Parameter Optimization Model of Heuristic Algorithms for Controller Placement Problem in Large-Scale SDN

Abstract

The Controller Placement Problem (CPP) is a key technical challenge in a large-scale Software Defined Network (SDN). Low-complexity heuristic algorithm is widely used for solving the CPP. However, parameter settings of the heuristic algorithm greatly affect the result of the CPP. Therefore, we establish a Parameter Optimization Model (POM) for the heuristic algorithm applied to the CPP. The heuristic algorithm can effectively solve the CPP by using the optimized parameters obtained in POM. To verify the effectiveness of the POM, we first establish a synthetical-delay controller placement model to reduce the delay between the controllers and the switches and the delay between the controllers. Further, we select the bat algorithm, the firefly algorithm, and the varna-based optimization respectively to solve the model, and use the particle swarm optimization method to optimize the parameters of the three algorithms. Experimental results on real topologies show that compared with original algorithms and other similar algorithms, the algorithms with optimized parameters perform better.

Keywords

• Controller placement problem
• delay
• heuristic algorithm
• parameter optimization
• particle swarm optimization
• software defined network