Emperor Penguin Optimized Clustering for Improved Multilevel Hierarchical Routing in Wireless Sensor Networks

Abstract

AbstractIn recent years, wireless sensor network (WSN) is a very effective in adaptive application for research community. The WSN nodes have limited amount of energy that needs that the energy should be used in an efficient way. The energy depletion factor should be reduced by combining the nodes for data collection and routing. This paper proposed an energy-efficient-based emperor penguin optimized (EPO) clustering for improved multilevel hierarchical routing (IMHR) in wireless sensor networks. The whole network region is divided by EPO algorithm into number of clusters and regions where every cluster has one cluster head (CH). According to energy condition, the WSN nodes are combined which perform routing in hierarchical level. The sensor nodes (SN) exchange different information such as distance and energy to perform clustering and routing process. The communicated messages are conveyed by IMHR for cluster association. In our work, multilevel hierarchical routing (MHR) is improved by optimizing MHR with social ski-driver (SSD) algorithm. MATLAB platform is used to implement the work and take the graphical analysis by means of throughput, delay, PDR, etc., by comparing with exiting techniques. The performance of proposed throughput is 99.3%, packet delivery ratio is 97%, and the delay is 6.1 s.KeywordsMultilevel hierarchical routingEnergy-efficient clusteringCluster headEmperor penguin optimizationSocial ski-driver