A Proactive Flow Admission and Re-Routing Scheme for Load Balancing and Mitigation of Congestion Propagation in SDN Data Plane

TL;DR

This paper proposes a proactive SDN load balancing scheme that monitors network conditions, identifies bottlenecks, and reroutes flows using Bayesian modeling to prevent congestion propagation and improve network performance.

Contribution

It introduces a novel proactive flow admission and rerouting scheme using Bayesian networks to effectively balance load and mitigate congestion in SDN data planes.

Findings

Efficient rerouting reduces congestion propagation.

Improved network load balancing under high traffic.

Enhanced QoS parameters with the proposed scheme.

Abstract

The centralized architecture in software-defined network (SDN) provides a global view of the underlying network, paving the way for enormous research in the area of SDN traffic engineering (SDN TE). This research focuses on the load balancing aspects of SDN TE, given that the existing reactive methods for data-plane load balancing eventually result in packet loss and proactive schemes for data plane load balancing do not address congestion propagation. In the proposed work, the SDN controller periodically monitors flow level statistics and utilization on each link in the network and over-utilized links that cause network congestion and packet loss are identified as bottleneck links. For load balancing the identified largest flow and further traffic through these bottleneck links are rerouted through the lightly-loaded alternate path. The proposed scheme models a Bayesian Network using the observed port utilization and residual bandwidth to decide whether the newly computed alternate path can handle the new flow load before flow admission which in turn reduces congestion propagation. The simulation results show that when the network traffic increases the proposed method efficiently re-routes the flows and balance the network load which substantially improves the network efficiency and the quality of service (QoS) parameters.