Routing optimization strategy for power SDN communication network based on NSGA-II

Aiming at the problems of uneven link load distribution and energy waste in power communication networks, this paper proposes a multi-objective genetic algorithm-based routing optimization strategy for power communication networks considering software-defined networks. The standard deviation of the remaining bandwidth of the whole network and the number of newly activated links, as quantitative indicators, are used to realize the dynamic allocation of power communication network resources. Simulation results show that the NSGA-II multi-objective genetic algorithm selected in this paper has better optimization effect than the shortest path Dijkstra algorithm, and this strategy can meet the increasing demand of service carrying capacity and make the link load distribution more uniform.