OCHSMO: Selection Optimal of Cluster Head Based Spider Monkey Optimization

Abstract

the cluster heads (CHs) are distributed randomly in the Low Energy Adaptive Clustering Hierarchy (LEACH) protocol. Some sensor nodes may be placed further away from the CHs and thus are not covered. This causes excessive route energy consumption of the isolated nodes. Because of randomly selecting the CHs, some nodes can die quickly due to extra workload. By used Spider Monkey Optimization (SMO), we can elect the CHs and design cluster-based routing algorithms. The SMO looks for the social behaviors of spider monkeys to choose the optimal route. The social behaviors are an example of the fission-fusion system. In this paper, we proposed the Selection Optimal of Cluster Head Based Spider Monkey Optimization (OCHSMO) algorithm. The proposed algorithm has used the mechanism of the SMO to solve the problems of cluster routing in the WSNs. It improves the LEACH protocol in terms of energy consumption, system lifetime, stability period, and system quality of the network. Experimental results show that the OCHSMO algorithm is better than the LEACH algorithm in all performance measures. We used the MATLAB to evaluate the performance.