Hybridization of Energy Optimization Technique for Cluster Based Routing using Various Computational Intelligence Methods in WSN

Approaches in WSN technology has determined by opportunity of tiny and inexpensive sensor nodes with adequacy sensing multiple kinds information processing wireless communication. Network lifetime energy efficiency are major indexes WSN. Several clustering techniques intended to extend the network but whereas there is an issue incompetent Cluster Head (CH) election. To overcome this issue, Integration Novel Memetic Brain Storm Optimization approach Levy Distribution (IoNM-BSOLyD) been proposed for using fitness function. In meanwhile, election CH done utilizing function, which incorporates following amplitude such as energy, distance adjacent nodes, BS, load. After clustering, routing decides detecting pursuing route work, a Water Wave Hill Climbing technique (WWO-HCg) introduced purpose. This methodology deals ternary QoS aspect delay, consumption, packet delivery ratio, security select optimal path enhance well. protocol provides better performance result than other contemporary protocols.