An Comparison of Different Cluster Head Selection Techniques for Wireless Sensor Network

Abstract

Wireless Sensor Network is based on the hierarchical cluster and hence the Cluster Heads (CHs) will consume some more energy owing to the additional overload for the receiving and the aggregating of data from that of their member sensor nodes and this transmits all the aggregated data to its Base Station (BS). So the proper selection of the CH has a vital role to play in conserving the energy of the sensor nodes for the purpose of prolonging the WSNs and their lifetime. Here in this work, a proposed Low Energy Adaptive Clustering Hierarchy (LEACH), the Genetic Algorithm (GA) and finally the Chemical Reaction Optimization (CRO) algorithm is considered. The LEACH is a popular clustering algorithm wherein the sensor nodes will elect themselves to be the CH having a certain probability. But the main disadvantage of this algorithm will be that it may choose a CH having low energy that will be able to die quickly and thereby degrades the network performance. So there is a large number of algorithms that are developed for improving the LEACH. These results have been compared with certain currently existing algorithms for being able to demonstrate the proposed algorithm and its superiority.