SDN routing strategy based on genetic algorithm and particle swarm optimization under SFC background
Haiyan Hu, Qiaoyan Kang, Jianfeng Wang, Shuo Zhao, Yifan Yuan, Youbin Fu · 2023
To solve the problem of low routing efficiency and limited link utilization when Service Function Chain (SFC) deployment adopts the traditional shortest path algorithm in the face of large-scale network topology due to the expansion of the path search scope and only considering the shortest path each time, this paper proposes a routing strategy based on meta-heuristic algorithm to achieve the optimization of SFC routing. Firstly, the inertia weights in the original PSO algorithm are dynamically processed to adapt to the dynamic characteristics of Software Defined Networking (SDN) network topology and improve the optimization ability and convergence speed of the original algorithm. Secondly, the crossover and mutation of genetic algorithm are introduced to improve the ability of the algorithm to find the optimal path. Simulation results show that compared with the traditional k-shortest path algorithm, the proposed method can effectively improve link utilization during routing, reduce the routing time of large-scale network topology, and improve the SFC routing efficiency.