World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
67
Citations
22210
World Ranking
2165
National Ranking
1088

Electronics and Electrical Engineering

D-Index
61
Citations
20830
World Ranking
1497
National Ranking
615

Overview

T. V. Lakshman is affiliated with Nokia in the United States. Their research output primarily lies within the field of Computer Science, with a strong focus on Computer Networks and Communications. Additional subfields of study include Artificial Intelligence, Electrical and Electronic Engineering, Information Systems, and Computational Mechanics.

The scientist's work spans multiple interconnected topics, notably:

  • Network Traffic and Congestion Control
  • Software-Defined Networks and 5G
  • IoT and Edge/Fog Computing
  • Cloud Computing and Resource Management
  • Sparse and Compressive Sensing Techniques
  • Internet Traffic Analysis and Secure E-voting
  • Image and Video Quality Assessment

T. V. Lakshman has published research in various venues, reflecting a presence in both conference and journal outlets. Frequent publication venues include:

  • arXiv (Cornell University)
  • IEEE Transactions on Network and Service Management
  • IEEE Open Journal of the Communications Society
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • IEEE INFOCOM 2022 - IEEE Conference on Computer Communications

Recent papers authored or co-authored by Lakshman include:

  • Deep Neural Network Approximated Dynamic Programming for Combinatorial Optimization, 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • Resource Allocation in Data Centers Using Fast Reinforcement Learning Algorithms, 2021, IEEE Transactions on Network and Service Management
  • Learning Based Methods for Traffic Matrix Estimation From Link Measurements, 2021, IEEE Open Journal of the Communications Society
  • MAGNet: Machine Learning Guided Application-Aware Networking for Data Centers, 2021, IEEE Transactions on Cloud Computing
  • Network Link Weight Setting: A Machine Learning Based Approach, 2022, IEEE INFOCOM 2022 - IEEE Conference on Computer Communications

Frequent collaborators in Lakshman's research include Murali Kodialam, Shenghe Xu, Shivendra S. Panwar, Sarit Mukherjee, and Leandros Tassiulas.

Best Publications

  • The performance of TCP/IP for networks with high bandwidth-delay products and random loss

    T. V. Lakshman;Upamanyu Madhow

  • Statistical analysis and simulation study of video teleconference traffic in ATM networks

    D.P. Heyman;A. Tabatabai;T.V. Lakshman

  • SRED: stabilized RED

    T.J. Ott;T.V. Lakshman;L.H. Wong

  • High-speed policy-based packet forwarding using efficient multi-dimensional range matching

    T. V. Lakshman;D. Stiliadis

  • Fast and memory-efficient regular expression matching for deep packet inspection

    Fang Yu;Zhifeng Chen;Yanlei Diao;T. V. Lakshman

  • Minimum interference routing with applications to MPLS traffic engineering

    M. Kodialam;T.V. Lakshman

  • Traffic engineering in software defined networks

    Sugam Agarwal;Murali Kodialam;T. V. Lakshman

  • Towards an elastic distributed SDN controller

    Advait Dixit;Fang Hao;Sarit Mukherjee;T.V. Lakshman

  • Gigabit rate packet pattern-matching using TCAM

    Fang Yu;R.H. Katz;T.V. Lakshman

  • Packet routing device, packet routing method and packet router

    Petri Aukia;Goparaswamy Kajamalai;Tirunell V Lakshman;Debasis Mitra

  • Dynamic routing of bandwidth guaranteed tunnels with restoration

    M. Kodialam;T.V. Lakshman

  • Network aware resource allocation in distributed clouds

    Mansoor Alicherry;T.V. Lakshman

  • Minimum interference routing of bandwidth guaranteed tunnels with MPLS traffic engineering applications

    K. Kar;M. Kodialam;T.V. Lakshman

  • What are the implications of long-range dependence for VBR-video traffic engineering?

    Daniel P. Heyman;T. V. Lakshman

  • Providing cloud-based services using dynamic network virtualization

    Fang Hao;Tirunellai V. Lakshman;Sarit Mukherjee;Haoyu Song

  • Source models for VBR broadcast-video traffic

    Daniel P. Heyman;T. V. Lakshman

  • VBR video: tradeoffs and potentials

    T.V. Lakshman;A. Ortega;A.R. Reibman

  • Beyond best effort: router architectures for the differentiated services of tomorrow's Internet

    V.P. Kumar;T.V. Lakshman;D. Stiliadis

  • Fundamental bounds and approximations for ATM multiplexers with applications to video teleconferencing

    A. Elwalid;D. Heyman;T.V. Lakshman;D. Mitra

  • Enhancing dynamic cloud-based services using network virtualization

    Fang Hao;T. V. Lakshman;Sarit Mukherjee;Haoyu Song

Frequent Co-Authors

Murali Kodialam
Murali Kodialam Nokia (United States)
Sudipta Sengupta
Sudipta Sengupta Amazon (United States)
Randy H. Katz
Randy H. Katz University of California, Berkeley
Shivendra S. Panwar
Shivendra S. Panwar New York University
Dipak Ghosal
Dipak Ghosal University of California, Davis
Upamanyu Madhow
Upamanyu Madhow University of California, Santa Barbara
Nick Duffield
Nick Duffield Texas A&M University
Debasis Mitra
Debasis Mitra Columbia University

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