基于改进遗传算法的SDN多控制器负载均衡机制研究

Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2022-05-10 Cooperative journals: 《计算机应用研究》

徐爱鑫 孙士民 汪晓凡 徐国威 王美玉

Abstract： This paper proposed the Non-cooperative Game Theory-based of load-reduction Master Controller Reselection model in Software Defined Networking to address the multi-controller load imbalance problem, called GTMCR. To begin with, the discriminating overload controller utilized the Overload Dynamic Thresholds approach (ODT) . Next, the migration of switches followed a Priority Decision Switching Strategy (PDSS) . Finally, the constructed optimization model took the load balancing degree of controller clusters, average total delay and switch migration cost as utility functions. To prevent the global optimal solution from slipping into the local optimum, the solution value of optimal deployment used the Genetic Algorithm for Improved Multi-objective Optimization (GAIMO) with the addition of a similarity operator to boost the algorithm's convergence speed and the accuracy of the global optimal solution. The experimental results show that this mechanism effectively balances the control plane load while achieving the goal of optimizing network performance.

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