A Dynamic Traffic Engineering Strategy Using Latency-AwareCongestion Control in Software-Defined ‎Networks

  • Authors

    • S. D. Vijayakumar Department of AI & DS Nandha Engineering College, ‎Erode, India
    • R. Praveenkumar Department of ECE Nandha Engineering College, ‎Erode, India
    • M. Prakash Department of ECE Kangeyam Institute of ‎Technology, Tirupur, India
    • T. Rajkumar Department of ECE Nandha College of ‎Technology, Erode, India
    • P. A. Selvaraj Department of Computer ‎Science and Design Kongu Engineering College, ‎Erode, India
    • P. Karunakaran Department of AI & DS Nandha Engineering College, ‎Erode, India
    https://doi.org/10.14419/peb76802

    Received date: July 8, 2025

    Accepted date: September 13, 2025

    Published date: October 5, 2025

  • Software-Defined Networking (SDN); ‎Retransmission Timeout (RTO); Traffic ‎Engineering; Network Performance Optimization

  • Abstract

    This work focuses a wide range of modules centered ‎on latency-aware optimization strategies in order to ‎meet the increasing need for low-latency ‎communication in contemporary networks. The ‎system incorporates sophisticated congestion ‎control algorithms including LEDBAT, TCP Vegas, ‎and BBR, which regulate transmission rates more ‎efficiently than conventional loss-based techniques ‎by using delay-based metrics like round-trip time ‎‎(RTT) and queuing delay. To guarantee effective ‎path selection under latency limitations, traffic ‎engineers use multipath routing strategies as ECMP ‎and MPTCP, modified Dijkstra's algorithm with ‎latency weights, and constraint-based shortest path ‎first (CSPF). Utilizing the programmability of ‎Software-Defined Networking (SDN), the system ‎integrates metaheuristic methods including genetic ‎algorithms, ant colony optimization, and particle ‎swarm optimization along with intelligent routing ‎strategies utilizing reinforcement learning. By using ‎real-time latency feedback, these techniques allow ‎for dynamic and adaptive routing decisions. ‎OpenFlow and P4 flow rerouting features improve ‎the system's responsiveness to network conditions ‎even more. Mechanisms for monitoring and ‎feedback are essential for facilitating accurate ‎decision-making. The SDN controller's RTT ‎measurement modules continuously measure ‎connection latency, and exponential weighted ‎moving average (EWMA) methods smooth the ‎data gathered to prevent overreactions to brief ‎variations. These components work together to ‎create a strong framework for next-generation ‎network environments that optimize latency‎.

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  • How to Cite

    Vijayakumar , S. D. ., Praveenkumar, R. . ., Prakash , M. ., Rajkumar, T. . ., Selvaraj, P. A. . ., & Karunakaran , P. . (2025). A Dynamic Traffic Engineering Strategy Using Latency-AwareCongestion Control in Software-Defined ‎Networks. International Journal of Basic and Applied Sciences, 14(6), 80-87. https://doi.org/10.14419/peb76802