A novel approach based on gray wolf evolutionary algorithm for controller load balancing in software defined networks using dynamic switch migration

Software Defined Network (SDN) has become a popular model for centralized control and management in many modern network scenarios. However, for large data centers with hundreds of thousands of servers and several thousand switches, a single controller mode causes the system to suffer from lack of scalability and reliability. The use of distributed architecture can improve system performance, but the main limitation of this work is the static mapping between the switch and the controller, which may lead to load imbalances in the controllers. The use of multiple controllers distributed in SDN has been used to improve scalability and reliability, where each controller manages a fixed partition of the network. In the proposed method, a balanced controller (BalCon) is used as a scheme to dynamic migrate the SDN switch to achieve load balance between SDN controllers with low migration cost. The decision to migrate is made by the monitor based on network traffic. To balance load in the software-based network, a staged switch migration strategy is used and the target controller is selected by the gray wolf algorithm. The results show that the response time of the proposed method is 13% better than the BalCon method. Also, by increasing the sending rate to 8.33%, the controller's throughput improves compared to the BalCon method. Therefore, the load balance of the proposed method has a better performance than previous works.