A novel controller placement algorithm based on network portioning concept and a hybrid discrete optimization algorithm for multi-controller software-defined networks

Abstract

Software defined network (SDN) has shown significant advantages in numerous real-life aspects with separating the control plane from the data plane that provides programmable management for networks. However, with the increase in the network size, a single controller of SDN imposes considerable limitations on various features. Therefore, in networks with immense scalability, multiple controllers are essential. Specifying the optimal number of controllers and their deployment place is known as the controller placement problem (CPP), which affects the network's performance. In the present paper, a novel controller placement algorithm has been introduced using the advantages of nature-inspired optimization algorithms and network portioning. Firstly, the Manta Ray Foraging Optimization (MRFO) and Salp Swarm Algorithm (SSA) have been discretized to solve CPP. Three new operators comprising a two-point swap, random insert, and half points crossover operators were introduced to discretized the algorithms. Afterward, the resulting discrete MRFO and SSA algorithms were hybridized in a promoting manner. Next, the proposed discrete algorithm has been evaluated on six well-known software-defined networks with a different number of controllers. In addition, the networks have been chosen from various sizes to evaluate the scalability of the proposed algorithm. The proposed algorithm has been compared with several other state-of-the-art algorithms regarding network propagation delay and convergence rate in experiments. The findings indicated the effectiveness of the contributions and the superiority of the proposed algorithm over the competitor algorithms.