Scalability comparison of SDN control plane architectures based on simulations

Abstract

Software Defined Networking (SDN) is an emerging networking paradigm which separates the control plane from the data forwarding plane. To control large networks, designing a scalable control plane for SDN is one of the most significant challenges. In this paper, we focus on comparing the scalability performance of SDN control planes with different architectures. We first compare simulation and emulation approach in scalability evaluation for SDN, and conclude that simulation is the most appropriate approach for our study. To apply simulation approach, we identify two critical processes (flow setup and statistics collection) which restrict the scalability of the control plane. Based on these two processes, we abstract switches and controllers in the five existing SDN control plane architectures (i.e., centralized, P2P with local view, P2P with global view, hierarchical, and hybrid). These abstractions allow us to build simulations based on ns-3 network simulator for SDN networks with different control plane architectures. Our experiments show that the hierarchical control plane achieves the best scalability performance, while the centralized and P2P with global view control planes get the worst performance. Furthermore, our simulations demonstrate the significance of statistics collection speed in scaling the SDN network. We believe this study can give implications about control plane architecture selection for operators (developers) who want to deploy (develop) their own SDN networks (controllers).