbone Networks ,”  Proc. Allerton Conf. on Communication, Control, and Computing, Allerton, IL, September 2006, (9 pages; CD proceedings – page numbers not available).**

100.   Krishna Jagannathan, Sem Borst, Phil Whiting, Eytan Modiano, " Scheduling of Multi-Antenna Broadcast Systems with Heterogeneous Users ,”  Allerton Conference on Communication, Control and Computing, Allerton, IL, September 2006, (10 pages; CD proceedings – page numbers not available).**

99.   Andrew Brzezinski, Gil Zussman, and Eytan Modiano, " Enabling Distributed Throughput Maximization in Wireless Mesh Networks - A Partitioning Approach ,”  Proceedings of ACM MOBICOM'06, Los Angeles, CA, Sep. 2006, (12 pages; CD proceedings – page numbers not available).**

98.   Eytan Modiano, Devavrat Shah, and Gil Zussman, " Maximizing Throughput in Wireless Networks via Gossiping ,”  Proc. ACM SIGMETRICS / IFIP Performance'06, Saint-Malo, France, June 2006, (12 pages; CD proceedings – page numbers not available). (best paper award)

97.   Anand Srinivas, Gil Zussman, and Eytan Modiano, " Mobile Backbone Networks – Construction and Maintenance ,”  Proc. ACM MOBIHOC'06, Florence, Italy, May 2006, (12 pages; CD proceedings – page numbers not available).**

96.   Andrew Brzezinski and Eytan Modiano, " Achieving 100% throughput in reconfigurable optical networks ,”  IEEE INFOCOM 2006 High-Speed Networking Workshop, Barcelona, Spain, April 2006, (5 pages; CD proceedings – page numbers not available).**

95.   Krishna P. Jagannathan, Sem Borst, Phil Whiting, Eytan Modiano, " Efficient scheduling of multi-user multi-antenna systems ,”  Proceedings of WiOpt 2006, Boston, MA, April 2006, (8 pages; CD proceedings – page numbers not available).**

94.   Andrew Brzezinski and Eytan Modiano, " Greedy weighted matching for scheduling the input-queued switch ,”  Conference on Information Sciences and Systems (CISS), Princeton, NJ, March 2006, pgs. 1738 – 1743.**

93.   Murtaza Zafer and Eytan Modiano, " Optimal Adaptive Data Transmission over a Fading Channel with Deadline and Power Constraints ,”  Conference on Information Sciences and Systems (CISS), Princeton, New Jersey, March 2006, pgs. 931 – 937.**

92.   Li-Wei Chen and E. Modiano, " A Geometric Approach to Capacity Provisioning in WDM Networks with Dynamic Traffic ,”  Conference on Information Science and Systems (CISS), Princeton, NJ, March, 2006, pgs. 1676 – 1683, **

91.   Jun Sun and Eytan Modiano, " Channel Allocation Using Pricing in Satellite Networks ,”  Conference on Information Science and Systems (CISS), Princeton, NJ, March, 2006, pgs. 182 – 187.**

90.   Jun Sun, Jay Gao, Shervin Shambayatti and Eytan Modiano, " Ka-Band Link Optimization with Rate Adaptation ,”  IEEE Aerospace Conference, Big Sky, MN, March, 2006. (7 pages; CD proceedings – page numbers not available).

89.   Alessandro Tarello, Eytan Modiano and Jay Gao, " Energy efficient transmission scheduling over Mars proximity links ,”  IEEE Aerospace Conference, Big Sky, MN, March, 2006. (10 pages; CD proceedings – page numbers not available).

88.   A. Brzezinski and E. Modiano, " RWA decompositions for optimal throughput in reconfigurable optical networks ,”  INFORMS Telecommunications Conference, Dallas, TX, March 2006 (3 pages; CD proceedings – page numbers not available).**

87.   Li Wei Chen and E. Modiano, " Geometric Capacity Provisioning for Wavelength Switched WDM Networks ,”  Workshop on Information Theory and Application, University of California, San Diego, CA, February, 2006. (8 pages; CD proceedings – page numbers not available).**

86.   Murtaza Zafer and Eytan Modiano, " Joint Scheduling of Rate-guaranteed and Best-effort Services over a Wireless Channel ,”  IEEE Conference on Decision and Control, Seville, Spain, December, 2005, pgs. 6022–6027.**

85.   Jun Sun and Eytan Modiano, " Opportunistic Power Allocation for Fading Channels with Non-cooperative Users and Random Access ,”  IEEE BroadNets – Wireless Networking Symposium, Boston, MA, October, 2005, pgs. 397–405.**

84.   Li Wei Chen and Eytan Modiano, " Uniform vs. Non-uniform Band Switching in WDM Networks ,”  IEEE BroadNets-Optical Networking Symposium, Boston, MA, October, 2005, pgs. 219– 228.**

83.   Sonia Jain and Eytan Modiano, " Buffer Management Schemes for Enhanced TCP Performance over Satellite Links ,”  IEEE MILCOM, Atlantic City, NJ, October 2005 (8 pages; CD proceedings – page numbers not available).**

82.   Murtaza Zafer and Eytan Modiano, " Continuous-time Optimal Rate Control for Delay Constrained Data Transmission ,”  Allerton Conference on Communications, Control and Computing, Allerton, IL, September, 2005 (10 pages; CD proceedings – page numbers not available).**

81.   Alessandro Tarello, Eytan Modiano, Jun Sun, Murtaza Zafer, " Minimum Energy Transmission Scheduling subject to Deadline Constraints ,”  IEEE Wiopt, Trentino, Italy, April, 2005, pgs. 67–76. (Winner of best student paper award).**

80.   Amir Khandani, Eytan Modiano, Jinane Abounadi, Lizhong Zheng, " Reliability and Route Diversity in Wireless Networks ,”  Conference on Information Science and System, Baltimore, MD, March, 2005, (8 pages; CD proceedings – page numbers not available).**

79.   Andrew Brzezinski, Iraj Saniee, Indra Widjaja, Eytan Modiano, " Flow Control and Congestion Management for Distributed Scheduling of Burst Transmissions in Time-Domain Wavelength Interleaved Networks ,”  IEEE/OSA Optical Fiber Conference (OFC), Anaheim, CA, March, 2005, pgs. WC4-1–WC4-3.

78.   Andrew Brzezinski and Eytan Modiano, " Dynamic Reconfiguration and Routing Algorithms for IP-over-WDM Networks with Stochastic Traffic ,”  IEEE Infocom 2005, Miami, FL, March, 2005, pgs. 6–11.**

77.   Murtaza Zafer and Eytan Modiano, " A Calculus Approach to Minimum Energy Transmission Policies with Quality of Service Guarantees ,”  IEEE Infocom 2005, Miami, FL, March, 2005, pgs. 548–559.**

76.   Michael Neely and Eytan Modiano, " Fairness and optimal stochastic control for heterogeneous networks ,”  IEEE Infocom 2005, Miami, FL, March, 2005, pgs. 1723 – 1734.**

75.   Aradhana Narula-Tam, Thomas G. Macdonald, Eytan Modiano, and Leslie Servi, " A Dynamic Resource Allocation Strategy for Satellite Communications ,”  IEEE MILCOM, Monterey, CA, October, 2004, pgs. 1415 – 1421.

74.   Li-Wei Chen, Poompat Saengudomlert and Eytan Modiano, " Optimal Waveband Switching in WDM Networks ,”  IEEE International Conference on Communication (ICC), Paris, France, June, 2004, pgs. 1604 – 1608.**

73.   Michael Neely and Eytan Modiano, " Logarithmic Delay for NxN Packet Switches ,”  IEEE Workshop on High performance Switching and Routing (HPSR 2004), Phoenix, AZ, April, 2004, pgs. 3–9.**

72.   Li-Wei Chen and Eytan Modiano, " Dynamic Routing and Wavelength Assignment with Optical Bypass using Ring Embeddings ,”  IEEE Workshop on High performance Switching and Routing (HPSR 2004), Phoenix, Az, April, 2004, pgs. 119–125.**

71.   Randall Berry and Eytan Modiano, " On the Benefits of Tunability in Reducing Electronic Port Counts in WDM/TDM Networks ,”  IEEE Infocom, Hong Kong, March 2004, pgs. 1340–1351.

70.   Andrew Brzezinski and Eytan Modiano, " A new look at dynamic traffic scheduling in WDM networks with transceiver tuning latency ,”  Informs Telecommunications Conference, Boca Raton, FL, March 2004, pgs. 25–26.**

69.   Chunmei Liu and Eytan Modiano, " Packet Scheduling with Window Service Constraints ,”  Conference on Information Science and System, Princeton, NJ, March, 2004, pgs. 178–184.**

68.   Jun Sun, Eytan Modiano, and Lizhong Zheng, " A Novel Auction Algorithm for Fair Allocation of a Wireless Fading Channel ,”  Conference on Information Science and System, Princeton, NJ, March, 2004, pgs. 1377–1383.**

67.   Murtaza Zafer and Eytan Modiano, " Impact of Interference and Channel Assignment on Blocking Probability in Wireless Networks ,”  Conference on Information Science and System, Princeton, NJ, March, 2004, pgs. 430–436.**

66.   Chunmei Liu and Eytan Modiano, " An Analysis of TCP over Random Access Satellite Links ,”  IEEE Wireless Communications and Networking Conference (WCNC), Atlanta, GA, February, 2004, pgs. 2033–2040..**

65.   Randall Berry and Eytan Modiano, " Using tunable optical transceivers for reducing the number of ports in WDM/TDM Networks ,”  IEEE/OSA Optical Fiber Conference (OFC), Los Angeles, CA, February, 2004, pgs. 23–27.

64.   Aradhana Narula-Tam, Eytan Modiano and Andrew Brzezinski, " Physical Topology Design for Survivable Routiing of Logical Rings in WDM-based Networks ,”  IEEE Globecom, San francisco, CA, December, 2003, pgs. 2552–2557.

63.   Jun Sun, Lizhong Zheng and Eytan Modiano, " Wireless Channel Allocation Using an Auction Algorithm ,”  Allerton Conference on Communications, Control and Computing, October, 2003, pgs. 1114–1123..**

62.   Amir Khandani, Jinane Abounadi, Eytan Modiano, Lizhong Zhang, " Cooperative Routing in Wireless Networks ,”  Allerton Conference on Communications, Control and Computing, October, 2003, pgs. 1270–1279.**

61.   Poompat Saengudomlert, Eytan Modiano and Robert Gallager, " Dynamic Wavelength Assignment for WDM all optical Tree Networks ,”  Allerton Conference on Communications, Control and Computing, October, 2003, 915–924.**

60.   Aradhana Narula-Tam and Eytan Modiano, " Designing Physical Topologies that Enable Survivable Routing of Logical Rings ,”  IEEE Workshop on Design of Reliable Communication Networks (DRCN), October, 2003, pgs. 379–386.

59.   Anand Srinivas and Eytan Modiano, " Minimum Energy Disjoint Path Routing in Wireless Ad Hoc Networks ,”  ACM Mobicom, San Diego, Ca, September, 2003, pgs. 122–133.**

58.   Michael Neely and Eytan Modiano, " Improving Delay in Ad-Hoc Mobile Networks Via Redundant Packet Transfers ,”  Conference on Information Science and System, Baltimore, MD, March, 2003 (6 pages; CD proceedings – page numbers not available).**

57.   Michael Neely, Eytan Modiano and Charles Rohrs, " Dynamic Power Allocation and Routing for Time Varying Wireless Networks ,”  IEEE Infocom 2003, San Francisco, CA, April, 2003, pgs. 745–755.**

56.   Alvin Fu, Eytan Modiano, and John Tsitsiklis, " Optimal Energy Allocation for Delay-Constrained Data Transmission over a Time-Varying Channel ,”  IEEE Infocom 2003, San Francisco, CA, April, 2003, pgs. 1095–1105.**

55.   Poompat Saengudomlert, Eytan Modiano and Rober Gallager, " On-line Routing and Wavelength Assignment for Dynamic Traffic in WDM Ring and Torus Networks ,”  IEEE Infocom 2003, San Francisco, CA, April, 2003, pgs. 1805–1815.**

54.   Li-Wei Chen and Eytan Modiano, " Efficient Routing and Wavelength Assignment for Reconfigurable WDM Networks with Wavelength Converters ,”  IEEE Infocom 2003, San Francisco, CA, April, 2003, pgs. 1785–1794. Selected as one of the best papers of Infocom 2003 for fast track publication in IEEE/ACM Transactions on Networking.**

53.   Mike Neely, Jun Sun and Eytan Modiano, " Delay and Complexity Tradeoffs for Dynamic Routing and Power Allocation in a Wireless Network ,”  Allerton Conference on Communication, Control, and Computing, Allerton, Illinois, October, 2002, pgs. 157 –159.**

52.   Anand Ganti, Eytan Modiano and John Tsitsiklis, " Transmission Scheduling for Multi-Channel Satellite and Wireless Networks ,”  Allerton Conference on Communication, Control, and Computing, Allerton, Illinois, October, 2002, pgs. 1318–1327.**

51.   Poompat Saengudomlert, Eytan Modiano, and Robert G. Gallager, " Optimal Wavelength Assignment for Uniform All-to-All Traffic in WDM Tree Networks ,”  Allerton Conference on Communication, Control, and Computing, Allerton, Illinois, October, 2002, pgs. 528–537.**

50.   Hungjen Wang, Eytan Modiano and Muriel Medard, " Partial Path Protection for WDM Networks: End-to-End Recovery Using Local Failure Information ,”  IEEE International Symposium on Computer Communications (ISCC), Taormina, Italy, July 2002, pgs. 719–725.**

49.   Jun Sun and Eytan Modiano, " Capacity Provisioning and Failure Recovery in Mesh-Torus Networks with Application to Satellite Constellations ,”  IEEE International Symposium on Computer Communications (ISCC), Taormina, Italy, July 2002, pgs. 77–84.**

48.   Alvin Fu, Eytan Modiano, and John Tsitsiklis, " Optimal Energy Allocation and Admission Control for Communications Satellites ,”  IEEE INFOCOM 2002, New York, June, 2002, pgs. 648–656.**

47.   Michael Neely, Eytan Modiano and Charles Rohrs, " Power and Server Allocation in a Multi-Beam Satellite with Time Varying Channels ,”  IEEE INFOCOM 2002, New York, June, 2002, pgs. 1451–1460..**

46.   Mike Neely, Eytan Modiano and Charles Rohrs, " Tradeoffs in Delay Guarantees and Computation Complexity for N x N Packet Switches ,”  Conference on Information Science and Systems, Princeton, NJ, March, 2002, pgs. 136–148.**

45.   Alvin Fu, Eytan Modiano and John Tsitsiklis, " Transmission Scheduling Over a Fading Channel with Energy and Deadline Constraints ,”  Conference on Information Science and System, Princeton, NJ, March, 2002, pgs. 1018–1023.**

44.   Chunmei Liu and Eytan Modiano, " On the Interaction of Layered Protocols: The Case of Window Flow Control and ARQ ,”  Conference on Information Science and System, Princeton, NJ, March, 2002, pgs. 118–124.**

43.   Mike Neely, Eytan Modiano and Charles Rohrs, " Packet Routing over Parallel Time-varying Queues with Application to Satellite and Wireless Networks ,”  Conference on Information Science and System, Princeton, NJ, March, 2002, pgs. 360–366.**

42.   Ahluwalia Ashwinder, Eytan Modiano and Li Shu, " On the Complexity and Distributed Construction of Energy Efficient Broadcast Trees in Static Ad Hoc Wireless Networks ,”  Conference on Information Science and System, Princeton, NJ, March, 2002, pgs. 807–813.**

41.   Jun Sun and Eytan Modiano, " Capacity Provisioning and Failure Recovery for Satellite Constellations ,”  Conference on Information Science and System, Princeton, NJ, March, 2002, pgs. 1039–1045.**

40.   Eytan Modiano, Hungjen Wang, and Muriel Medard, " Partial Path Protection for WDM networks ,”  Informs Telecommunications Conference, Boca Raton, FL, March 2002, pgs. 78–79.**

39.   Poompat Saengudomlert, Eytan H. Modiano, and Robert G. Gallager, " An On-Line Routing and Wavelength Assignment Algorithm for Dynamic Traffic in a WDM Bidirectional Ring ,”  Joint Conference on Information Sciences (JCIS), Durham, North Carolina, March, 2002, pgs. 1331–1334.**

38.   Randy Berry and Eytan Modiano, " Switching and Traffic Grooming in WDM Networks ,”  Joint Conference on Information Sciences (JCIS), Durham, North Carolina, March, 2002, pgs. 1340–1343.

37.   Eytan Modiano, Hungjen Wang, and Muriel Medard, " Using Local Information for WDM Network Protection ,”  Joint Conference on Information Sciences (JCIS), Durham, North Carolina, March, 2002, pgs. 1398–1401.**

36.   Aradhana Narula-Tam and Eytan Modiano, " Network architectures for supporting survivable WDM rings ,”  IEEE/OSA Optical Fiber Conference (OFC) 2002, Anaheim, CA, March, 2002, pgs. 105–107.

35.   Michael Neely, Eytan Modiano, Charles Rohrs, " Packet Routing over Parallel Time-Varying Queues with Application to Satellite and Wireless Networks ,”  Allerton Conference on Communication, Control, and Computing, Allerton, Illinois, September, 2001, pgs. 1110-1111.**

34.   Eytan Modiano and Randy Berry, " The Role of Switching in Reducing Network Port Counts ,”  Allerton Conference on Communication, Control, and Computing, Allerton, Illinois, September, 2001, pgs. 376-385.

33.   Eytan Modiano, " Resource allocation and congestion control in next generation satellite networks ,”  IEEE Gigabit Networking Workshop (GBN 2001), Anchorage, AK, April 2001, (2 page summary-online proceedings).

32.   Eytan Modiano and Aradhana Narula-Tam, " Survivable Routing of Logical Topologies in WDM Networks ,”  IEEE Infocom 2001, Anchorage, AK, April 2001, pgs. 348–357.

31.   Michael Neely and Eytan Modiano, " Convexity and Optimal Load Distribution in Work Conserving */*/1 Queues ,”  IEEE Infocom 2001, Anchorage, AK, April 2001, pgs. 1055–1064.

30.   Eytan Modiano and Randy Berry, " Using Grooming Cross- Connects to Reduce ADM Costs in Sonet/WDM Ring Networks ,”  IEEE/OSA Optical Fiber Conference (OFC) 2001, Anaheim, CA March 2001, pgs. WL1- WL3.

29.   Eytan Modiano and Aradhana Narula-Tam, " Designing Survivable Networks Using Effective Rounting and Wavelenght Assignment (RWA) ,”  IEEE/OSA Optical Fiber Conference (OFC) 2001, Anaheim, CA March 2001, pgs. TUG5-1 – TUG5– 3.

28.   Roop Ganguly and Eytan Modiano, " Distributed Algorithms and Architectures for Optical Flow Switching in WDM networks ,”  IEEE International Symposium on Computer Communications (ISCC 2000), Antibes, France, July 2000, pgs. 134–139.

27.   Aradhana Narula-Tam, Philip J. Lin and Eytan Modiano, " Wavelength Requirements for Virtual topology Reconfiguration in WDM Ring Networks ,”  IEEE International Conference on Communications (ICC 2000), New Orleans, LA, June 2000, pgs. 1650–1654.

26.   Eytan Modiano, "Optical Flow Switching for the Next Generation Internet,”  IEEE Gigabit Networking Workshop (GBN 2000), Tel-aviv, March 2000 (2 page summary-online proceedings).

25.   Aradhana Narula and Eytan Modiano, " Dynamic Reconfiguration in WDM Packet Networks with Wavelength Limitations ,”  IEEE/OSA Optical Fiber Conference (OFC) 2000, Baltimore, MD, March, 2000, pgs. 1210–1212.

24.   Brett Schein and Eytan Modiano, " Quantifying the benefits of configurability in circuit-switched WDM ring networks ,”  IEEE Infocom 2000, Tel Aviv, Israel, April, 2000, pgs.1752–1760..***

23.   Aradhana Narula-Tam and Eytan Modiano, " Load Balancing Algorithms for WDM-based IP networks ,”  IEEE Infocom 2000, Tel Aviv, Israel, April, 2000, pgs. 1010–1019.

22.   Nan Froberg, M. Kuznetsov, E. Modiano, et. al., " The NGI ONRAMP test bed: Regional Access WDM technology for the Next Generation Internet ,”  IEEE LEOS ’99, October, 1999, pgs. 230–231.

21.   Randy Berry and Eytan Modiano, " Minimizing Electronic Multiplexing Costs for Dynamic Traffic in Unidirectional SONET Ring Networks ,”  IEEE International Conference on Communications (ICC ’99), Vancouver, CA, June 1999, pgs. 1724–1730..***

20.   Brett Schein and Eytan Modiano, "Increasing Traffic Capacity in WDM Ring Networks via Topology Reconfiguration,”  Conference on Information Science and Systems, Baltimore, MD, March 1999, pgs. 201 – 206.

19.   Eytan Modiano and Richard Barry, " Design and Analysis of an Asynchronous WDM Local Area Network Using a Master/Slave Scheduler ,”  IEEE Infocom ’99, New York, NY, March 1999, pgs. 900–907.

18.   Randy Berry and Eytan Modiano, " Grooming Dynamic Traffic in Unidirectional SONET Ring Networks ,”  IEEE/OSA Optical Fiber Conference (OFC) ’99, San Diego, CA, February 1999, pgs. 71–73.

17.   Angela Chiu and Eytan Modiano, " Reducing Electronic Multiplexing Costs in Unidirectional SONET/WDM Ring Networks Via Efficient Traffic Grooming ,”  IEEE Globecom '98, Sydney, Australia, November 1998, pgs. 322–327.

16.   Eytan Modiano, " Throughput Analysis of Unscheduled Multicast Transmissions in WDM Broadcast-and-Select Networks ,”  IEEE International Symposium on Information Theory, Boston, MA, September 1998, pg. 167.

15.   Eytan Modiano and Angela Chiu, "Traffic Grooming Algorithms for Minimizing Electronic Multiplexing Costs in Unidirectional SONET/WDM Ring Networks,”  Conference on Information Science and Systems, Princeton, NJ, March 1998, 653–658.

14.   Eytan Modiano and Eric Swanson, " An Architecture for Broadband Internet Services over a WDM-based Optical Access Network ,”  IEEE Gigabit Networking Workshop (GBN '98), San Francisco, CA, March 1998 (2 page summary-online proceedings).

13.   Eytan Modiano, " Unscheduled Multicasts in WDM Broadcast-and-Select Networks ,”  IEEE Infocom '98, San Francisco, CA, March 1998, pgs. 86–93.

12.   Eytan Modiano, Richard Barry and Eric Swanson, " A Novel Architecture and Medium Access Control (MAC) protocol for WDM Networks ,”  IEEE/OSA Optical Fiber Conference (OFC) '98, San Jose, CA, February 1998, pgs. 90–91.

11.   Eytan Modiano, " Scheduling Algorithms for Message Transmission Over a Satellite Broadcast System ,”  IEEE MILCOM 97, Monterey, CA, November 1997, pgs. 628–634.

10.   Eytan Modiano, " Scheduling Packet Transmissions in A Multi-hop Packet Switched Network Based on Message Length ,”  IEEE International Conference on Computer Communications and Networks (IC3N) Las Vegas, Nevada, September 1997, pgs. 350–357.

9.   Eytan Modiano, "A Simple Algorithm for Optimizing the Packet Size Used in ARQ Protocols Based on Retransmission History,”  Conference on Information Science and Systems, Baltimore, MD, March 1997, pgs. 672–677.

8.   Eytan Modiano, " A Multi-Channel Random Access Protocol for the CDMA Channel ,”  IEEE PIMRC '95, Toronto, Canada, September 1995, pgs. 799–803.

7.   Eytan Modiano Jeffrey Wieselthier and Anthony Ephremides, " A Simple Derivation of Queueing Delay in a Tree Network of Discrete-Time Queues with Deterministic Service Times ,”  IEEE International Symposium on Information Theory, Trondheim, Norway, June 1994, pg. 372.

6.   Eytan Modiano, Jeffrey Wieselthier and Anthony Ephremides, "An Approach for the Analysis of Packet Delay in an Integrated Mobile Radio Network,”  Conference on Information Sciences and Systems, Baltimore, MD, March 1993, pgs. 138-139.

5.   Eytan Modiano and Anthony Ephremides, " A Method for Delay Analysis of Interacting Queues in Multiple Access Systems ,”  IEEE INFOCOM 1993, San Francisco, CA, March 1993, pgs. 447 – 454.

4.   Eytan Modiano and Anthony Ephremides, " A Model for the Approximation of Interacting Queues that Arise in Multiple Access Schemes ,”  IEEE International Symposium on Information Theory, San Antonio, TX, January 1993, pg. 324.

3.   Eytan Modiano and Anthony Ephremides, " Efficient Routing Schemes for Multiple Broadcasts in a Mesh ,”  Conference on Information Sciences and Systems, Princeton, NJ, March 1992, pgs. 929 – 934.

2.   Eytan Modiano and Anthony Ephremides, " On the Secrecy Complexity of Computing a Binary Function of Non-uniformly Distributed Random Variables ,”  IEEE International Symposium on Information Theory, Budapest, Hungary, June 1991, pg. 213.

1.   Eytan Modiano and Anthony Ephremides, "Communication Complexity of Secure Distributed Computation in the Presence of Noise,”  IEEE International Symposium on Information Theory, San Diego, CA, January 1990, pg. 142.

Book Chapters

  • Hyang-Won Lee, Kayi Lee, Eytan Modiano, " Cross-Layer Survivability " in Cross-Layer Design in Optical Networks, Springer, 2013.
  • Li-Wei Chen and Eytan Modiano, " Geometric Capacity Provisioning for Wavelength-Switched WDM Networks ," Chapter in Computer Communications and Networks Series: Algorithms for Next Generation Networks, Springer, 2010.
  • Amir Khandani, Eytan Modiano, Lizhong Zhang, Jinane Aboundi, " Cooperative Routing in Wireless Networks ," Chapter in Advances in Pervasive Computing and Networking, Kluwer Academic Publishers, 2005.
  • Jian-Qiang Hu and Eytan Modiano, " Traffic Grooming in WDM Networks ," Chapter in Emerging Optical Network Technologies, Kluwer Academic Publishers, to appear, 2004.
  • Eytan Modiano, " WDM Optical Networks ," Wiley Encyclopedia of Telecommunications (John Proakis, Editor), 2003.
  • Eytan Modiano, " Optical Access Networks for the Next Generation Internet ," in Optical WDM Networks: Principles and Practice, Kluwer Academic Prublishers, 2002.
  • Eytan Modiano, Richard Barry and Eric Swanson, " A Novel Architecture and Medium Access Control protocol for WDM Networks ," Trends in Optics and Photonics Series (TOPS) volume on Optical Networks and Their Applications, 1998.
  • Eytan Modiano and Kai-Yeung Siu, "Network Flow and Congestion Control," Wiley Encyclopedia of Electrical and Electronics Engineering, 1999.

Technical Reports

  • Amir Khandani, Eytan Modiano, Jinane Abounadi, Lizhong Zheng, "Reliability and Route Diversity in Wireless Networks, " MIT LIDS Technical Report number 2634, November, 2004.
  • Anand Srinivas and Eytan Modiano, "Minimum Energy Disjoint Path Routing in Wireless Ad Hoc Networks, " MIT LIDS Technical Report, P-2559, March, 2003.
  • Eytan Modiano and Aradhana Narula-Tam, "Survivable lightpath routing: a new approach to the design of WDM-based networks, " LIDS report 2552, October, 2002.
  • Michael Neely, Eytan Modiano and Charles Rohrs, "Packet Routing over Parallel Time-Varying Queues with Application to Satellite and Wireless Networks," LIDS report 2520, September, 2001.
  • Jun Sun and Eytan Modiano, "Capacity Provisioning and Failure Recovery in Mesh-Torus Networks with Application to Satellite Constellations," LIDS report 2518, September, 2001.
  • Hungjen Wang, Eytan Modiano and Muriel Medard, "Partial Path Protection for WDM Networks: End-to-End Recovery Using Local Failure Information, " LIDS report 2517, Sept. 2001.
  • Alvin Fu, Eytan Modiano, and John Tsitsiklis, "Optimal Energy Allocation and Admission Control for Communications Satellites, " LIDS report 2516, September, 2001.
  • Michael Neely, Eytan Modiano and Charles Rohrs, "Power and Server Allocation in a Multi-Beam Satellite with Time Varying Channels, " LIDS report 2515, September, 2001.
  • Eytan Modiano, "Scheduling Algorithms for Message Transmission Over the GBS Satellite Broadcast System, " Lincoln Laboratory Technical Report Number TR-1035, June 1997.
  • Eytan Modiano, "Scheduling Packet Transmissions in A Multi-hop Packet Switched Network Based on Message Length, " Lincoln Laboratory Technical Report number TR-1036, June, 1997.
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25 of today’s coolest network and computing research projects

Latest concoctions from university labs include language learning website, a newfangled Internet for mobile devices and even IP over xylophones

University labs, fueled with millions of dollars in funding and some of the biggest brains around, are bursting with new research into computer and networking technologies.

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networks, computer and a general focus on shrinking things and making them faster are among the hottest areas, with some advances already making their way into the market. Here’s a roundup of 25 such projects that caught our eyes:

This free website, Duolingo , from a pair of Carnegie Mellon University computer scientists serves double duty: It helps people learn new languages while also translating the text on Web pages into different languages.

CMU’s Luis von Ahn and Severin Hacker have attracted more than 100,000 people in a beta test of the system, which initially offered free language lessons in English, Spanish, French and German, with the computer offering advice and guidance on unknown words. Using the system could go a long way toward translating the Web, many of whose pages are unreadable by those whose language skills are narrow.

Von Ahn is a veteran of such crowdsourcing technologies, having created online reCAPTCHA puzzles to cut down on spam while simultaneously digitizing old books and periodicals. Von Ahn’s spinoff company, reCAPTCHA, was acquired by Google in 2009. Duolingo, spun off in November to offer commercial and free translation services, received $3.3 million in funding from Union Square Ventures, actor Ashton Kutcher and others.

Princeton University Computer Science researchers envision an Internet that is more flexible for operators and more useful to mobile users. Princeton’s Serval system is what Assistant Professor of Computer Science Michael Freedman calls a Service Access Layer that sits between the IP Network Layer (Layer 3) and Transport Layer (Layer 4), where it can work with unmodified network devices. Serval’s purpose is to make Web services such as Gmail and Facebook more easily accessible, regardless of where an end user is, via a services naming scheme that augments what the researchers call an IP address set-up “designed for communication between fixed hosts with topology-dependent addresses.” Data center operators could benefit by running Web servers in virtual machines across the cloud and rely less on traditional load balancers.

Serval, which Freedman describes as a “replacement” technology, will likely have its first production in service-provider networks. “Its largest benefits come from more dynamic settings, so its features most clearly benefit the cloud and mobile spaces,” he says.

If any of this sounds similar to software-defined networking (SDN), there are in fact connections. Freedman worked on an SDN/OpenFlow project at Stanford University called Ethane that was spun out into a startup called Nicira for which VMware recently plunked down $1.26 billion.

WiFi routers to the rescue

Researchers at Germany’sTechnical University in Darmstadt have described a way for home Wi-Fi routers to form a backup mesh network to be used by the police, firefighters and other emergency personnel in the case of a disaster or other incident that wipes out standard cell and phone systems.

The proliferation of Wi-Fi routers makes the researchers confident that a dense enough ad hoc network could be created, but they noted that a lack of unsecured routers would require municipalities to work with citizens to allow for the devices to be easily switched into emergency mode. The big question is whether enough citizens would really allow such access, even if security was assured.

Hyperspeed signaling

University of Tulsa engineers want to slow everything down, for just a few milliseconds, to help network administrations avoid cyberattacks.

By slowing traffic, the researchers figure more malware can be detected and then headed off via an algorithm that signals at hyperspeed to set up defenses. Though researcher Sujeet Shenoi told the publication New Scientist that it might not be cheap to set up such a defense system, between the caching system and reserved data pipes needed to support the signals.

Control-Alt-Hack

University of Washington researchers have created a card game called Control-Alt-Hack that’s designed to introduce computer science students to security topics.

The game, funded in part by Intel Labs and the National Science Foundation, made its debut at the Black Hat security conference in Las Vegas over the summer. The tabletop game involves three to six players working for an outfit dubbed Hackers, Inc., that conducts security audits and consulting, and players are issued challenges, such as hacking a hotel mini bar payment system or wireless medical implant, or converting a robotic vacuum cleaner into a toy. The game features cards (including descriptions of well-rounded hackers who rock climb, ride motorcycles and do more than sit at their computers), dice, mission cards, “hacker cred tokens” and other pieces, and is designed for players ages 14 and up. It takes about an hour to play a game. No computer security degree needed.

“We went out of our way to incorporate humor,” said co-creator Tamara Denning, a UW doctoral student in computer science and engineering, referring to the hacker descriptions and challenges on the cards. “We wanted it to be based in reality, but more importantly we want it to be fun for the players.”

Ghost-USB-Honeypot project

This effort, focused on nixing malware like Flame that spreads from computer to computer via USB storage drives, got its start based on research from Sebastian Poeplau at Bonn University’s Institute of Computer Science. Now it’s being overseen by the broader Honeynet Project.

The breakthrough by Poeplau and colleagues was to create a virtual drive that runs inside a USB drive to snag malware . According to the project website: “Basically, the honeypot emulates a USB storage device. If your machine is infected by malware that uses such devices for propagation, the honeypot will trick it into infecting the emulated device.”

One catch: the security technology only works on XP 32 bit, for starters.

IP over Xylophone Players (IPoXP)

Practical applications for running IP over xylophones might be a stretch, but doing so can teach you a few things about the truly ubiquitous protocol.

A University of California Berkeley researcher named R. Stuart Geiger led this project, which he discussed earlier this year at the Association for Computing Machinery’s Conference on Human Factors in Computing Systems . Geiger’s Internet Protocol over Xylophone Players (IPoXP) provides a fully compliant IP connection between two computers. His setup uses a pair of Arduino microcontrollers, some sensors, a pair of xylophones and two people to play the xylophones.

The exercise provided some insights into the field of Human-Computer Interaction (HCI). It emulates a technique HCI specialists use to design interfaces called umwelt, which is a practice of imagining what the world must look like to the potential users of the interface. This experiment allowed participants to get the feel for what it would be like to be a circuit.

“I don’t think I realized how robust and modular the OSI model is,” Geiger said. “The Internet was designed for much more primitive technologies, but we haven’t been able to improve on it, because it is such a brilliant model.”

Making software projects work

San Francisco State University and other researchers are puzzling over why so many software projects wind up getting ditched, fail or get completed, but late and over budget. The key, they’ve discovered, is rethinking how software engineers are trained and managed to ensure they can work as teams.

The researchers, also from Florida Atlantic University and Fulda University in Germany, are conducting a National Science Foundation-funded study with their students that they hope will result in a software model that can predict whether a team is likely to fail. Their study will entail collecting information on how often software engineering students – teamed with students at the same university and at others — meet, email each other, etc.

“We want to give advice to teachers and industry leaders on how to manage their teams,” says Dragutin Petkovic, professor and chair of SF State’s Computer Science Department. “Research overwhelmingly shows that it is ‘soft skills,’ how people work together, that are the most critical to success.”

Ultra low-power wireless

Forget about 3G, 4G and the rest: University of Arkansas engineering researchers are focused on developing very low-power wireless systems that can grab data from remote sensors regardless of distortion along the network path.

These distortion-tolerant systems would enable sensors, powered by batteries or energy-harvesting, to remain in the field for long periods of time and withstand rough conditions to monitor diverse things such as tunnel stability and animal health. By tolerating distortion, the devices would expend less energy on trying to clean up communications channels.

“If we accept the fact that distortion is inevitable in practical communication systems, why not directly design a system that is naturally tolerant to distortion?” says Jingxian Wu, assistant professor of electrical engineering.

The National Science Foundation is backing this research with $280,000 in funding.

2-way wireless

University of Waterloo engineering researchers have developed a way for wireless voice and data signals to be sent and received simultaneously on a single radio channel frequency, a breakthrough they say could make for better performing, more easily connected and more secure networks.

“This means wireless companies can increase the bandwidth of voice and data services by at least a factor of two by sending and receiving at the same time, and potentially by a much higher factor through better adaptive transmission and user management in existing networks,” said Amir Khandani, a Waterloo electrical and computer engineering professor, in a statement. He says the cost for hardware and antennas to support such a system wouldn’t cost any more than for current one-way systems.

Next up is getting industry involved in bringing such technology into the standards process.

Next steps require industry involvement by including two-way in forthcoming standards to enable wide spread implementation.

The Waterloo research was funded in part by the Canada Foundation for Innovation and the Ontario Ministry of Research and Innovation.

Spray-on batteries

Researchers at Rice University in Houston have developed a prototype spray-on battery that could allow engineers to rethink the way portable electronics are designed.

The rechargeable battery boasts similar electrical characteristics to the lithium ion batteries that power almost every mobile gadget, but it can be applied in layers to almost any surface with a conventional airbrush, said Neelam Singh, a Rice University graduate student who led a team working on the technology for more than a year.

Current lithium ion batteries are almost all variations on the same basic form: an inflexible block with electrodes at one end. Because they cannot easily be shaped, they sometimes restrict designers, particularly when it comes to small gadgets with curved surfaces, but the Rice prototypes could change that. “Today, we only have a few form factors of batteries, but this battery can be fabricated to fill the space available,” said Singh.

The battery is sprayed on in five layers: two current collectors sandwich a cathode, a polymer separator and an anode. The result is a battery that can be sprayed on to plastics, metal and ceramics.

The researchers are hoping to attract interest from electronics companies, which Singh estimates could put it into production relatively easily. “Airburshing technology is well-established. At an industrial level it could be done very fast,” she said.

Mobile Mosh pit

Two MIT researchers formally unveiled over the summer a protocol called State Synchronization Protocol (SSP) and a remote log-in program using it dubbed Mosh (for mobile shell) that’s intended as an alternative to Secure Shell (SSH) for ensuring good connectivity for mobile clients even when dealing with low bandwidth connections. SSP and Mosh have been made available for free, on GNU/, FreeBSD and OS X, via an MIT website .

SSH, often used by network and system admins for remotely logging into servers, traditionally connects computers via TCP, but it’s that use of TCP that creates headaches for mobile users, since TCP assumes that the two endpoints are fixed, says Keith Winstein, a graduate student with MIT’s Computer Science and Artificial Intelligence Lab (CSAIL), and Mosh’s lead developer. “This is not a great way to do real-time communications,” Winstein says. SSP uses UDP, a connectionless, stateless transport mechanism that could be useful for stabilizing mobile usage of apps from Gmail to Skype.

Network Coding

Researchers from MIT, California Institute of Technology and University of Technology in Munich are putting network coding and error-correction coding to use in an effort to measure capacity of wired, and more challengingly, even small wireless networks (read their paper here for the gory details).

The researchers have figured out a way to gauge the upper and lower bounds of capacity in a wireless network. Such understanding could enable enterprises and service providers to design more efficient networks regardless of how much noise is on them (and wireless networks can get pretty darn noisy).

More details from MIT press office.

100 terahertz level

A University of Pittsburgh research team is claiming a communications breakthrough that they say could be used to speed up electronic devices such as and laptops in a big way. Their advance is a demonstrated access to more than 100 terahertz of bandwidth (electromagnetic spectrum between infrared and microwave light), whereas electronic devices traditionally have been limited to bandwidth in the gigahertz realm.

Researchers Hrvoje Petek of the University of Pittsburgh and visiting professor Muneaki Hase of the University of Tsukuba in Japan, have published their NSF-funded research findings in a paper in Nature Photonics. The researchers “detail their success in generating a frequency comb-dividing a single color of light into a series of evenly spaced spectral lines for a variety of uses-that spans a more than 100 terahertz bandwidth by exciting a coherent collective of atomic motions in a semiconductor silicon crystal.”

Petek says the advance could result in devices that carry a thousand-fold more information.

Separately, IBM researchers have developed a prototype optical chip that can transfer data at 1Tbps, the equivalent of downloading 500 high-definition movies, using light pulses rather than by sending electrons over wires.

The Holey Optochip is described as a parallel optical transceiver consisting of a transmitter and a receiver, and designed to handle gobs of data on corporate and consumer networks.

Cooling off with graphene

Graphene is starting to sound like a potential wonder material for the electronics business. Researchers from the University of California at Riverside, the University of Texas at Dallas and Austin, and Xiamen University in China have come up with a way to engineer graphene so that it has much better thermal properties. Such an isotopically-engineered version of graphene could be used to build cooler-running laptops, wireless gear and other equipment. The need for such a material has grown as electronic devices have gotten more powerful but shrunk in size.

“The important finding is the possibility of a strong enhancement of thermal conduction properties of isotopically pure graphene without substantial alteration of electrical, optical and other physical properties,” says UC Riverside Professor of Electrical Engineering Alexander Balandin, in a statement. “Isotopically pure graphene can become an excellent choice for many practical applications provided that the cost of the material is kept under control.”

Such a specially engineered type of graphene would likely first find its way into some chip packaging materials as well into photovoltaic solar cells and flexible displays, according to UC Riverside. Beyond that, it could be used with silicon in computer chips, for interconnect wiring to to spread heat.

Industry researchers have been making great strides on the graphene front in recent years. IBM, for example, last year said it had created the first graphene-based integrated circuit. Separately, two Nobel Prize winning scientists out of the U.K. have come up with a new way to use graphene – the thinnest material in the world – that could make Internet pipes feel a lot fatter.

Keeping GPS honest

Cornell University researchers are going on the offense against those who would try to hack GPS systems like those used in everything from cars to military drones to cellphone systems and power grids. Over the summer, Cornell researchers tested their system for outsmarting GPS spoofers during a Department of Homeland Security-sponsored demo involving a mini helicopter in the New Mexico desert at the White Sands Missile Range.

Cornell researchers have come up with GPS receiver modifications that allow the systems to distinguish between real and bogus signals that spoofers would use to trick cars, airplanes and other devices into handing over control. They emphasized that the threat of GPS spoofing is very real, with Iran last year claiming to have downed a GPS-guided American drone using such techniques.

Getting smartphones their ZZZZs

Purdue University researchers have come up with a way to detect smartphone bugs that can drain batteries while they’re not in use.

“These energy bugs are a silent battery killer,” says Y. Charlie Hu, a Purdue University professor of electrical and computer engineering. “A fully charged phone battery can be drained in as little as five hours.”

The problem is that app developers aren’t perfect when it comes to building programs that need to perform functions when phones are asleep and that use APIs provided by smartphone makers. The researchers, whose work is funded in part by the National Science Foundation, investigated the problem on Android phones, and found that about a quarter of some 187 apps contained errors that could drain batteries. The tools they’re developing to detect such bugs could be made available to developers to help them cut down on battery-draining mistakes.

Quantum leap in search

University of Southern California and University of Waterloo researchers are exploring how quantum computing technology can be used to speed up the math calculations needed to make Internet search speedy even as the gobs of data on the Web expands.

The challenge is that Google’s page ranking algorithm is considered by some to be the largest numerical calculation carried out worldwide, and no quantum computer exists to handle that. However, the researchers have created models of the web to simulate how quantum computing could be used to slice and dice the Web’s huge collection of data. Early findings have been encouraging, with quantum computers shown through the models to be faster at ranking the most important pages and improving as more pages needed to be ranked.

The research was funded by the NSF, NASA Ames Research Center, Lockheed Martin’s University Research Initiative and a Google faculty research award.

Sharing malware in a good way

Georgia Tech Research Institute security specialists have built a system called Titan designed to help corporate and government officials anonymously share information on malware attacks they are fighting, in hopes of fighting back against industrial espionage.

The threat analysis system plows through a repository of some 100,000 pieces of malicious code per day, and will give contributors quick feedback on malware samples that can be reverse-engineered by the Titan crew. Titan will also alert members of new threats, such as targeted spear-phishing attacks, and will keep tabs on not just Windows threats, but also those to MacIntosh and iOS, and Google Android systems.

“As a university, Georgia Tech is uniquely positioned to take this white hat role in between industry and government,” said Andrew Howard, a GTRI research scientist who is part of the Titan project . “We want to bring communities together to break down the walls between industry and government to provide a trusted, sharing platform.”

Touch-feely computing

Researchers from the University of Notre Dame, MIT and the University of Memphis are working on educational software that can respond to students’ cognitive and emotional states, and deliver the appropriate content based on how knowledgeable a student is about a subject, or even how bored he or she is with it.

AutoTutor and Affective AutoTutor get a feel for students’ mood and capabilities based on their responses to questions, including their facial expressions, speech patterns and hand movements.

“Most of the 20th-century systems required humans to communicate with computers through windows, icons, menus and pointing devices,” says Notre Dame Assistant Professor of Psychology Sidney D’Mello, an expert in human-computer interaction and AI in education . “But humans have always communicated with each other through speech and a host of nonverbal cues such as facial expressions, eye contact, posture and gesture. In addition to enhancing the content of the message, the new technology provides information regarding the cognitive states, motivation levels and social dynamics of the students.”

Mobile nets on the move

For emergency responders and others who need to take their mobile networks with them, even in fast-moving vehicles, data transmission quality can be problematic. North Carolina State University researchers say they’ve come up with a way to improve the quality of these Mobile ad hoc networks (MANET).

“Our goal was to get the highest data rate possible, without compromising the fidelity of the signal,” says Alexandra Duel-Hallen, a professor of electrical and computer engineering at NC State whose work is outlined in the paper “ Enabling Adaptive Rate and Relay Selection for 802.11 Mobile Ad Hoc Networks .” 

The challenge is that fast moving wireless nodes make it difficult for relay paths to be identified by the network, as channel power tends to fluctuate much more in fast-moving vehicles. The researchers have come up with an algorithm for nodes to choose the best data relay and transmission paths, based on their experience with recent transmissions.

Tweet the Street

Researchers from the University of California, Riverside and Yahoo Research Barcelona have devised a model that uses data about volumes to predict how financial markets will behave. Their model bested other baseline strategies by 1.4% to 11% and outperformed the Dow Jones Industrial Average during a four-month simulation.

“These findings have the potential to have a big impact on market investors,” said Vagelis Hristidis, an associate professor at the Bourns College of Engineering. “With so much data available from social media, many investors are looking to sort it out and profit from it.”

The research, focused on what Twitter volumes, retweets and who is doing the tweeting might say about individual stocks, differs from that of earlier work focused on making sense of the broader market based on positive and negative sentiments in tweets.

As with so many stock-picking techniques, the researchers here tossed out plenty of caveats about their system, which they said might work quite differently, for example, during a period of overall market growth rather than the down market that their research focused on.

Franken-software

University of Texas, Dallas scientists have developed software dubbed Frankenstein that’s designed to be even more monstrous than the worst malware in the wild so that such threats can be understood better and defended against. Frankenstein can disguise itself as it swipes and messes with data, and could be used as a cover for a virus or other malware by stitching together pieces of such data to avoid antivirus detection methods.

“[Mary] Shelley’s story [about Dr. Frankenstein and his monster] is an example of a horror that can result from science, and similarly, we intend our creation as a warning that we need better detections for these types of intrusions,” said Kevin Hamlen, associate professor of computer science at UT Dallas who created the software, along with doctoral student Vishwath Mohan. “Criminals may already know how to create this kind of software, so we examined the science behind the danger this represents, in hopes of creating countermeasures.”

Such countermeasures might include infiltrating terrorist computer networks, the researchers say. To date, they’ve used the NSF and Air Force Office of Scientific Research-funded technology on benign algorithms, not any production systems.

Safer e-wallets

While e-wallets haven’t quite taken off yet, University of Pittsburgh researchers are doing their part to make potential e-wallet users more comfortable with the near-field communications (NRC) and/or RFID-powered technology.

Security has been a chief concern among potential users, who are afraid thieves could snatch their credit card numbers through the air. But these researchers have come up with a way for e-wallet credit cards to turn on and off, rather than being always on whenever in an electromagnetic field.

“Our new design integrates an antenna and other electrical circuitry that can be interrupted by a simple switch, like turning off the lights in the home or office,” says Marlin Mickle, the Nickolas A. DeCecco Professor of Engineering and executive director of the RFID Center for Excellence in the Swanson School. “The RFID or NFC credit card is disabled if left in a pocket or lying on a surface and unreadable by thieves using portable scanners.”

Mickle claims the advance is both simple and inexpensive, and once the researchers have received what they hope will be patent approval, they expect the technology to be adopted commercially.

Digging into Big Data

The University of California, Berkeley has been handed $10 million by the National Science Foundation as part of a broader $200 million federal government effort to encourage the exploration and better exploitation of massive amounts of information dubbed Big Data collected by far-flung wireless sensors, social media systems and more.

UC Berkeley has five years to use its funds for a project called the Algorithms, Machines and People (AMP) Expedition, which will focus on developing tools to extract important information from Big Data, such as trends that could predict everything from earthquakes to cyberattacks to epidemics.

“Buried within this flood of information are the keys to solving huge societal problems and answering the big questions of science,” said Michael Franklin, director of the AMP Expedition team and a UC Berkeley professor of electrical engineering and computer sciences, in a statement . “Our goal is to develop a new generation of data analysis tools that provide a quantum leap in our ability to make sense of the world around us.”

AMP Expedition researchers are building an open-source software stack called the Berkeley Data Analysis System (BDAS) that boasts large-scale machine-learning and data analysis methods, infrastructure that lets programmers take advantage of cloud and cluster computing, and crowdsourcing (in other words, human intelligence). It builds on the AMPLab formed early last year, with backing from Google, SAP and others.

Bob Brown tracks network research in his and Facebook page, as well on Twitter and Google + . 

IDG News Service and other IDG publications contributed to this report

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Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 4516))

What are the big movements in networking that researchers should heed? A standout is the global spread of communities of interest (the networking analogue of the flat world) and their need for “dynamic virtual networks” that support rich applications requiring resources from several domains. The imperative for inter-networking, i.e., the enablement of coordinated sharing of resources across multiple domains, is certain. This challenge has many facets, ranging from the organizational, e.g., different, possibly competing, owners to the technical, e.g., different technologies. Yet another key characteristic of the emerging networking environment is that the service provider is required to handle ever-increasing uncertainty in demand, both in volume and time. On the other hand there are new instruments available to handle the challenge. Thus, inter-networking and uncertainty management are important challenges of emerging networking that deserve attention from the research community.

We describe research that touch on both topics. First, we consider a model of data-optical inter-networking, where routes connecting end-points in data domains are concatenation of segments in the data and optical domains. The optical domain in effect acts as a carrier’s carrier for multiple data domains. The challenge to inter-networking stems from the limited view that the data and optical domains have of each other. Coordination has to be enabled through parsimonious and qualitatively restrictive information exchange across domains. Yet the overall optimization objective, which is to maximize end-to-end carried traffic with minimum lightpath provisioning cost, enmeshes data and optical domains. This example of inter-networking also involves two technologies. A mathematical reflection of the latter fact is the integrality of some of the decision variables due to wavelengths being the bandwidth unit in optical transmission. Through an application of Generalized Bender’s Decomposition the problem of optimizing provisioning and routing is decomposed into sub-problems, which are solved by the different domains and the results exchanged in iterations that provably converge to the global optimum.

In turning to uncertainty management we begin by presenting a framework for stochastic traffic management. Traffic demands are uncertain and given by probability distributions. While there are alternative perspectives (and metrics) to resource usage, such as social welfare and network revenue, we adopt the latter, which is aligned with the service provider’s interests. Uncertainty introduces the risk of misallocation of resources. What is the right measure of risk in networking? We examine various definitions of risk, some taken from modern portfolio theory, and suggest a balanced solution. Next we consider the optimization of an objective which is a risk-adjusted measure of network revenue. We obtain conditions under which the optimization problem is an instance of convex programming. Studies of the properties of the solution show that it asymptotically meets the stochastic efficiency criterion. Service providers’ risk mitigation policies are suggested. For instance, by selecting the appropriate mix of long-term contracts and opportunistic servicing of random demand, the service provider can optimize its risk-adjusted revenue. The “efficient frontier”, which is the set of Pareto optimal pairs of mean revenue and revenue risk, is useful to the service provider in selecting its operating point.

Joint work with Qiong Wang and Anwar Walid, Bell Labs, Murray Hill.

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Debasis Mitra

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Mitra, D. (2007). Topics in Networking Research. In: Mason, L., Drwiega, T., Yan, J. (eds) Managing Traffic Performance in Converged Networks. ITC 2007. Lecture Notes in Computer Science, vol 4516. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72990-7_3

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  • 15 Latest Networking Research Topics for Students

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Comparative analysis between snort and suricata IDS software(s)

Description of the topic

The main focus of this research is to conduct a comparative analysis between Snort and Suricata software to determine which IDS software can provide better performance. There are various IDS software(s) available that can be used by organizations but it is difficult to identify which one is best (Aldarwbi et al., 2022). Different organizational structures are often facing problems while setting up an IDS system which results in false positives and intrusions. Through this research, it can be identified which IDS software is better and what secure configuration is required to detect intrusions (Waleed et al., 2022).

Research objectives

  • To evaluate Snort and Suricata IDS software(s) to determine the most optimal one.
  • To identify the false positive rate of Snort and Suricata on the networked environment.

Research questions

RQ1: Which IDS software can perform better on the production network in terms of performance, security, scalability and reliability?

RQ2: What different ways can be followed to deal with false positive problems in IDS technology?

Research methodology

The given research objectives and research questions can be addressed using quantitative research methodology where an experimental approach can be followed. For the given topic, both Snort and Suricata IDS systems should be configured and tested against different attacks. Depending on the findings, it can be analyzed which IDS software can perform better in terms of performance and security (Shuai & Li, 2021).

  • Aldarwbi, M.Y., Lashkari, A.H. and Ghorbani, A.A. (2022) “The sound of intrusion: A novel network intrusion detection system,” Computers and Electrical Engineering , 104, p. 108455.
  • Shuai, L. and Li, S. (2021) “Performance optimization of Snort based on DPDK and Hyperscan,” Procedia Computer Science , 183, pp. 837-843.
  • Waleed, A., Jamali, A.F. and Masood, A. (2022) “Which open-source ids? Snort, Suricata or Zeek,” Computer Networks , 213, p. 109116.

Role of honeypots and honey nets in network security

Network Security has become essential nowadays and there is a need for setting up robust mechanisms to maintain confidentiality and integrity (Feng et al., 2023). Due to the number of security mechanisms available, organizations found it hard to finalize and implement them on their network. For example, honey pots and honeynet approaches look almost the same and have the same purpose but work differently. Under this research topic, the configuration of honeynets and honeypots can be done to check which one can perform better security in terms of trapping cyber attackers. The entire implementation can be carried out in the cloud-based instance for improved security and it can be identified which type of honey pot technology must be preferred (Maesschalck et al., 2022).

  • To set up a honey pot system using Open Canary on the virtual instance to protect against cyber attackers.
  • To set up a honeynet system on the virtual instance to assure protection is provided against malicious attackers.
  • To test honeypots and honeynets by executing DDoS attacks to check which can provide better security.

RQ1: Why is there a need for using honeypots over honey pots in a production networked environment?

RQ2: What are the differences between cloud-based and local honey pot systems for endpoint protection?

This research can be carried out using the quantitative method of research. At the initial stage, the implementation of honeypots and honeypots can be done on the virtual instance following different security rules. Once the rules are applied, the testing can be performed using a Kali Linux machine to check whether honey pots were effective or honeynets (Gill et al., 2020).

  • Feng, H. et al. (2023) “Game theory in network security for Digital Twins in industry,” Digital Communications and Networks [Preprint].
  • Gill, K.S., Saxena, S. and Sharma, A. (2020) “GTM-CSEC: A game theoretic model for cloud security based on ids and Honeypot,” Computers & Security , 92, p. 101732
  • Maesschalck, S. et al. (2022) “Don’t get stung, cover your ICS in honey: How do honeypots fit within industrial control system security,” Computers & Security , 114, p. 102598.

How do malware variants are progressively improving?

This research can be based on evaluating how malware variants are progressively improving and what should be its state in the coming future. Malware is able to compromise confidential user’s information assets which is why this research can be based on identifying current and future consequences owing to its improvements (Deng et al., 2023). In this field, there is no research work that has been carried out to identify how malware variants are improving their working and what is expected to see in future. Once the evaluation is done, a clear analysis can also be done on some intelligent preventive measures to deal with dangerous malware variants and prevent any kind of technological exploitation (Tang et al., 2023).

  • To investigate types of malware variants available to learn more about malware's hidden features.
  • To focus on future implications of malware executable programs and how they can be avoided.
  • To discuss intelligent solutions to deal with all malware variants.

RQ1: How do improvements in malware variants impact enterprises?

RQ2: What additional solutions are required to deal with malware variants?

In this research, qualitative analysis can be conducted on malware variants and the main reason behind their increasing severity. The entire research can be completed based on qualitative research methodology to answer defined research questions and objectives. Some real-life case studies should also be integrated into the research which can be supported by the selected topic (Saidia Fasci et al., 2023).

  • Deng, H. et al. (2023) “MCTVD: A malware classification method based on three-channel visualization and deep learning,” Computers & Security , 126, p. 103084.
  • Saidia Fasci, L. et al. (2023) “Disarming visualization-based approaches in malware detection systems,” Computers & Security , 126, p. 103062.
  • Tang, Y. et al. (2023) “BHMDC: A byte and hex n-gram based malware detection and classification method,” Computers & Security , p. 103118.

Implementation of IoT - enabled smart office/home using cisco packet tracer

The Internet of Things has gained much more attention over the past few years which is why each enterprise and individual aims at setting up an IoT network to automate their processes (Barriga et al., 2023). This research can be based on designing and implementing an IoT-enabled smart home/office network using Cisco Packet Tracer software. Logical workspace, all network devices, including IoT devices can be used for preparing a logical network star topology (Elias & Ali, 2014). To achieve automation, the use of different IoT rules can be done to allow devices to work based on defined rules.

  • To set up an IoT network on a logical workspace using Cisco Packet Tracer simulation software.
  • To set up IoT-enabled rules on an IoT registration server to achieve automation (Hou et al., 2023).

RQ: Why is the Cisco packet tracer preferred for network simulation over other network simulators?

At the beginning of this research, a quantitative research methodology can be followed where proper experimental set-up can be done. As a packet tracer is to be used, the star topology can be used to interconnect IoT devices, sensors and other network devices at the home/office. Once a placement is done, the configuration should be done using optimal settings and all IoT devices can be connected to the registration server. This server will have IoT rules which can help in achieving automation by automatically turning off lights and fans when no motion is detected (Baggan et al., 2022).

  • Baggan, V. et al. (2022) “A comprehensive analysis and experimental evaluation of Routing Information Protocol: An Elucidation,” Materials Today: Proceedings , 49, pp. 3040–3045.
  • Barriga, J.A. et al. (2023) “Design, code generation and simulation of IOT environments with mobility devices by using model-driven development: Simulateiot-Mobile,” Pervasive and Mobile Computing , 89, p. 101751.
  • Elias, M.S. and Ali, A.Z. (2014) “Survey on the challenges faced by the lecturers in using packet tracer simulation in computer networking course,” Procedia - Social and Behavioral Sciences , 131, pp. 11–15.
  • Hou, L. et al. (2023) “Block-HRG: Block-based differentially private IOT networks release,” Ad Hoc Networks , 140, p. 103059.

Comparative analysis between AODV, DSDV and DSR routing protocols in WSN networks

For wireless sensor networks (WSN), there is a major need for using WSN routing rather than performing normal routines. As WSN networks are self-configured, there is a need for an optimal routing protocol that can improve network performance in terms of latency, jitter, and packet loss (Luo et al., 2023). There are often various problems faced when WSN networks are set up due to a lack of proper routing protocol selection. As a result of this, severe downtime is faced and all links are not able to communicate with each other easily (Hemanand et al., 2023). In this research topic, the three most widely used WSN routing protocols AODV, DSDV and DSR can be compared based on network performance. To perform analysis, three different scenarios can be created in network simulator 2 (Ns2).

  • To create three different scenarios on ns2 software to simulate a network for 1 to 100 seconds.
  • To analyze which WSN routing is optimal in terms of network performance metrics, including latency, jitter and packet loss.
  • To use CBR and NULL agents for all wireless scenarios to start with simulation purposes.

RQ: How do AODV, DSR and DSDV routing protocols differ from each other in terms of network performance?

This research can be carried out using a quantitative research method. The implementation for the provided research topic can be based on Ns2 simulation software where three different scenarios can be created (AODV, DSDV and DSR). For each scenario, NULL, CSR and UDP agents can be done to start with simulation for almost 1 to 100 seconds. For all transmissions made during the given time, network performance can be checked to determine which routing is best (Mohapatra & Kanungo, 2012).

  • Human and, D. et al. (2023) “Analysis of power optimization and enhanced routing protocols for Wireless Sensor Networks,” Measurement: Sensors , 25, p. 100610. Available at: https://doi.org/10.1016/j.measen.2022.100610.
  • Luo, S., Lai, Y. and Liu, J. (2023) “Selective forwarding attack detection and network recovery mechanism based on cloud-edge cooperation in software-defined wireless sensor network,” Computers & Security , 126, p. 103083. Available at: https://doi.org/10.1016/j.cose.2022.103083.
  • Mohapatra, S. and Kanungo, P. (2012) “Performance analysis of AODV, DSR, OLSR and DSDV routing protocols using NS2 Simulator,” Procedia Engineering , 30, pp. 69–76. Available at: https://doi.org/10.1016/j.proeng.2012.01.835.

Securing wireless network using AAA authentication and WLAN controller

Wireless networks often face intrusion attempts due to insecure protocols and sometimes open SSIDs. As a result of this, man-in-the-middle and eavesdropping attacks become easier which results in the loss of confidential information assets (Sivasankari & Kamalakkannan, 2022). When it comes to managing networks in a large area, there are higher chances for attacks that enable cyber attackers in intercepting ongoing communication sessions. However, there is currently no research conducted where the use of AAA authentication has been done with WLAN controllers to make sure a higher level of protection is provided (Nashwan, 2021). The proposed research topic can be based on securing wireless networks with the help of AAA authentication and WLAN controllers. The use of AAA authentication can be done to set up a login portal for users whilst the WLAN controller can be used for managing all wireless access points connected to the network (Nashwan, 2021).

  • To set up AAA authentication service on the wireless network simulated on Cisco Packet Tracer for proper access control.
  • To set up a WLAN controller on the network to manage all wireless access points effortlessly.
  • To use WPA2-PSK protocol on the network to assure guest users are only able to access wireless networks over a secure protocol.

RQ1: What additional benefits are offered by AAA authentication on the WLAN networks?

RQ2: Why are wireless networks more likely to face network intrusions than wired networks?

This research topic is based on the secure implementation of a wireless LAN network using a Cisco packet tracer. Hence, this research can be carried out using a quantitative research method. The implementation can be carried out using AAA authentication which can assure that access control is applied for wireless logins. On the other hand, a WLAN controller can also be configured which can ensure that all WAPs are managed (ZHANG et al., 2012).

  • Nashwan, S. (2021) “AAA-WSN: Anonymous Access Authentication Scheme for wireless sensor networks in Big Data Environment,” Egyptian Informatics Journal , 22(1), pp. 15–26.
  • Sivasankari, N. and Kamalakkannan, S. (2022) “Detection and prevention of man-in-the-middle attack in IOT network using regression modeling,” Advances in Engineering Software , 169, p. 103126.
  • ZHANG, J. et al. (2012) “AAA authentication for Network mobility,” The Journal of China Universities of Posts and Telecommunications , 19(2), pp. 81-86.

OWASP's approach to secure web applications from web application exploits

The research can revolve around the development of web applications by considering OWASP's top 10 rules. Usually, web applications are deployed by organizations depending on their requirements and these applications are vulnerable to various exploits, including injection, broken authentication and other forgery attacks (Poston, 2020). Identifying every single vulnerability is difficult when reference is not taken and often organizations end up hosting a vulnerable server that leads to privacy issues and compromises confidential information easily. In this research, OWASP's top 10 approaches can be followed to develop a secure web application that can be able to protect against top web application exploits. This approach is based on emphasizing severe and minor vulnerabilities which must be patched for protecting against web application attacks (Deepa & Thilagam, 2016).

  • The first objective can be setting up an insecure web application on the cloud environment which can be exploited with different techniques.
  • The second objective can be to consider all techniques and procedures provided by OWASP's top 10 methodologies.
  • The last objective can be applying all fixes to insecure web applications to make them resistant to OWASP top 10 attacks (Sonmez, 2019).

RQ1: What are the benefits of using OWASP's top 10 approaches to harden web applications in comparison to other security approaches?

The research methodology considered for this research project can be quantitative using an experimental approach. The practical work can be done for the selected topic using AWS or the Azure cloud platform. Simply, a virtual web server can be configured and set up with a secure and insecure web application. Following OWASP's top 10 techniques and procedures, the web application can be secured from possible attacks. In addition, insecure applications can also be exploited and results can be evaluated (Applebaum et al., 2021).

  • Applebaum, S., Gaber, T. and Ahmed, A. (2021) “Signature-based and machine-learning-based web application firewalls: A short survey,” Procedia Computer Science , 189, pp. 359–367. Available at: https://doi.org/10.1016/j.procs.2021.05.105.
  • Deepa, G. and Thilagam, P.S. (2016) “Securing web applications from injection and logic vulnerabilities: Approaches and challenges,” Information and Software Technology , 74, pp. 160–180. Available at: https://doi.org/10.1016/j.infsof.2016.02.005.
  • Poston, H. (2020) “Mapping the owasp top Ten to the blockchain,” Procedia Computer Science , 177, pp. 613-617. Available at: https://doi.org/10.1016/j.procs.2020.10.087.
  • Sonmez, F.Ö. (2019) “Security qualitative metrics for Open Web Application Security Project Compliance,” Procedia Computer Science , 151, pp. 998-1003. Available at: https://doi.org/10.1016/j.procs.2019.04.140.

Importance of configuring RADIUS (AAA) server on the network

User authentication has become significant nowadays as it guarantees that a legitimate user is accessing the network. But a problem is faced when a particular security control is to be identified for authentication and authorization. These controls can be categorized based on mandatory access controls, role-based access control, setting up captive portals and many more. Despite several other security controls, one of the most efficient ones is the RADIUS server (SONG et al., 2008). This server can authenticate users on the network to make sure network resources are accessible to only legal users. This research topic can be based on understanding the importance of RADIUS servers on the network which can also be demonstrated with the help of the Cisco Packet Tracer. A network can be designed and equipped with a RADIUS server to ensure only legal users can access network resources (WANG et al., 2009).

  • To configure RADIUS (AAA) server on the network which can be able to authenticate users who try to access network resources.
  • To simulate a network on a packet tracer simulation software and verify network connectivity.

RQ1: What are other alternatives to RADIUS (AAA) authentication servers for network security?

RQ2: What are the common and similarities between RADIUS and TACACS+ servers?

As a logical network is to be designed and configured, a quantitative research methodology can be followed. In this research coursework, a secure network design can be done using a packet tracer network simulator, including a RADIUS server along with the DMZ area. The configuration for the RADIUS server can be done to allow users to only access network resources by authenticating and authorizing (Nugroho et al., 2022).

  • Nugroho, Y.S. et al. (2022) “Dataset of network simulator related-question posts in stack overflow,” Data in Brief , 41, p. 107942.
  • SONG, M., WANG, L. and SONG, J.-de (2008) “A secure fast handover scheme based on AAA protocol in Mobile IPv6 Networks,” The Journal of China Universities of Posts and Telecommunications , 15, pp. 14-18.
  • WANG, L. et al. (2009) “A novel congestion control model for interworking AAA in heterogeneous networks,” The Journal of China Universities of Posts and Telecommunications , 16, pp. 97-101.

Comparing mod security and pF sense firewall to block illegitimate traffic

Firewalls are primarily used for endpoint security due to their advanced features ranging from blocking to IDS capabilities and many more. It is sometimes challenging to identify which type of firewall is best and due to this reason, agencies end up setting up misconfigured firewalls (Tiwari et al., 2022). This further results in a cyber breach, destroying all business operations. The research can be emphasizing conducting a comparison between the two most widely used firewalls i.e. Mod Security and pF sense. Using a virtualized environment, both firewalls can be configured and tested concerning possible cyber-attacks (Lu & Yang, 2020).

  • To use the local environment to set up Mod security and pF sense firewall with appropriate access control rules.
  • To test both firewalls by executing distributed denial of service attacks from a remote location.
  • To compare which type of firewall can provide improved performance and robust security.

RQ: How do Mod security and pF sense differ from each other in terms of features and performance?

The practical experimentation for both firewalls can be done using a virtualized environment where two different machines can be created. Hence, this research can be carried out using a quantitative research method . The first machine can have Mod security and the second machine can have pF sense configured. A new subnet can be created which can have these two machines. The third machine can be an attacking machine which can be used for testing firewalls. The results obtained can be then evaluated to identify which firewall is best for providing security (Uçtu et al., 2021).

  • Lu, N. and Yang, Y. (2020) “Application of evolutionary algorithm in performance optimization of Embedded Network Firewall,” Microprocessors and Microsystems , 76, p. 103087.
  • Tiwari, A., Papini, S. and Hemamalini, V. (2022) “An enhanced optimization of parallel firewalls filtering rules for scalable high-speed networks,” Materials Today: Proceedings , 62, pp. 4800-4805.
  • Uçtu, G. et al. (2021) “A suggested testbed to evaluate multicast network and threat prevention performance of Next Generation Firewalls,” Future Generation Computer Systems , 124, pp. 56-67.

Conducting a comprehensive investigation on the PETYA malware

The main purpose of this research is to conduct a comprehensive investigation of the PETYA malware variant (McIntosh et al., 2021). PETYA often falls under the category of ransomware attacks which not only corrupt and encrypt files but can compromise confidential information easily. Along with PETYA, there are other variants also which lead to a security outage and organizations are not able to detect these variants due to a lack of proper detection capabilities (Singh & Singh, 2021). In this research, a comprehensive analysis has been done on PETYA malware to identify its working and severity level. Depending upon possible causes of infection of PETYA malware, some proactive techniques can also be discussed (Singh & Singh, 2021). A separation discussion can also be made on other malware variants, their features, and many more.

  • The main objective of this research is to scrutinize the working of PETYA malware because a ransomware attack can impact the micro and macro environment of the organizations severely.
  • The working of PETYA malware along with its source code can be reviewed to identify its structure and encryption type.
  • To list all possible CVE IDs which are exploited by the PETYA malware.

RQ1: How dangerous is PETYA malware in comparison to other ransomware malware?

This research can be based on qualitative research methodology to evaluate the working of PETYA malware from various aspects, the methodology followed and what are its implications. The research can be initiated by evaluating the working of PETYA malware, how it is triggered, what encryption is applied and other factors. A sample source code can also be analyzed to learn more about how cryptography is used with ransomware (Abijah Roseline & Geetha, 2021).

  • Abijah Roseline, S. and Geetha, S. (2021) “A comprehensive survey of tools and techniques mitigating computer and mobile malware attacks,” Computers & Electrical Engineering , 92, p. 107143.
  • McIntosh, T. et al. (2021) “Enforcing situation-aware access control to build malware-resilient file systems,” Future Generation Computer Systems , 115, pp. 568-582.
  • Singh, J. and Singh, J. (2021) “A survey on machine learning-based malware detection in executable files,” Journal of Systems Architecture , 112, p. 101861.

Setting up a Live streaming server on the cloud platform

Nowadays, various organizations require a live streaming server to stream content depending upon their business. However, due to a lack of proper hardware, organizations are likely to face high network congestion, slowness and other problems (Ji et al., 2023). Referring to the recent cases, it has been observed that setting up a streaming server on the local environment is not expected to perform better than a cloud-based streaming server configuration (Martins et al., 2019). This particular research topic can be based on setting up a live streaming server on the AWS or Azure cloud platform to make sure high network bandwidth is provided with decreased latency. The research gap analysis would be conducted to analyze the performance of live streaming servers on local and cloud environments in terms of network performance metrics (Bilal et al., 2018).

  • To set up a live streaming server on the AWS or Azure cloud platform to provide live streaming services.
  • To use load balancers alongside streaming servers to ensure the load is balanced and scalability is achieved.
  • To use Wireshark software to test network performance during live streaming.

RQ1: Why are in-house streaming servers not able to provide improved performance in comparison to cloud-based servers?

RQ2: What additional services are provided by cloud service providers which help in maintaining network performance?

The implementation is expected to carry out on the AWS cloud platform with other AWS services i.e. load balancer, private subnet and many more (Efthymiopoulou et al., 2017). Hence, this research can be carried out using a quantitative research method. The configuration of ec2 instances can be done which can act as a streaming server for streaming media and games. For testing this project, the use of OBS studio can be done which can help in checking whether streaming is enabled or not. For network performance, Wireshark can be used for testing network performance (George et al., 2020).

  • Bilal, KErbad, A. and Hefeeda, M. (2018) “QoE-aware distributed cloud-based live streaming of multi-sourced Multiview Videos,” Journal of Network and Computer Applications , 120, pp. 130-144.
  • Efthymiopoulou, M. et al. (2017) “Robust control in cloud-assisted peer-to-peer live streaming systems,” Pervasive and Mobile Computing , 42, pp. 426-443.
  • George, L.C. et al. (2020) “Usage visualization for the AWS services,” Procedia Computer Science , 176, pp. 3710–3717.
  • Ji, X. et al. (2023) “Adaptive QoS-aware multipath congestion control for live streaming,” Computer Networks , 220, p. 109470.
  • Martins, R. et al. (2019) “Iris: Secure reliable live-streaming with Opportunistic Mobile Edge Cloud offloading,” Future Generation Computer Systems , 101, pp. 272-292.

Significance of using OSINT framework for Network reconnaissance

Network reconnaissance is becoming important day by day when it comes to penetration testing. Almost all white hat hackers are dependent on the OSINT framework to start with network reconnaissance and footprinting when it comes to evaluating organizational infrastructure. On the other hand, cyber attackers are also using this technique to start fetching information about their target. Currently, there is no investigation carried out to identify how effective the OSINT framework is over traditional reconnaissance activities (Liu et al., 2022). This research is focused on using OSINT techniques to analyze victims using different sets of tools like Maltego, email analysis and many other techniques. The analysis can be based on fetching sensitive information about the target which can be used for conducting illegal activities (Abdullah, 2019).

  • To use Maltego software to conduct network reconnaissance on the target by fetching sensitive information.
  • To compare the OSINT framework with other techniques to analyze why it performs well.

RQ1: What is the significance of using the OSINT framework in conducting network reconnaissance?

RQ2: How can the OSINT framework be used by cyber hackers for conducting illegitimate activities?

The OSINT framework is easily accessible on its official website where different search options are given. Hence, this research can be carried out using a quantitative research method. Depending upon the selected target, each option can be selected and tools can be shortlisted for final implementation. Once the tools are shortlisted, they can be used to conduct network reconnaissance (González-Granadillo et al., 2021). For example, Maltego can be used as it is a powerful software to fetch information about the target.

  • Abdullah, S.A. (2019) “Seui-64, bits an IPv6 addressing strategy to mitigate reconnaissance attacks,” Engineering Science and Technology , an International Journal, 22(2), pp. 667–672.
  • Gonzalez-Granadillo, G. et al. (2021) “ETIP: An enriched threat intelligence platform for improving OSINT correlation, analysis, visualization and sharing capabilities,” Journal of Information Security and Applications , 58, p. 102715.
  • Liu, W. et al. (2022) “A hybrid optimization framework for UAV Reconnaissance Mission Planning,” Computers & Industrial Engineering , 173, p. 108653.

Wired and wireless network hardening in cisco packet tracer

At present, network security has become essential and if enterprises are not paying attention to the security infrastructure, there are several chances for cyber breaches. To overcome all these issues, there is a need for setting up secure wired and wireless networks following different techniques such as filtered ports, firewalls, VLANs and other security mechanisms. For the practical part, the use of packet tracer software can be done to design and implement a highly secure network (Sun, 2022).

  • To use packet tracer simulation software to set up secure wired and wireless networks.
  • Use different hardening techniques, including access control rules, port filtering, enabling passwords and many more to assure only authorized users can access the network (Zhang et al., 2012).

RQ: Why is there a need for emphasizing wired and wireless network security?

Following the quantitative approach, the proposed research topic implementation can be performed in Cisco Packet Tracer simulation software. Several devices such as routers, switches, firewalls, wireless access points, hosts and workstations can be configured and interconnected using Cat 6 e cabling. For security, every device can be checked and secure design principles can be followed like access control rules, disabled open ports, passwords, encryption and many more (Smith & Hasan, 2020).

  • Smith, J.D. and Hasan, M. (2020) “Quantitative approaches for the evaluation of Implementation Research Studies,” Psychiatry Research , 283, p. 112521.
  • Sun, J. (2022) “Computer Network Security Technology and prevention strategy analysis,” Procedia Computer Science , 208, pp. 570–576.
  • Zhang, YLiang, R. and Ma, H. (2012) “Teaching innovation in computer network course for undergraduate students with a packet tracer,” IERI Procedia , 2, pp. 504–510.

Different Preemptive ways to resist spear phishing attacks

When it comes to social engineering, phishing attacks are rising and are becoming one of the most common ethical issues as it is one of the easiest ways to trick victims into stealing information. This research topic is based on following different proactive techniques which would help in resisting spear phishing attacks (Xu et al., 2023). This can be achieved by using the Go-Phish filter on the machine which can automatically detect and alert users as soon as the phished URL is detected. It can be performed on the cloud platform where the apache2 server can be configured along with an anti-phishing filter to protect against phishing attacks (Yoo & Cho, 2022).

  • To set up a virtual instance on the cloud platform with an apache2 server and anti-phishing software to detect possible phishing attacks.
  • To research spear phishing and other types of phishing attacks that can be faced by victims (Al-Hamar et al., 2021).

RQ1: Are phishing attacks growing just like other cyber-attacks?

RQ2: How effective are anti-phishing filters in comparison to cyber awareness sessions?

The entire research can be conducted by adhering to quantitative research methodology which helps in justifying all research objectives and questions. The implementation of the anti-phishing filter can be done by creating a virtual instance on the cloud platform which can be configured with an anti-phishing filter. Along with this, some phishing attempts can also be performed to check whether the filter works or not (Siddiqui et al., 2022).

  • Al-Hamar, Y. et al. (2021) “Enterprise credential spear-phishing attack detection,” Computers & Electrical Engineering , 94, p. 107363.
  • Siddiqui, N. et al. (2022) “A comparative analysis of US and Indian laws against phishing attacks,” Materials Today: Proceedings , 49, pp. 3646–3649.
  • Xu, T., Singh, K. and Rajivan, P. (2023) “Personalized persuasion: Quantifying susceptibility to information exploitation in spear-phishing attacks,” Applied Ergonomics , 108, p. 103908.
  • Yoo, J. and Cho, Y. (2022) “ICSA: Intelligent chatbot security assistant using text-CNN and multi-phase real-time defense against SNS phishing attacks,” Expert Systems with Applications , 207, p. 117893.

Evaluating the effectiveness of distributed denial of service attacks

The given research topic is based on evaluating the effectiveness of distributed denial of service attacks on cloud and local environments. Hence, this research can be carried out using a quantitative research method. Cyber attackers find DDoS as one of the most dangerous technological exploitation when it comes to impacting network availability (Krishna Kishore et al., 2023). This research can revolve around scrutinizing the impact of DDoS attacks on the local environment and cloud environment. This can be done by executing DDoS attacks on a simulated environment using hoping or other software(s) to check where it has a higher magnitude (de Neira et al., 2023).

  • To set up a server on the local and cloud environment to target using DDoS attacks for checking which had experienced slowness.
  • To determine types of DDoS attack types, their magnitude and possible mitigation techniques.

RQ: Why do DDoS attacks have dynamic nature and how is it likely to sternly impact victims?

The experimentation for this research can be executed by creating a server on the local and cloud environment. Hence, this research can be carried out using a quantitative research method. These servers can be set up as web servers using apache 2 service. On the other hand, a Kali Linux machine can be configured with DDoS execution software. Each server can be targeted with DDoS attacks to check its effectiveness (Benlloch-Caballero et al., 2023).

  • Benlloch-Caballero, P., Wang, Q. and Alcaraz Calero, J.M. (2023) “Distributed dual-layer autonomous closed loops for self-protection of 5G/6G IOT networks from distributed denial of service attacks,” Computer Networks , 222, p. 109526.
  • de Neira, A.B., Kantarci, B. and Nogueira, M. (2023) “Distributed denial of service attack prediction: Challenges, open issues and opportunities,” Computer Networks , 222, p. 109553.
  • Krishna Kishore, P., Ramamoorthy, S. and Rajavarman, V.N. (2023) “ARTP: Anomaly-based real time prevention of distributed denial of service attacks on the web using machine learning approach,” International Journal of Intelligent Networks , 4, pp. 38–45.

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15 Latest Networking Research Topics for Students

Research in every field is becoming more and more essential because of constant developments around the world. Similar is the case in the field of networking. This is the reason; students who are preparing to master the field of networking need to keep their knowledge of the current state of the art in the field up to date.

However, choosing the right research topic often becomes a tough task for students to carry out their research effectively. That being the case, this list contains 15 latest research topics in the field of networking. Whether you are a seasoned researcher or just starting, this list can provide you with ample inspiration and guidance to drive your research forward in the dynamic and evolving field of Networking.

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Research Topics & Ideas: CompSci & IT

50+ Computer Science Research Topic Ideas To Fast-Track Your Project

IT & Computer Science Research Topics

Finding and choosing a strong research topic is the critical first step when it comes to crafting a high-quality dissertation, thesis or research project. If you’ve landed on this post, chances are you’re looking for a computer science-related research topic , but aren’t sure where to start. Here, we’ll explore a variety of CompSci & IT-related research ideas and topic thought-starters, including algorithms, AI, networking, database systems, UX, information security and software engineering.

NB – This is just the start…

The topic ideation and evaluation process has multiple steps . In this post, we’ll kickstart the process by sharing some research topic ideas within the CompSci domain. This is the starting point, but to develop a well-defined research topic, you’ll need to identify a clear and convincing research gap , along with a well-justified plan of action to fill that gap.

If you’re new to the oftentimes perplexing world of research, or if this is your first time undertaking a formal academic research project, be sure to check out our free dissertation mini-course. In it, we cover the process of writing a dissertation or thesis from start to end. Be sure to also sign up for our free webinar that explores how to find a high-quality research topic. 

Overview: CompSci Research Topics

  • Algorithms & data structures
  • Artificial intelligence ( AI )
  • Computer networking
  • Database systems
  • Human-computer interaction
  • Information security (IS)
  • Software engineering
  • Examples of CompSci dissertation & theses

Topics/Ideas: Algorithms & Data Structures

  • An analysis of neural network algorithms’ accuracy for processing consumer purchase patterns
  • A systematic review of the impact of graph algorithms on data analysis and discovery in social media network analysis
  • An evaluation of machine learning algorithms used for recommender systems in streaming services
  • A review of approximation algorithm approaches for solving NP-hard problems
  • An analysis of parallel algorithms for high-performance computing of genomic data
  • The influence of data structures on optimal algorithm design and performance in Fintech
  • A Survey of algorithms applied in internet of things (IoT) systems in supply-chain management
  • A comparison of streaming algorithm performance for the detection of elephant flows
  • A systematic review and evaluation of machine learning algorithms used in facial pattern recognition
  • Exploring the performance of a decision tree-based approach for optimizing stock purchase decisions
  • Assessing the importance of complete and representative training datasets in Agricultural machine learning based decision making.
  • A Comparison of Deep learning algorithms performance for structured and unstructured datasets with “rare cases”
  • A systematic review of noise reduction best practices for machine learning algorithms in geoinformatics.
  • Exploring the feasibility of applying information theory to feature extraction in retail datasets.
  • Assessing the use case of neural network algorithms for image analysis in biodiversity assessment

Topics & Ideas: Artificial Intelligence (AI)

  • Applying deep learning algorithms for speech recognition in speech-impaired children
  • A review of the impact of artificial intelligence on decision-making processes in stock valuation
  • An evaluation of reinforcement learning algorithms used in the production of video games
  • An exploration of key developments in natural language processing and how they impacted the evolution of Chabots.
  • An analysis of the ethical and social implications of artificial intelligence-based automated marking
  • The influence of large-scale GIS datasets on artificial intelligence and machine learning developments
  • An examination of the use of artificial intelligence in orthopaedic surgery
  • The impact of explainable artificial intelligence (XAI) on transparency and trust in supply chain management
  • An evaluation of the role of artificial intelligence in financial forecasting and risk management in cryptocurrency
  • A meta-analysis of deep learning algorithm performance in predicting and cyber attacks in schools

Research topic idea mega list

Topics & Ideas: Networking

  • An analysis of the impact of 5G technology on internet penetration in rural Tanzania
  • Assessing the role of software-defined networking (SDN) in modern cloud-based computing
  • A critical analysis of network security and privacy concerns associated with Industry 4.0 investment in healthcare.
  • Exploring the influence of cloud computing on security risks in fintech.
  • An examination of the use of network function virtualization (NFV) in telecom networks in Southern America
  • Assessing the impact of edge computing on network architecture and design in IoT-based manufacturing
  • An evaluation of the challenges and opportunities in 6G wireless network adoption
  • The role of network congestion control algorithms in improving network performance on streaming platforms
  • An analysis of network coding-based approaches for data security
  • Assessing the impact of network topology on network performance and reliability in IoT-based workspaces

Free Webinar: How To Find A Dissertation Research Topic

Topics & Ideas: Database Systems

  • An analysis of big data management systems and technologies used in B2B marketing
  • The impact of NoSQL databases on data management and analysis in smart cities
  • An evaluation of the security and privacy concerns of cloud-based databases in financial organisations
  • Exploring the role of data warehousing and business intelligence in global consultancies
  • An analysis of the use of graph databases for data modelling and analysis in recommendation systems
  • The influence of the Internet of Things (IoT) on database design and management in the retail grocery industry
  • An examination of the challenges and opportunities of distributed databases in supply chain management
  • Assessing the impact of data compression algorithms on database performance and scalability in cloud computing
  • An evaluation of the use of in-memory databases for real-time data processing in patient monitoring
  • Comparing the effects of database tuning and optimization approaches in improving database performance and efficiency in omnichannel retailing

Topics & Ideas: Human-Computer Interaction

  • An analysis of the impact of mobile technology on human-computer interaction prevalence in adolescent men
  • An exploration of how artificial intelligence is changing human-computer interaction patterns in children
  • An evaluation of the usability and accessibility of web-based systems for CRM in the fast fashion retail sector
  • Assessing the influence of virtual and augmented reality on consumer purchasing patterns
  • An examination of the use of gesture-based interfaces in architecture
  • Exploring the impact of ease of use in wearable technology on geriatric user
  • Evaluating the ramifications of gamification in the Metaverse
  • A systematic review of user experience (UX) design advances associated with Augmented Reality
  • A comparison of natural language processing algorithms automation of customer response Comparing end-user perceptions of natural language processing algorithms for automated customer response
  • Analysing the impact of voice-based interfaces on purchase practices in the fast food industry

Research Topic Kickstarter - Need Help Finding A Research Topic?

Topics & Ideas: Information Security

  • A bibliometric review of current trends in cryptography for secure communication
  • An analysis of secure multi-party computation protocols and their applications in cloud-based computing
  • An investigation of the security of blockchain technology in patient health record tracking
  • A comparative study of symmetric and asymmetric encryption algorithms for instant text messaging
  • A systematic review of secure data storage solutions used for cloud computing in the fintech industry
  • An analysis of intrusion detection and prevention systems used in the healthcare sector
  • Assessing security best practices for IoT devices in political offices
  • An investigation into the role social media played in shifting regulations related to privacy and the protection of personal data
  • A comparative study of digital signature schemes adoption in property transfers
  • An assessment of the security of secure wireless communication systems used in tertiary institutions

Topics & Ideas: Software Engineering

  • A study of agile software development methodologies and their impact on project success in pharmacology
  • Investigating the impacts of software refactoring techniques and tools in blockchain-based developments
  • A study of the impact of DevOps practices on software development and delivery in the healthcare sector
  • An analysis of software architecture patterns and their impact on the maintainability and scalability of cloud-based offerings
  • A study of the impact of artificial intelligence and machine learning on software engineering practices in the education sector
  • An investigation of software testing techniques and methodologies for subscription-based offerings
  • A review of software security practices and techniques for protecting against phishing attacks from social media
  • An analysis of the impact of cloud computing on the rate of software development and deployment in the manufacturing sector
  • Exploring the impact of software development outsourcing on project success in multinational contexts
  • An investigation into the effect of poor software documentation on app success in the retail sector

CompSci & IT Dissertations/Theses

While the ideas we’ve presented above are a decent starting point for finding a CompSci-related research topic, they are fairly generic and non-specific. So, it helps to look at actual dissertations and theses to see how this all comes together.

Below, we’ve included a selection of research projects from various CompSci-related degree programs to help refine your thinking. These are actual dissertations and theses, written as part of Master’s and PhD-level programs, so they can provide some useful insight as to what a research topic looks like in practice.

  • An array-based optimization framework for query processing and data analytics (Chen, 2021)
  • Dynamic Object Partitioning and replication for cooperative cache (Asad, 2021)
  • Embedding constructural documentation in unit tests (Nassif, 2019)
  • PLASA | Programming Language for Synchronous Agents (Kilaru, 2019)
  • Healthcare Data Authentication using Deep Neural Network (Sekar, 2020)
  • Virtual Reality System for Planetary Surface Visualization and Analysis (Quach, 2019)
  • Artificial neural networks to predict share prices on the Johannesburg stock exchange (Pyon, 2021)
  • Predicting household poverty with machine learning methods: the case of Malawi (Chinyama, 2022)
  • Investigating user experience and bias mitigation of the multi-modal retrieval of historical data (Singh, 2021)
  • Detection of HTTPS malware traffic without decryption (Nyathi, 2022)
  • Redefining privacy: case study of smart health applications (Al-Zyoud, 2019)
  • A state-based approach to context modeling and computing (Yue, 2019)
  • A Novel Cooperative Intrusion Detection System for Mobile Ad Hoc Networks (Solomon, 2019)
  • HRSB-Tree for Spatio-Temporal Aggregates over Moving Regions (Paduri, 2019)

Looking at these titles, you can probably pick up that the research topics here are quite specific and narrowly-focused , compared to the generic ones presented earlier. This is an important thing to keep in mind as you develop your own research topic. That is to say, to create a top-notch research topic, you must be precise and target a specific context with specific variables of interest . In other words, you need to identify a clear, well-justified research gap.

Fast-Track Your Research Topic

If you’re still feeling a bit unsure about how to find a research topic for your Computer Science dissertation or research project, check out our Topic Kickstarter service.

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Investigating the impacts of software refactoring techniques and tools in blockchain-based developments.

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Investigating the impacts of software refactoring techniques and tools in blockchain-based developments is in my favour. May i get the proper material about that ?

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Latest Research Topics in Networking

                Latest Research Topics in Networking offer newfangled project topics for our students from bachelors and master degree (B.E/M.E/M.Phil/M.Tech/MCA) in the field of networking. Networking is the biggest and fastest emerging area, making it hinder students with new research into networking technologies. However, students spend more money on their networking projects. To help our students, we also offer the latest networking projects at optimum cost as far as we also provided 5000+ projects from 120+ countries students from all over the world.

We develop projects both in software and hardware, and in software, we use both open source and proprietary software. We also suggest our students always choose the latest topics because the latest ideas only give something innovative and colorful.

Think well…Always be a part of us… we pose your pioneering projects…..

Topics in Networking

                  Latest Research Topics in Networking covers possible list of topics intended also for under graduate and also post graduate students and scholars. In networking, security is one of the major issues in all types of wired and wireless networks, e.g., cloud networking. There is also a lot of research in the networking field because it is also a vast area that prefers among more users.  

Generally,  networking is defined as the computing devices that exchange information and share ideas among individuals or groups of devices or users using either wired or wireless connection.

Let us see the latest topics in networking,

  • Secure and control sensitive data also in cloud environment (any)
  • The future of IoT and also bio metrics
  • Software defined networking
  • Network security and also cryptography
  • Network Function Virtualization
  • Cognitive computing and also machine learning
  • Micro services architecture
  • Adaptive security
  • Augmented and virtual reality
  • Cloud networking
  • Big data analytics in mobile networking
  • Smart personal assistants
  • Wearable’s in sensor networks
  • Blockchain as a service (BaaS)
  • Containerization (traditional virtualization)
  • Resource allocation SDN
  • Ultra dense wireless networks planning
  • SDN + Virtualized radio Access Networks also with Fog computing
  • Spectrum efficiency enhancement by LTE-U also with Wi-Fi
  • 5G wireless backhaul networks
  • SDN based Elastic optical networks also in cloud.
  • Green mobile cloud network: Green cloudlet
  • C-RAN: Cloud Radio Access Network
  • 5G networks multicasting
  • Traffic engineering also in software defined networks
  • D2D communication in 5G
  • Over Wi-Fi secure device-to-device communication
  • Cloud Robotics
  • 5G networks for visible light communication
  • Big data in mobile cloud networks
  • Prevention and also in detection of network attacks
  • SDN network automation to 802.11ac and also in IPv6

Simulation Tools, Software’s and Programming Languages Used in Networking Projects

Programming languages:.

  • R-programming
  • Matlab and also in scilab

Simulation Software’s:

  • Psimulator2
  • Network simulators (NS2 and also in NS3)

Other Tools:

  • Matlab Simulink
  • Matlab tool boxes
  • Word net tool
  • And also in MADAMIRA tool

        We also provide a few collections of networking and simulation tools, software, and programming languages for developing projects in the networking and other areas. For each project, we give PPT, documents, video files, and also completed code implementation. Our additional support for our students is journal paper writing support, paper publication in high reputed journals, and thesis writing support.

A good beginning is often overt as happy endings…..

Let us come together for your immense research…… , related pages, services we offer.

Mathematical proof

Pseudo code

Conference Paper

Research Proposal

System Design

Literature Survey

Data Collection

Thesis Writing

Data Analysis

Rough Draft

Paper Collection

Code and Programs

Paper Writing

Course Work

Computer Science

Computer networks.

Computer networks allow computers to communicate with one another, and provide the fundamental infrastructures supporting our modern society. Research on computer networks at Yale improves on essential network system properties such as efficiency, robustness, and programmability. The research spans all networking layers, including application-network integration (ANI); highly robust, flexible networking; software-defined networking (SDN) and programmable networking applications; and mobile networking.

Faculty working in this area:

Highlights in this area:.

Topics in Computer and Network Security

Stanford cs 356, fall 2023.

CS 356 is graduate course that covers foundational work and current topics in computer and network security. The course consists of reading and discussing published research papers, presenting recent security work, and completing an original research project.

Course Information

Discussion: Mon/Wed 3:00–4:20 PM. Gates B12 . This course is largely based on in-person discussion rather than lecture. Attendance and participation is expected.

Instructor: Zakir Durumeric Office Hours: M/W 4:30–5:00 PM, or by appointment.

Course Assistant: Kimberly Ruth . Office hours by appointment.

Prerequisites: CS 356 is open to all graduate students as well as advanced undergraduate students. While the course has no official prerequisites, it requires a mature understanding of software systems and networks. Students are expected to have taken CS 155: Computer and Network Security or equivalent.

Topics and Readings

The tentative schedule and required readings for the class are below:

9/27  Introduction

Against security nihilism.

Blog Post. 2016. Chris Palmer.

Mining Your Ps and Qs: Detection of Widespread Weak Keys...

SEC '12 . N. Heninger, Z. Durumeric, E. Wustrow, J.A. Halderman.

How to Read a Paper

10/2  web privacy and security, the web never forgets: persistent tracking mechanisms in the....

CCS '14 . Gunes Acar, Christian Eubank, Steven Englehardt, Marc Juarez, Arvind Narayanan, Claudia Diaz.

Imperfect Forward Secrecy: How Diffie-Hellman Fails in Practice

CCS '15 . D. Adrian, K. Bhargavan, Z. Durumeric, P. Gaudry, M. Green, J.A. Halderman, N. Heninger, A. Springall, E. Thomé, L. Valenta, B. VanderSloot, E. Wustrow, S. Zanella-Beguelin, P. Zimmermann.

10/4  Usability

Alice in warningland: a large-scale field study of browser security.

SEC '13 . Devdatta Akhawe, Adrienne Porter Felt.

...no one can hack my mind”: Comparing Expert and Non-Expert Security Practices

SOUPS '15 . Iulia Ion, Rob Reeder, Sunny Consolvo.

10/9  Authentication and Phishing

The tangled web of password reuse.

NDSS '14 . Anupam Das, Joseph Bonneau, Matthew Caesar, Nikita Borisov, XiaoFeng Wang.

Detecting credential spearphishing in enterprise settings

SEC '17 . Grant Ho, Aashish Sharma, Mobin Javed, Vern Paxson, David Wagner.

10/11  Denial of Service

Inferring internet denial-of-service activity.

SEC '01 . David Moore, Geoffrey Voelker, Stefan Savage.

Understanding the Mirai Botnet

10/16  spam and ecrime, framing dependencies introduced by underground commoditization.

WEIS '15 . Kurt Thomas, Danny Huang, David Wang, Elie Bursztein, Chris Grier, Thomas Holt, Christopher Kruegel, Damon McCoy, Stefan Savage, Giovanni Vigna.

Spamalytics: An Empirical Analysis of Spam Marketing Conversion

CCS '08 . Chris Kanich, Christian Kreibich, Kirill Levchenko, Brandon Enright, Geoffrey Voelker, Vern Paxson, and Stefan Savage.

10/18  Software Attacks

Hacking blind s&p '14 . andrea bittau, adam belay, ali mashtizadeh, david mazieres, dan boneh. sok: eternal war in memory.

S&P '13 . Laszlo Szekeres, Mathias Payer, Tao Wei, Dawn Song.

10/23  Software Defenses

Native client: a sandbox for portable, untrusted x86 native code.

S&P '09 . Bennet Yee, David Sehr, Gregory Dardyk, J. Bradley Chen, Robert Muth, Tavis Ormandy, Shiki Okasaka, Neha Narula, Nicholas Fullagar.

Multiprogramming a 64 kB Computer Safely and Efficiently

SOSP '17 . Amit Levy, Bradford Campbell, Branden Ghena, Daniel B. Giffin, Pat Pannuto, Prabal Dutta, Philip Levis.

10/25  Malware and Supply Chain

Towards measuring supply chain attacks on package managers for interpreted languages.

NDSS '21 . Ruian Duan, Omar Alrawi, Ranjita Pai Kasturi, Ryan Elder, Brendan Saltaformaggio, Wenke Lee.

Before We Knew It: An Empirical Study of Zero-Day Attacks In The Real World

CCS '12 Leyla Bilge and Tudor Dumitraş.

10/30  Side Channels and Information Leakage

Timing analysis of keystrokes and timing attacks on ssh.

SEC '01 . Dawn Song, David Wagner, Xuqing Tia.

Spectre Attacks: Exploiting Speculative Execution

S&P '19 . P. Kocher, J. Horn, A. Fogh, D. Genkin, D. Gruss, W. Haas, M. Hamburg, M. Lipp, S. Mangard, T. Prescher, M. Schwarz, Y. Yarom.

11/1   Hardware

Stealthy dopant-level hardware trojans.

CHES '13 . Georg Becker, Francesco Regazzoni, Christof Paar, Wayne Burleson.

Comprehensive Experimental Analyses of Automotive Attack Surfaces

SEC '11 . Stephen Checkoway, Damon McCoy, Brian Kantor, Danny Anderson, Hovav Shacham, Stefan Savage.

W32.Stuxnet Dossier

Symantec Technical Report . Nicolas Falliere, Liam Murchu, Eric Chien.

11/8  Machine Learning

Towards evaluating the robustness of neural networks.

S&P '16 . Nicholas Carlini and David Wagner.

Outside the Closed World: On Using Machine Learning For Network Intrusion Detection

S&P '10 . Robin Sommer and Vern Paxson.

11/13  Vulnerable Populations / Security For Everyone

A stalker’s paradise: how intimate partner abusers exploit technology.

CHI '18 Diana Freed, Jackeline Palmer, Diana Minchala, Karen Levy, Thomas Ristenpart, Nicola Dell.

A11y Attacks: Exploiting Accessibility in Operating Systems

CCS '14 Yeongjin Jang, Chengyu Song, Simon Chung, Tielei Wang, Wenke Lee.

11/15  Privacy and Dark Patterns

Robust de-anonymization of large sparse datasets.

S&P '08 . Arvind Narayanan and Vitaly Shmatikov.

Dark patterns at scale: Findings from a crawl of 11K shopping websites

S&P '08 . Arunesh Mathur, Gunes Acar, Michael Friedman, Eli Lucherini, Jonathon Mayer, Marshini Chetty, Arvind Narayanan.

11/20   Thanksgiving Break

11/22   thanksgiving break, 11/27  surveillance and anonymity, keys under doormats.

MIT Technical Report '15. H. Abelson, R. Anderson, S. Bellovin, J. Benaloh, M. Blaze, W. Diffie, J. Gilmore, M. Green, S. Landau, P. Neumann, R. Rivest, J. Schiller, B. Schneier, M. Specter, D. Weitzner.

Tor: The Second-Generation Onion Router

SEC '04 . Roger Dingledine, Nick Mathewson, Paul Syverson.

11/29  Government Attacks and Disinformation

When governments hack opponents: a look at actors and technology.

SEC '14 . Bill Marczak, John Scott-Railton, Morgan Marquis-Boire, Vern Paxson.

Disinformation as Collaborative Work: Surfacing the Participatory Nature of Strategic Information Operations

CSCW '19 . Kate Starbird, Ahmer Arif, Tom Wilson.

12/4  Ethics and Problem Selection

The moral character of cryptographic work.

Phillip Rogaway.

Science, Security, and the Elusive Goal of Security as a Scientific Pursuit

S&P '17 . Cormac Herley and P.C. van Oorschot.

12/6   Final Presentations

No required reading. attendance mandatory., course structure.

This course is composed of three parts: reading and discussing foundational papers in every class, reading and presenting recent work for one class, and completing a group research project. Grading will be based on:

Readings and Discussion (30%)

We will read and discuss 1–2 papers for each class. Typically, these are formative works in an area of security. Students should come prepared to actively discuss assigned papers and to make substantive intellectual contributions. This means that you need to thoroughly read each paper ahead of time. Before each section, students will submit a short (400 word) summary and reaction for each each paper, as well as a proposal of one discussion question for class.

Students should submit the reading assignments through Gradescope by 2:30 pm on the day of each class . Paper responses should be completed individually without the assistance of LLMs (e.g., ChatGPT).

Grading will be based 20% on these written responses and 10% on in-class participation. We do not allow any late days for paper reactions, but students may skip two paper summaries and two lectures without penalty. We will take class attendance. However, participation grades are based on not only attendence, but active participation during class discussion.

Do not underestimate the amount of time required to properly read and process a research paper. Expect to spend several hours preparing for each section.

Topic Presentation (15%)

While reading formative papers helps to demonstrate how a subfield started, it oftentimes leaves us wondering how the area has evolved. To fill this gap, each student in the class will present one recent paper during the quarter topically relevant to that day's class. At the start of the quarter, students will have the opportunity to sign up for the topic/date that they want to present their paper. Stuents will have 12-15 minutes to present their paper.

Students are expected to do a literature search and to select a paper that was published in the last three years from a top-tier venue in security (e.g., IEEE Security and Privacy, USENIX Security, ACM Computer or Communication Security) or adjacent field (e.g., CHI, NSDI, ASPLOS, PLDI, etc.). Students should submit their papers to approval to the teaching staff a week prior to their presentation.

Course Project (55%)

Students will complete a quarter-long original research project in small groups (1–3 students) on a topic of their own choosing. Groups will present their work during the last two sections as well as submit a 6–10 page report, similar to the papers we read in the course.

  • Project Proposal (5%). Project groups will meet with course staff to discuss their project during the third week of class and submit a one page project proposal. Written proposals are due on 10/16.
  • Mid-Quarter Progress Report (5%). Submit a short (1–2 pages) progress report part way through the quarter. The report should indicate what has been accomplished, what work is remaining, obstacles the team has encountered, and any preliminary data or insights. Due 11/17.
  • Class Presentation (10%). Each group will give a 10 minute class presentation during the last week of the course.
  • Final Paper (35%). Groups will submit a final project report similar to the papers we read in the course. Papers should be 6–10 pages and use the USENIX LaTeX template . It may be helpful to read Writing Technical Articles if you haven't previously published any work in computer science. Due 12/8.

Students should submit all reports through Gradescope by 11:59PM on the day of each deadline.

In past offerings, well-executed projects have led to publications at top-tier security conferences and workshops. I'm happy to work with groups to publish their work.

This class has no final exam. Attendance on 12/6 is required.

  • Our Promise
  • Our Achievements
  • Our Mission
  • Proposal Writing
  • System Development
  • Paper Writing
  • Paper Publish
  • Synopsis Writing
  • Thesis Writing
  • Assignments
  • Survey Paper
  • Conference Paper
  • Journal Paper
  • Empirical Paper
  • Journal Support
  • Top 5 Interesting Computer Network Research Topics

A computer network is a network of diverse computing hardware linked through different communication technologies to share various resources . The communication links of the network can be either wired (cables) or wireless (radio waves / IR signals).

This page shows you useful information on Computer Network Research Topics, Projects with Source Code, Research Areas, Project Topics, and Tools!!!

Moreover, the network can be differentiated in the characteristics of constrained resources, network structure, requests history/demand, communication technologies , and more. However, it is flexible to share resources, and it has some technical challenges in real-time development. Here, we have given you the common services that we offer for overcoming network issues.

Our Approaches and Services to Solving Computer Network Issues

  • Communication technologies selection
  • Communication protocols in the network
  • Performing both conceptual and practical research
  • Study in qualitative and quantitative aspects
  • Simulation Models
  • Proofs / Theorems / Prototypes Testing / Use Cases
  • Experiments for Various Simulation Scenarios
  • Graphical / Tabular Representation of Results
  • Developing New Techniques
  • Thinking Novel Ideas
  • Multiple Evaluations
  • IEEE Standards Refinement

The layering approach in networking is used to divide the message into various chunks . Basically, there are seven layers in the networking process where each layer has unique responsibilities. All these layers co-operatively work together to transfer the message from one end to another (i.e., source to destination ). Now, we can see the available layers and their function in sequential order.

What are the layers of computer networks?

  • Physical Layer – Used for offering mechanical / electrical needs, distribute the bits through transmission medium
  • Data Link Layer – Used for offering hop-to-hop distribution, arrange the bits into frames
  • Network Layer – Used for offering internetworking, pass over the packets between source and destination
  • Transport Layer – Used for offering error correction and process-to-process distribution
  • Session Layer – Used for launching and manage temporary sessions
  • Presentation Layer – Used for data translation, compression, and encryption
  • Application Layer – User for users to access the network resources / services

With an aim to support wireless communications, numerous different technologies have been launched.  Before selecting this technology, one should undergo deep study on which is more suitable for their computer network projects . Our research team will help you in both business/individual if you need the best guidance over that selection of innovative computer network research topics . Usually, we recommend the technology based on the requirement of your selected networking projects for final year students . For your information, here we have given you a few lists of communication technologies,

Communication Technologies in Computer Networks

  • Wi-Fi and Wi-Max
  • Radio Frequency Identification (RFID)
  • Ultra-Wideband, Bluetooth and Zigbee
  • Global Positioning System (GPS)
  • Mobile Communication (4G, 5G, 5G Beyond and 6G)
  • Radar and Satellite Communication
  • 3GPP – LTE-M, EC-GSM and Narrowband-IoT
  • Non-3GPP – Sigfox, Wieghtless and LoRa

In recent days, you can witness the gradual growth of computer networks in networking industries through many new developments. It includes so many technologies to portrait the actual networking industry’s performance. Here, we have given you some new networking technologies that are expected to master the next networking industries. .

Current Technologies in Computer Networks

  • Artificial Intelligence (AI) and Cloud Repatriation
  • Software Defined Networks
  • Fog-Edge Computing
  • UAV-Wireless Data Links
  • Responsive Internet Architecture
  • Multiple Cloud Services Technology
  • Internet of Things and Inter-Networking
  • Quantum and Serverless Computing
  • 5G enabled Nano Technology
  • Digital Twin and Machine Learning (ML)
  • Digital Communications
  • Network Communications Protocols

For illustrative purpose,  Digital Communication  work in accordance with enabling communication technologies, modulation, signal processing projects, channel modeling, and error control . Similarly,  Network Communications Protocols  take an in-charge of routing, resource allocation, data distribution, and medium access control.

Both technologies/areas have high capabilities in a different dimension of the networking process. And they are network designing, model construction, networking testing on testbeds, experimental analysis, and performance assessments. Our researchers have given you the currently ongoing of innovative computer network research topics mentioned below for your reference.

Latest Computer Network Research Topics

  • Enhancing System Robustness in Decentralized Network
  • Improving Network Quality of Services and Resource Usage
  • SLA–Aware Resource Scheduling and Provisioning
  • Network Architectures Design and Processes Management

How to develop computer networks projects with source code?

Basically, networking is a widespread process where network construction and deployment in the real world is a challenging job. So, the entire process is fragmented into different tasks where they are performed by a set of skilled networking engineers as follows,

  • Software Developer – Design and build software applications
  • Networking Experts – modeling the network structure
  • Database Admin – Store and manage the network information
  • Support Specialist – Analyze the connected entities of the system
  • Programmer – Develop the suitable code works for achieving required performance

For research purposes, we can simulate the original network behavior and performance inappropriate simulation tools. Most importantly, it reduces the cost of real-time implementation and deployment.

Our developers have long-term experience in handling networking concepts . So, if you need the best Computer Networks Projects with Source Code support , you can approach our team. Below, we have also mentioned our qualified services in your project.

  • We do both conceptual and practical study on recent research topics
  • We design unique network simulation models, proof-of-concept prototypes and investigational testbeds
  • We employ result guaranteed new technologies to upgrade and assess the existing standard of networking systems
  • We develop own algorithm, protocols and hybrid techniques based on project requirements
  • We precisely access the network performance using suitable network parameters for comparative study of different systems

Performance Analysis of Computer Networks

Now, we can see the performance measurement of the networking model. Through the sophisticated simulation tool / experimental testbeds , we can develop any kind of network scenario. Once the model is processed, then the efficiency of the model is verified by several metrics. Here, we have given you the metrics along with different modelling techniques .

  • Medium Access Control – Retransmissions Delay, Collisions and Packet loss
  • Network Protocols – Latency, Throughput and Packet loss
  • RF Channel Models – Noise, Shadowing and Fading
  • Spectrum (Sense and Observation) – Latency and Detection Trustworthiness
  • Links and Transceivers – Block error ratio and Signal-to-Noise Ratio (SNR)

What is computer network simulation?

Simulate the network model based on the code of the software application . Through code, we can instruct the model to perform our project requirements. At the end of the simulation, it yields the overall performance and behaviour of the network in different dimensions and metrics. Further, it also measures the communication between the network entities.   

Purposes of source code

The source code of software has the main responsibility to create strong basements for designing and simulating the network model . Through the code only, the developers can make the smart work to tackle the problem in a simplified way. Effective code work is also a part of the contribution in research.

Since your code can help for learning or reusability (other application development), for your clarity, our developers will explain the implementation of research methodologies while delivering Computer Networks Projects with Source Code . Below, we have given you the different simulations of real-time network models,

How does computer network simulation works?

  • Plan and design the model
  • Develop the suitable hypothesis model
  • Forecast the hypothetical aspects
  • Perform comparative study to improve the hypothesis
  • Simulate the developed model
  • Based on experimental results, relate and enhance the hypothesis / model
  • Do the experiments and get the results

So far, we have discussed computer networks, network layers, communication technologies, current research areas, computer network research topics, project simulation, and performance estimation . Now, our development team has a list of widely used network simulator tools.

Network simulators let the users modify the simulator operations for their project needs. Then the users can analyze the system performance and entity behavior under different circumstances. Further, it supports communication standards/protocols like TCP, WLAN, CR, Wi-Max, WSN , and many more. Here, we have given you the list of a few best result yielding simulators which is more apt for computer network simulations,

  • Component-based network simulator with graphical user interface support
  • Allow to design traffic models, decentralized system, protocols, computer networks, multi-processors, and many more
  • Further, it enables animated and responsive simulation in modular environs
  • Empower to design and deploy network application, device and infrastructure
  • Develop predictive model, protocol and communication networks to interpret the network functionalities
  • Support both real-time wired and wireless models
  • Allow to create Finite State Automata for figuring out the network behavior
  • Easy to design and develop traffic models
  • Utilize QualNet analyzer to understand the obtained simulated outcome
  • Enabled OS: Linux and Windows

For instance, NS3 (network Simulator 3) is detailed here.

NS3 is one of the best simulation tools to design and simulate networking projects . With the help of this tool, we can virtually design different nodes through Helper classes. By the by, it enables the installation of internet stacks, applications, devices, and many more. Further, we can insert parameters in the channel for performance evaluation in implementing computer network research topics . And let them produce traffic at runtime and pass the packets from source to destination through the selected route path. The other special features are given as follows,

  • Create pcap file to get the core information of the transmitting packets. For instance: Source IP, Sequence no, Destination IP, etc. Employ Wireshark tool to view the pcap.
  • Trace the network route for assess number of packets send/receive. For this purpose, the trace files will be produced automatically to monitor whole network.
  • Easy to plot the graph from obtained simulation outcome in with assurance of preciseness.
  • Network Animator is released to depict the realistic view of the network through animation. It shows you the real structure and how the data are transferred between nodes.

To sum up, we have sufficient technical professionals to support you in all the latest research areas of computer networks . In addition, our developments also give you the best assistance in project development from tool selection to result in an assessment. So, if you need our reliable service computer network research topics,  projects with source code then communicate our team.

MILESTONE 1: Research Proposal

Finalize journal (indexing).

Before sit down to research proposal writing, we need to decide exact journals. For e.g. SCI, SCI-E, ISI, SCOPUS.

Research Subject Selection

As a doctoral student, subject selection is a big problem. Phdservices.org has the team of world class experts who experience in assisting all subjects. When you decide to work in networking, we assign our experts in your specific area for assistance.

Research Topic Selection

We helping you with right and perfect topic selection, which sound interesting to the other fellows of your committee. For e.g. if your interest in networking, the research topic is VANET / MANET / any other

Literature Survey Writing

To ensure the novelty of research, we find research gaps in 50+ latest benchmark papers (IEEE, Springer, Elsevier, MDPI, Hindawi, etc.)

Case Study Writing

After literature survey, we get the main issue/problem that your research topic will aim to resolve and elegant writing support to identify relevance of the issue.

Problem Statement

Based on the research gaps finding and importance of your research, we conclude the appropriate and specific problem statement.

Writing Research Proposal

Writing a good research proposal has need of lot of time. We only span a few to cover all major aspects (reference papers collection, deficiency finding, drawing system architecture, highlights novelty)

MILESTONE 2: System Development

Fix implementation plan.

We prepare a clear project implementation plan that narrates your proposal in step-by step and it contains Software and OS specification. We recommend you very suitable tools/software that fit for your concept.

Tools/Plan Approval

We get the approval for implementation tool, software, programing language and finally implementation plan to start development process.

Pseudocode Description

Our source code is original since we write the code after pseudocodes, algorithm writing and mathematical equation derivations.

Develop Proposal Idea

We implement our novel idea in step-by-step process that given in implementation plan. We can help scholars in implementation.

Comparison/Experiments

We perform the comparison between proposed and existing schemes in both quantitative and qualitative manner since it is most crucial part of any journal paper.

Graphs, Results, Analysis Table

We evaluate and analyze the project results by plotting graphs, numerical results computation, and broader discussion of quantitative results in table.

Project Deliverables

For every project order, we deliver the following: reference papers, source codes screenshots, project video, installation and running procedures.

MILESTONE 3: Paper Writing

Choosing right format.

We intend to write a paper in customized layout. If you are interesting in any specific journal, we ready to support you. Otherwise we prepare in IEEE transaction level.

Collecting Reliable Resources

Before paper writing, we collect reliable resources such as 50+ journal papers, magazines, news, encyclopedia (books), benchmark datasets, and online resources.

Writing Rough Draft

We create an outline of a paper at first and then writing under each heading and sub-headings. It consists of novel idea and resources

Proofreading & Formatting

We must proofread and formatting a paper to fix typesetting errors, and avoiding misspelled words, misplaced punctuation marks, and so on

Native English Writing

We check the communication of a paper by rewriting with native English writers who accomplish their English literature in University of Oxford.

Scrutinizing Paper Quality

We examine the paper quality by top-experts who can easily fix the issues in journal paper writing and also confirm the level of journal paper (SCI, Scopus or Normal).

Plagiarism Checking

We at phdservices.org is 100% guarantee for original journal paper writing. We never use previously published works.

MILESTONE 4: Paper Publication

Finding apt journal.

We play crucial role in this step since this is very important for scholar’s future. Our experts will help you in choosing high Impact Factor (SJR) journals for publishing.

Lay Paper to Submit

We organize your paper for journal submission, which covers the preparation of Authors Biography, Cover Letter, Highlights of Novelty, and Suggested Reviewers.

Paper Submission

We upload paper with submit all prerequisites that are required in journal. We completely remove frustration in paper publishing.

Paper Status Tracking

We track your paper status and answering the questions raise before review process and also we giving you frequent updates for your paper received from journal.

Revising Paper Precisely

When we receive decision for revising paper, we get ready to prepare the point-point response to address all reviewers query and resubmit it to catch final acceptance.

Get Accept & e-Proofing

We receive final mail for acceptance confirmation letter and editors send e-proofing and licensing to ensure the originality.

Publishing Paper

Paper published in online and we inform you with paper title, authors information, journal name volume, issue number, page number, and DOI link

MILESTONE 5: Thesis Writing

Identifying university format.

We pay special attention for your thesis writing and our 100+ thesis writers are proficient and clear in writing thesis for all university formats.

Gathering Adequate Resources

We collect primary and adequate resources for writing well-structured thesis using published research articles, 150+ reputed reference papers, writing plan, and so on.

Writing Thesis (Preliminary)

We write thesis in chapter-by-chapter without any empirical mistakes and we completely provide plagiarism-free thesis.

Skimming & Reading

Skimming involve reading the thesis and looking abstract, conclusions, sections, & sub-sections, paragraphs, sentences & words and writing thesis chorological order of papers.

Fixing Crosscutting Issues

This step is tricky when write thesis by amateurs. Proofreading and formatting is made by our world class thesis writers who avoid verbose, and brainstorming for significant writing.

Organize Thesis Chapters

We organize thesis chapters by completing the following: elaborate chapter, structuring chapters, flow of writing, citations correction, etc.

Writing Thesis (Final Version)

We attention to details of importance of thesis contribution, well-illustrated literature review, sharp and broad results and discussion and relevant applications study.

How PhDservices.org deal with significant issues ?

1. novel ideas.

Novelty is essential for a PhD degree. Our experts are bringing quality of being novel ideas in the particular research area. It can be only determined by after thorough literature search (state-of-the-art works published in IEEE, Springer, Elsevier, ACM, ScienceDirect, Inderscience, and so on). SCI and SCOPUS journals reviewers and editors will always demand “Novelty” for each publishing work. Our experts have in-depth knowledge in all major and sub-research fields to introduce New Methods and Ideas. MAKING NOVEL IDEAS IS THE ONLY WAY OF WINNING PHD.

2. Plagiarism-Free

To improve the quality and originality of works, we are strictly avoiding plagiarism since plagiarism is not allowed and acceptable for any type journals (SCI, SCI-E, or Scopus) in editorial and reviewer point of view. We have software named as “Anti-Plagiarism Software” that examines the similarity score for documents with good accuracy. We consist of various plagiarism tools like Viper, Turnitin, Students and scholars can get your work in Zero Tolerance to Plagiarism. DONT WORRY ABOUT PHD, WE WILL TAKE CARE OF EVERYTHING.

3. Confidential Info

We intended to keep your personal and technical information in secret and it is a basic worry for all scholars.

  • Technical Info: We never share your technical details to any other scholar since we know the importance of time and resources that are giving us by scholars.
  • Personal Info: We restricted to access scholars personal details by our experts. Our organization leading team will have your basic and necessary info for scholars.

CONFIDENTIALITY AND PRIVACY OF INFORMATION HELD IS OF VITAL IMPORTANCE AT PHDSERVICES.ORG. WE HONEST FOR ALL CUSTOMERS.

4. Publication

Most of the PhD consultancy services will end their services in Paper Writing, but our PhDservices.org is different from others by giving guarantee for both paper writing and publication in reputed journals. With our 18+ year of experience in delivering PhD services, we meet all requirements of journals (reviewers, editors, and editor-in-chief) for rapid publications. From the beginning of paper writing, we lay our smart works. PUBLICATION IS A ROOT FOR PHD DEGREE. WE LIKE A FRUIT FOR GIVING SWEET FEELING FOR ALL SCHOLARS.

5. No Duplication

After completion of your work, it does not available in our library i.e. we erased after completion of your PhD work so we avoid of giving duplicate contents for scholars. This step makes our experts to bringing new ideas, applications, methodologies and algorithms. Our work is more standard, quality and universal. Everything we make it as a new for all scholars. INNOVATION IS THE ABILITY TO SEE THE ORIGINALITY. EXPLORATION IS OUR ENGINE THAT DRIVES INNOVATION SO LET’S ALL GO EXPLORING.

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research paper topics computer networking

Thesis and Research Topics in Computer Networking

Students who find programming complex and challenging mostly go for networking field in computer science engineering. But even after indulging in this field they are often confused about which topic to choose for the project or for an M.Tech thesis. Here is the list of some of the good topics in computer networking with a basic introduction which you can choose for your project or thesis. You can also get thesis help and thesis guidance on these topics from experts. In the infographic below you will find the list of latest thesis and research topics in computer networking .

List of the best thesis topics in networking:

Wireless Sensor Networks

Wireless Ad hoc Network

Vehicular Ad hoc Networks

Network Security

  • Evaluate and implement energy efficient protocol for data aggregation in wireless sensor networks
  • Node Localization Approach in underwater acoustic network using bio-inspired method
  • Evaluate and implement sink hole attack isolation method in wireless sensor networks
  • The three level hierarchical routing protocol for data aggregation in wireless sensor networks
  • Design and implement black hole attack isolation method in wireless sensor networks
  • The clock synchronization method in wireless sensor network for the efficient data transmission method
  • The efficient channel sensing scheme for wireless body area network
  • Design secure scheme for data transmission in opportunistic routing in wireless sensor networks
  • The misdirection attack isolation scheme in multilevel   hierarchical  routing protocol in WSN
  • To propose fault tolerance scheme for wireless sensor networks
  • To propose novel approach to maintain quality of service in the network for link failure
  • To propose hybrid routing protocol based on the bio-inspired methods in mobile ad hoc network
  • The threshold based mechanism for the isolation of worm hole attack in mobile ad hoc networks
  • Evaluate and implement clustering based method for the isolation of black hole attack in mobile ad hoc network
  • The novel method for the congestion avoidance in mobile ad hoc network to maintain quality of service in the network ‘
  • The multicasting scheme for the path establishment in mobile ad hoc networks
  • Implement and evaluate Sybil attack isolation scheme for vehicular ad hoc networks ‘
  • To propose novel scheme for the detection of DDOS attack in vehicular ad hoc networks
  • The zonal based routing scheme for path establishment in vehicular ad hoc networks
  • The secure and efficient message authentication scheme for vehicular ad hoc networks
  • The location based routing scheme for path establishment in vehicular ad hoc networks
  • The tree based multicasting scheme in vehicular ad hoc network for data transmission

TCP/IP Protocol

Now our systems computer, laptop, mobiles, and other internet devices are connected to one node to communicate with each other and to get internet access, and this whole process called a network system. They all are connected with the physical medium so that’s why they can be guided as wireless network system or copper wire network system to provide calculated data speed in the notes time frame. It spreads motions as electromagnetic waves or light pulses. The direct connection between two nodes are considered as guided medium and is more reliable and the occurrence of error has very less as compared to another medium. Un-guided medium is used in so many systems to provide multiple outputs at the same time. But in this system error rate is high.

To send or receive the internet signal, the two nodes follow a set of protocol which is known as IP (internet protocol). Each system is designed to follow this set of rules itself to generate maximum speed with a time limit. These protocols are designed in a manner that they follow these rules one by one. Each layer follows the protocol of the upper layer to provide services and then that layer follows the upper layer, this process will continue until data is transmitted or received. Lower layer always follows the basic set of rules and upper layer follows the advanced set of rules. Service provided by both layer will be different in terms of protocol instructions.

First data is sent or received in the application layer and then in the transport layer, after following the set of rules data then is sent to network layer to link layer and after that data has been sent to physical layer to the user. Data is divided into small packet format to provide consistency. Common internet protocol is RTP (Real-time Transport Protocol). which is used to provide information at the time of gaming, movie or music streaming. first two-layer are used to transmit or receive the information in small data packets.

Two main internet protocols are UDP (user datagram protocol) and TCP (transport control protocol). UDP and TCP both have their advantages and disadvantages of use. UDP is used because of their simplicity and with the use of UDP data can be sent immediately. But at the same time, it is unreliable as compared to TCP. TCP, then again, directs the sending rate concerning the client’s ability – stream control – and with respect to the limit of the system – clog control. It conveys the information altogether and guarantees that all information achieve the beneficiary. The hidden layers, similar to the system layer, are not required to perform solid conveyance.

TCP(Transmission Control Protocol) is a set of rules to access the Internet with the interconnection of various Internet-based devices. We can say it is a communication protocol in which there is a host with access to the Internet. This is a good topic for an M.Tech thesis in networking. If you are planning to choose this networking topic for research, then here is some basic introduction to this.

TCP/IP provides end to end data transmission between devices along with some other functionalities like addressing, mapping and acknowledgment. TCP/IP is a combination of two protocols. TCP controls the messages by dividing them into packets. IP controls the transmission of these packets from the sender to the receiver.

TCP/IP protocol layers

Following are the four layers of TCP/IP:

Application layer

Transport layer

Internet layer

Physical layer

Working of TCP/IP protocol

Client/Server model is used as a mode of communication by TCP/IP. It works in the following way:

Application layer consists of various applications for data exchange with use of protocols like HTTP(Hypertext Transfer Protocol), FTP(File Transfer Protocol), SMTP(Simple Mail Transfer Protocol)

The transport layer provides end-to-end communication between the host and the user. It uses protocol UDP(User Datagram Protocol).

Internet layer is responsible for the transfer of packets over the network and uses IP(Internet Protocol) for this purpose.

The physical layer provides interconnection between the nodes.

Advantages of TCP/IP protocol

It can be easily modified.

It is compatible with all the operating systems.

It is scalable in determining the most appropriate path.

Thus it is a good topic for M.Tech thesis as well as for research. A student can get thesis help on this topic from experts specialized in thesis guidance. You can also explore the Internet for further details on this topic.

Network Simulation Tools

Here is the list of commonly used network simulators having different features:

Another good computer networking topic for an M.Tech thesis is NS2 . NS stands for Network Simulator. It is an open-source, discrete-event based network simulator mainly used for research purpose and for teaching. It provides help in simulating routing protocols like IP, TCP, UDP, etc. It creates a simulation environment for studying the network. Following steps are followed while creating a simulation environment:

Topology Definition

Development of the model

The configuration of the link

Analysis of the problem

Visualization

NS2 create network topologies and then examines the behavior of the network under any event. The behavior is analyzed by tracing down the events. NS2 provides text-based as well as animation-based simulations.

Advantages of NS2

It has the ability to support multiple protocols.

It can represent network traffic graphically.

It can also support multiple algorithms for routing and queuing.

NS2 is a very good topic for an M.Tech thesis in the computer networking field. You will not only get theoretical knowledge but also practical experience of network simulator tool. You can get thesis guidance about NS2 from an expert who has practical knowledge about how to use this tool.

MANET stands for mobile ad hoc Network and is another good choice for an M.Tech thesis topic in networking. In MANET, the nodes are self-configurable and have the ability to move freely in any direction and can link with other devices frequently. MANET was originally used as a military project in defense. MANET have the challenges of weak signal strength, reliability, power consumption along with some other problems.

Characteristics of MANET

Each node is independent in nature i.e. each node act as the host as well as the router.

It is based on the distributed nature of operation for security and configuration.

The network is dynamic in nature i.e each node can join and exit the network at any time.

The nodes in the network are associated with less memory and power.

In MANET, the bandwidth remains fluctuating.

MANET creates a symmetric environment such that all the nodes have identical features like responsibilities and capabilities.

Hurdles in the path of MANET

There are certain hurdles in the path of MANET, which it has to overcome. Some of these are:

The reliability of the transmission is affected by certain factors like data loss, interference, and blockage.

The rate of transmission is limited to a certain range thus there is a reduced data rate.

Packet loss can occur while transmission of data.

Frequent path breaks.

Lack of firewall results in security issues in the network.

This was just the introduction to MANET to give an overview of what it is if you are going with this topic for your M.Tech thesis.

Network Security is the set of rules to ensure the safety of the network of an organization or personal network. You can choose this topic for your M.Tech thesis if you have a complete understanding of how the data is transferred over the network. Network Security also include security of physical hardware devices. Network Security in software means providing authorized access to the network by means of ids and passwords.

Whenever a user tries to access the network, his authenticity is checked by means of ids and passwords. This is done to prevent any malicious user from entering the network by the motive of hacking it.

Types of attacks to network

Active Attack – In this type of attack, a hacker tries to make changes to data while it is being sent from one node to another.

Passive Attack – In this type of attack, an outsider monitors system of the organization consistently to find vulnerable ports.

Network Security Tools

Following are some of the tools employed in network security:

Thus if you really have significant knowledge(practical + theoretical) of networking tools, security

measures then you should choose this topic for M.Tech thesis. Besides, you will get thesis help as well as guidance on this topic from computer networking experts.

Network Topologies

Network Topology is the arrangement of nodes in the network both physical and logical. It is an easy topic for M.Tech thesis. Following are some of the common physical topologies:

Bus – In the bus topology, each node is connected to the main cable known as bus such that every node is directly connected to every other node.

Star – In the star topology, each node is connected to a central hub such that all the nodes are indirectly connected to each other.

Ring – In this topology, the nodes form a closed loop such that the adjacent nodes are in direct connection with each other.

Token Ring – In the token ring topology, a protocol is used. A token is passed from one node to another. A node that wants to transfer data should acquire the token.

Mesh – In the mesh network, each node is directly connected to every other node. It can be a full mesh or partial mesh network.

Tree – It is the interconnection of bus topology and star topology.

Daisy Chain – In this topology, each node is connected to two other nodes but do not form a closed loop like ring topology.

Hybrid – It is a combination of two or more topologies.

If you are afraid of complex topics in networking for M.Tech thesis, then this topic is for. It is relatively simple to understand and work on. Just go for it.

It is another major topic in computer networking and also a good choice for a thesis or project. Ipv4 is the fourth version of Internet protocol while Ipv6 is the sixth version of Internet protocol.

Characteristics of IPv4

It uses a 32-bit address.

The address is written in decimal separated by dots.

The header includes a checksum.

Broadcast addresses are used to send data packets to other nodes.

In this the Internet Protocol Security is optional.

Characteristics of Ipv6

It uses a 128-bit address.

The address is written in hexadecimal separated by colons.

The header does not include a checksum.

Broadcast addresses are not used to send data packets.

The Internet Security Protocol is compulsory.

It is a good area to study how data transfer takes place over the internet. You will study the IP data packets of Ipv4 and Ipv6. You can select this as your M.Tech thesis topic.

OSI stands for open system interconnection. It is another good topic for an M.Tech thesis in the computer networking field. It provides a networking framework to implement protocols in layers. There are seven layers of OSI Model:

Physical Layer – This layer is responsible for transferring digital data from the source to the destination.

Data Link Layer – This layer checks error in data along with the MAC address. It turns bits into data frames.

Network Layer – This layer checks whether the data has reached the destination or not by examining the source and the destination address.

Transport Layer – This layer transfers data over the network by using the TCP protocol.

Session Layer – This layer manages the events and keeps them in sequence. It supports multiple types of connections.

Presentation Layer – It looks after the syntax along with encryption and decryption for the application layer above it.

Application Layer – It provides end-to-end user applications using protocols like HTTP, FTP, SMTP.

research paper topics computer networking

It is different from the TCP/IP model. You will get a thesis guide on this topic from computer networking experts.

However, with the change of social economy, computer networking system changes a lot and have also changed people’s lifestyle in a lot of aspects. As we know with the increasing demand for network speed, a number of network provider has been also increased. Due to the maximum number of the provider, one can easily access the high speed of the internet at a low cost. Local area network which is used in lots more other sectors like medical, military, education and science. Now we can see every-one need their own personal LAN (Local Area Network). Now LAN is not only for big enterprises but it is also available for small schools and families which are looking for high speed of data in the minimum amount.

The current speed of LAN is not enough for a user so that’s why companies are doing more research and study to provide the data at higher speed without the use of high bandwidth. But as we know if we want higher speed in a short time with a wide area, bandwidth will be increased to 30% to 300%. Now one of the very well known company called Huawei launched its 5G network, which is faster than the USA 5G network. So with this network Bandwidth also increased by 300%. It is beneficial for us but at the same time, a higher bandwidth is also not good for human life.

Various exploratory and early business LAN innovations were created during the 1970s. But then a new term called WLAN is introduced to the world in 1997 to provide a wireless network. This technology got famous in a very short span of time with the name of WiFi (Wireless Fidelity).

It stands for Wireless Local Area Network. It can be another good choice for an M.Tech thesis topic in computer networking. It is a wireless distribution method that uses high-frequency radio waves with a single access point to the Internet. In other words, it is wireless communication between two or more devices such that users can move around in a limited range area. It is most commonly used in homes or offices. The component connected to WLAN is referred to as the station. There are two types of stations – Access Point, Client.

Access Points are the base stations that transmit and receive radio frequencies for wireless-enabled devices. Clients are mobile phones, laptops, desktops connected to the wireless network.

Modes of Operation of WLAN

There are two modes of operation of WLAN:

Infrastructure – In infrastructure mode, base station act as the access point and all the nodes communicate through this point.

Ad hoc – In Ad hoc mode, mobile devices transmit data directly using peer to peer method. In this, there is no base station.

WLAN Advantages

It can support a large number of devices.

It is easy to set up wireless LAN than installing cables for the wired network.

It is easier to access a wireless network than a wired network.

WLAN Disadvantages

It is difficult to expand the network.

It faces security issues like hacking.

Interference is another problem with WLAN.

WLAN is another easier topic for an M.Tech thesis. It is used everywhere. You can take thesis help on this topic from networking professionals.

Cryptography

It is the science of maintaining the privacy of data. It is also an easy topic to choose for your M.Tech thesis in networking. There are three main objectives of cryptography used in transferring data over the network:

Confidentiality

Authentication

research paper topics computer networking

Cryptography employs two techniques for maintaining the privacy of data:

Encryption – In encryption, the plain text is converted into some other form known as ciphertext.

Decryption – In this technique, the converted text i.e the ciphertext is translated back to the original text.

There are two algorithms for cryptography. In a symmetric key, both the sender and the receiver share the same key for encryption and decryption.

In an asymmetric key, both the users have different keys respectively for encryption and decryption.

This is a familiar topic and very easy to understand. Take the guidance of a thesis expert about this area to start with this topic.

IEEE stands for Institute of Electrical and Electronics Engineers. IEEE 802 is a very challenging and a very good topic for your thesis. IEEE 802 comes under IEEE and deal with LAN(Local Area Network) and MAN(Metropolitan Area Network). It specifies certain services and protocols for the data link layer and physical layer of the OSI model. IEEE is further subdivided into 22 parts that cover a wide range of services.

IEEE 802 subdivides data link layer into two layers namely: Logical Link Layer(LLC)

Media Access Control(MAC)

You can choose any of its subfields as a part of your project or thesis. It is a very good area to explore.

These were some of the few topics for an M.Tech thesis in computer networking. You can also choose any one of these for research in networking or for your project. You can explore more on these topics.

If you need help with thesis topics in computer networking, you can contact us . You can call us on this number +91-9465330425 or email us at [email protected] for M.Tech and Ph.D. thesis help in computer networking. You can also fill the query form on the website.

For more details Contact Us.  You can call us on this number +91-9465330425 or drop an email at   [email protected]   for any type of dissertation help in India. You can also fill the query form on the website. 

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A network is a group of two or more network devices is used for communication. These devices and nodes in the question are connected through physical wired or wireless connections . The key purpose of the network is that connects at least two or three components and connected.  If you are looking for innovative network project topics , then look at this page to know more about the networks.

Important Stages of Research

  • Carried out literature review
  • Determine the research problems
  • Conducts research and collect results
  • Produce the original research
  • Start writing research work

There are several problems raised in-network for communication. In particular real-time applications such as video, transmission require high QoS performance and QoE results . Hence, we must know the important problems in networks. 

Research Network Project Topics for Engineering Students

What significant problem do wireless networks have?

  • Low bandwidth with packet collisions and interference
  • Low transmission strength
  • Lack of network management

Previously, we listed three problems in networks, and the following discusses one of the important issues in the network. Now the network management problem to craft innovative network project topics is in detail here. 

Why Network Management is important?

  • To improve the network availability and improves the maintenance of the network
  • To enrich the utilization of tools for network manage, and monitor of the network  troubleshooting
  • To reduce the network complexity by centralize the control of all network components
  • To reduce the cost of network management and maintenance and operational expenses.
  • To minimize the network, link and node failures in network and manage the network resources

Trending Network Research Topics

Network / information security

  • Sensor & mobile ad hoc network security
  • Internet security & applications
  • Service and systems
  • QoS network security
  • Intrusion detection & prevention

Mobile and Wireless Network

  • Wireless & mobile network operations
  • Wireless sensor networks
  • Wireless & mobile network architectures
  • Wireless multimedia systems
  • Mobile internet and web applications

Ubiquitous 5G Technologies

  • Cognitive radio and cooperative systems
  • Standardization and regulation
  • Smart city and industry
  • Hardware architecture and implementation

Wireless Networking

  • Services and applications
  • Network architectures
  • Network protocols
  • Network modeling, analysis and operation
  • Network security a nd privacy
  • Wireless and wireless systems
  • Network operations & management

Sensor Networks or Systems

  • Learning of models from sensor networks
  • Synchronization and localization
  • Data storage and query processing

For useful illustration, we study many research articles and literature reviews to find the performance of any research network project topics . Research methodology and novelty are tested using the performance evaluation. Now, we provide specific information for defining network performance management . 

How network performance is measured?

  • Scalability: Network scale is measured for the large scale and small scale network devices and the largest network with sending huge volume of packets with diverse of nature proves the network has obtained the greater performance.
  • Throughput: For the network’s performance validation, throughput is evaluated and amount of data packets must be reached to the destination by the defined time periods can be the network has obtained the higher throughput
  • Packet loss: It represents the number of packets transmission from one end to the other end. However, packet losses degrade the network performance.

In above, we have shortened the network performance parameters , and also in the following, we describe all network performance metrics by OSI layer-wise as physical, MAC and routing layers , etc. However, evaluate performance metrics makes the network intelligent and realizes the network topology and link conditions. 

Further, it is achieved when appropriate protocol selection and management control have been taken. For instance, cognitive radio networks (CRN) and software-defined networks (SDN) require global network management. 

What are network performance metrics?

  • Network Architecture: network scale, network connectivity , centralized, or distributed, and network topology (cluster , star or mesh), and node density
  • Channel Modeling: channel quality, channel bandwidth, holding time, channel switching time and handoff channel sequence
  • Application and Traffic: QoE and QoS parameters
  • MAC layer: Backoff time, Link BER, Access Collision Rate, Access Type, Error Correction Rate, and robustness
  • Phy layer: SNR, Shannon capacity, Modulation mode and coding method
  • Node property: Mobility mode, Mobility Speed, Packet Processing Time, Max Hop Distance, and Transmission Power
  • Routing layer: Number of Hops, Path Delay, packet drop rate and re-routing time , and path throughput
  • Transport layer: Queue size, congestion level, sliding window size, reliability level, retransmission timeout setup, etc.

If you contact us for your network project topics , you can assume that it is finished because we start to guide you from the initial step to the final step. We value your time by giving our efforts and deep research knowledge to your research networking topics. Thus, you can prefer your network project topics with complete professional guidance with exceptional guidance from us. 

ScienceDaily

How do neural networks learn? A mathematical formula explains how they detect relevant patterns

Neural networks have been powering breakthroughs in artificial intelligence, including the large language models that are now being used in a wide range of applications, from finance, to human resources to healthcare. But these networks remain a black box whose inner workings engineers and scientists struggle to understand. Now, a team led by data and computer scientists at the University of California San Diego has given neural networks the equivalent of an X-ray to uncover how they actually learn.

The researchers found that a formula used in statistical analysis provides a streamlined mathematical description of how neural networks, such as GPT-2, a precursor to ChatGPT, learn relevant patterns in data, known as features. This formula also explains how neural networks use these relevant patterns to make predictions.

"We are trying to understand neural networks from first principles," said Daniel Beaglehole, a Ph.D. student in the UC San Diego Department of Computer Science and Engineering and co-first author of the study. "With our formula, one can simply interpret which features the network is using to make predictions."

The team presented their findings in the March 7 issue of the journal Science .

Why does this matter? AI-powered tools are now pervasive in everyday life. Banks use them to approve loans. Hospitals use them to analyze medical data, such as X-rays and MRIs. Companies use them to screen job applicants. But it's currently difficult to understand the mechanism neural networks use to make decisions and the biases in the training data that might impact this.

"If you don't understand how neural networks learn, it's very hard to establish whether neural networks produce reliable, accurate, and appropriate responses," said Mikhail Belkin, the paper's corresponding author and a professor at the UC San Diego Halicioglu Data Science Institute. "This is particularly significant given the rapid recent growth of machine learning and neural net technology."

The study is part of a larger effort in Belkin's research group to develop a mathematical theory that explains how neural networks work. "Technology has outpaced theory by a huge amount," he said. "We need to catch up."

The team also showed that the statistical formula they used to understand how neural networks learn, known as Average Gradient Outer Product (AGOP), could be applied to improve performance and efficiency in other types of machine learning architectures that do not include neural networks.

"If we understand the underlying mechanisms that drive neural networks, we should be able to build machine learning models that are simpler, more efficient and more interpretable," Belkin said. "We hope this will help democratize AI."

The machine learning systems that Belkin envisions would need less computational power, and therefore less power from the grid, to function. These systems also would be less complex and so easier to understand.

Illustrating the new findings with an example

(Artificial) neural networks are computational tools to learn relationships between data characteristics (i.e. identifying specific objects or faces in an image). One example of a task is determining whether in a new image a person is wearing glasses or not. Machine learning approaches this problem by providing the neural network many example (training) images labeled as images of "a person wearing glasses" or "a person not wearing glasses." The neural network learns the relationship between images and their labels, and extracts data patterns, or features, that it needs to focus on to make a determination. One of the reasons AI systems are considered a black box is because it is often difficult to describe mathematically what criteria the systems are actually using to make their predictions, including potential biases. The new work provides a simple mathematical explanation for how the systems are learning these features.

Features are relevant patterns in the data. In the example above, there are a wide range of features that the neural networks learns, and then uses, to determine if in fact a person in a photograph is wearing glasses or not. One feature it would need to pay attention to for this task is the upper part of the face. Other features could be the eye or the nose area where glasses often rest. The network selectively pays attention to the features that it learns are relevant and then discards the other parts of the image, such as the lower part of the face, the hair and so on.

Feature learning is the ability to recognize relevant patterns in data and then use those patterns to make predictions. In the glasses example, the network learns to pay attention to the upper part of the face. In the new Science paper, the researchers identified a statistical formula that describes how the neural networks are learning features.

Alternative neural network architectures: The researchers went on to show that inserting this formula into computing systems that do not rely on neural networks allowed these systems to learn faster and more efficiently.

"How do I ignore what's not necessary? Humans are good at this," said Belkin. "Machines are doing the same thing. Large Language Models, for example, are implementing this 'selective paying attention' and we haven't known how they do it. In our Science paper, we present a mechanism explaining at least some of how the neural nets are 'selectively paying attention.'"

Study funders included the National Science Foundation and the Simons Foundation for the Collaboration on the Theoretical Foundations of Deep Learning. Belkin is part of NSF-funded and UC San Diego-led The Institute for Learning-enabled Optimization at Scale, or TILOS.

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Story Source:

Materials provided by University of California - San Diego . Original written by Ioana Patringenaru and Daniel Kane. Note: Content may be edited for style and length.

Journal Reference :

  • Adityanarayanan Radhakrishnan, Daniel Beaglehole, Parthe Pandit, Mikhail Belkin. Mechanism for feature learning in neural networks and backpropagation-free machine learning models . Science , 2024; DOI: 10.1126/science.adi5639

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Johns Hopkins' Gregory D. Hager selected to head NSF Computer and Information Science and Engineering Directorate

The directorate supports research in all areas of computer and information science and engineering, as well as advanced research cyberinfrastructure necessary for discovery in all science and engineering fields.

By Jaimie Patterson

Gregory D. Hager , a professor in the Department of Computer Science at the Whiting School of Engineering at Johns Hopkins University and the founding director of the Malone Center for Engineering in Healthcare , has been selected by the National Science Foundation to head its Directorate for Computer and Information Science and Engineering (CISE) beginning Monday, June 3. With an annual budget of over $1 billion, the directorate advances research, innovation, and education in the computer science, information science, and computer engineering fields in the United States.

Image caption: Gregory Hager

Image credit : Will Kirk / Johns Hopkins University

Hager is known for his research on collaborative and vision-based robotics, time-series analysis of image data, and medical applications of image analysis and robotics. As a leader in the development of algorithms for real-time computer vision and their uses for robotics, his work offers novel applications for automated surgical training, medical imaging and diagnostics, and computer-enhanced interventional medicine.

"Dr. Hager brings his in-depth knowledge, experience, and accomplishments in the field of computing to the NSF during an important time for CISE and the agency," says Sethuraman Panchanathan , director of the NSF. "Leadership across the whole spectrum of computer science and engineering is essential to our nation's future competitiveness, economic growth and success. NSF and CISE investments are powering important progress, ranging from AI, networking, cybersecurity, advanced semiconductor manufacturing, data science, and supercomputing that will no doubt unleash new breakthroughs. Computing education is crucial to the success of the industries of today and the future. I am confident that Dr. Hager's expertise and experience will advance CISE to new heights and enable fantastic accomplishments."

In addition to his leadership activities within the Malone Center, Hager has served as chair of the Computing Community Consortium and on the board of the Computing Research Association, co-chaired the 2015 review of the Networking and Information Technology Research and Development Program for the President's Council of Advisors on Science and Technology, and is a member of the governing board of the International Federation of Robotics Research. His leadership and research contributions have also earned him recognition from the Institute of Electrical and Electronics Engineers, the Association of Computing Machinery, the American Institute for Medical and Biological Engineering, and the American Association for the Advancement of Science.

"I'm thrilled to have this opportunity to help shape the future of computing research," Hager says. "Achieving this milestone in my career is in large part due to my experiences at Hopkins—both the interdisciplinary research that's part of our DNA as well as the leadership opportunities that I've been given.

"The impact of CISE-supported research can be seen everywhere, from the most advanced AI systems to the digital communications infrastructure that underlies our everyday social interactions and secure systems that support millions of financial transactions every day," he says. "It is essential that we continue to support this incredible, vibrant history of innovation and impact."

Hager, who will remain on the Whiting School faculty while he works at the NSF on an Intergovernmental Personnel Act assignment, also holds joint appointments in the departments of Electrical and Computer Engineering and Mechanical Engineering.

Posted in Science+Technology

Tagged engineering , national science foundation , whiting school

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