An Efficient Clustering and Routing Algorithm for Wireless Sensor Networks Using GSO and KGMO Techniques

Abstract

Wireless sensor networks (WSNs) play a key role in data transmission based on the locations of sensor nodes (SNs). WSN contains base station (BS) with several SNs, and these SNs are randomly spread across the entire region of monitoring. The BS aggregates the data received from several SNs for meaningful analysis-deployed environment. Energy conservation is the major challenge in the WSN. Since SNs are battery-operated over a period of time, SNs drain their energy in sensing the region of interest and passing on the same to the BS. The consumption of energy depends on the distance between SNs and BS. The SNs are clustered with a certain criteria, and by choosing the cluster head (CH) to aggregate the gathered information by SNs along with determining the optimized path from CH to BS by efficient routing protocol are the innovative techniques in enhancing the lifetime of WSN by optimizing the energy consumption. In this work, an efficient clustering and routing algorithm for WSN using glowworm swarm optimization (GSO) and kinetic gas molecule optimization (KGMO) techniques are proposed. The GSO-KGMO-WSN technique is applied to enhance the lifetime of WSN by effectively reducing the unnecessary data transmission between SNs and BS. This in turn reduces the dead SNs over the period of time which results in enhancing the lifetime of WSN.