A Dynamic Traffic Engineering Strategy Using Latency-Aware Congestion Control in Software-Defined Networks
S. D. Vijayakumar, R. Praveenkumar, M. Prakash, T. Rajkumar, P. A. Selvaraj, P. Karunakaran · International Journal of Basic and Applied Sciences · 2025
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.