SDN-Based Load Balancing Scheme for Multi-Controller Deployment

Abstract

Software-defined networking (SDN) separates the control plane from the data forwarding plane and realizes the flexible management of the network resources. With the explosive growth of network traffic and scale, multi-controllers need to be deployed to improve the scalability and reliability of the control plane. However, unreasonable subdomain partitioning of SDN controllers may cause the unbalanced distribution of controller loads and reduces the communication performance of the network. Therefore, in this paper, a dynamic multi-controller deployment scheme based on load balancing is proposed. We transform the flow requests into a queuing model and consider the traffic propagation delay and the capacity of controllers as two main factors affecting the deployment of the multi-controllers. In the initial static network, a modified affinity propagation algorithm (PSOAP) based on particle swarm optimization is proposed to solve the problem of clustering performance being affected by the initial values of the bias parameters and convergence coefficients, getting the reasonable network planning. With the dynamic traffic network, switches in different sub-domains are reassigned by breadth-first search (BFS) algorithm to achieve controller load balancing. The extensive evaluations demonstrate that the scheme can provide better stable, accurate, and load balancing multi-controller deployment when compared with affinity propagation (AP) and genetic algorithms.