ISFO-CS: An Improved Sailfish Optimization Algorithm for Controller Selection in SDWSN

Abstract

Software-defined wireless sensor networks (SDWSNs) have recently been added to networking, increasing scalability and performance. Choosing SDN controllers is a critical issue for network administrators in SDNs. The control plane in SDN is a separate procedure that operates on the control layer. In terms of applications and services, the controller provides a comprehensive view of the entire network. The three key factors examined when selecting a controller are open source, campus network, and productivity. An appropriate device for the prompt processing of all switch requests is required for SDN to function properly and the network to behave properly. To determine the optimum controller for the given parameters, decision logic that allows controller comparison must be developed. As a result, an improved Sailfish Optimization (ISFO) method is proposed in this study to ideally take the best controller node (CN) from a group of sensor nodes. The ISFO selects the best CN by considering a multi-objective fitness function incorporating distance, residual energy, node coverage, and sensor node communication cost. After selecting CN, the Fuzzy C-means (FCM) Clustering algorithm executes the subsequent data transmission process. The Matlab program is used to execute the simulation, and the performance of the proposed methodology is assessed using several performance criteria. The proposed model accomplishes a 0.95% packet delivery ratio for 500 rounds and takes 1.8s for 500 rounds of node to controller latency.