[This article belongs to Volume - 56, Issue - 01, 2024]
Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-15-03-2024-12

E. Akila and V.Baby Deepa

Abstract :

Clustering is an extremely efficient technique for saving energy in the Wireless Sensor Networks (WSNs). WSN 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. The selection of the CH will be a non-deterministic Polynomial (NP)-hard problem. The work has proposed one more energy efficient CH algorithm of selection that has been based on the CRO and the GA algorithms. This type of a CRO algorithm has been developed using some efficient schemes of the encoding of molecular structure that is for the energy efficiency considering several parameters like the intra-cluster based distance, the residual energy and sink distance. In case of the formation of the cluster and its phase several distance and energy parameters have been considered. This algorithm has been extensively tested based on different scenarios of that of the WSNs by means of varying the other sensor nodes and the CHs. These results have been compared with certain currently existing algorithms for being able to demonstrate the proposed algorithm and its superiority.