Ant Colony Algorithm Optimization for Software Defined Network Load Balancing

To solve the problems of low efficiency and poor flexibility caused by the traditional load balancing methods which can not obtain the statistical data of network devices effectively or the load balancing influence factors, this paper proposes a joint path server ant colony optimization algorithm considering path level and server level jointly. The server balance module collects the performance index of the server, grasps the status of the server in time, and calculates the weight of the server by using the dynamic algorithm based on the server performance. In the process of rerouting, this paper adopts an optimized ACO algorithm, which changes the search rules of the ordinary algorithm. The path searched by ants is filtered by the dynamic load balance value to determine the optimal path. The simulation results show that compared with the traditional load balancing control algorithm, the proposed scheme has better quality of service. It can achieve greater throughput and lower packet loss rate, which also shows excellent management and utilization of network resources.