Optimized Routing Protocol Using Metaheuristic Techniques for Improving Energy Efficiency in WSN

Abstract

Abstract A Wireless Sensor Network is a group of small, autonomous sensor nodes which are connected wirelessly and have sensing, processing, and communication capabilities. These nodes are responsible for gathering and monitoring physical information from the surrounding environment. Since these nodes are typically compact and operate with a battery, they have a limited power supply which leads to a constrained network lifetime. Therefore, the use of energy effective techniques that lengthen the network’s lifespan is highly significant. Hence, the objective of this research work is to reduce energy usage and increase the network’s lifespan. Clustering and optimization techniques are commonly used in sensor network to enhance its stability and lifespan. In a clustered sensor network, cluster heads play a crucial role, as they are responsible for performing various tasks that consume more energy. This research work aims to enhance the effectiveness of the network by proposing a hybrid nature-inspired optimization algorithm named as Energy Efficient Yellow Saddle Goatfish Pelican Optimization algorithm (EEYSGPO) which uses Yellow Saddle Goatfish Algorithm to identify the optimum cluster head from a set of nodes. The parameters like residual energy, distance, delay, load, and communication quality are all used to select the optimized cluster head in the clusters. After choosing the optimized cluster head, pelican optimization technique is used to determine the best route for communication between cluster head and the base station, which is calculated on the basis of distance and residual energy. The MATLAB simulator is used for simulation and the obtained results of suggested technique were compared with several existing energy-efficient techniques such as EECHIGWO, SSMOECHS, FGWSTERP and LEACH-PRO using performance measures such as throughput, dead nodes and energy consumption. Simulation findings reveal that the optimal selection of cluster heads and routes in EEYSPO algorithm resolved the issues related to premature convergence and increase the lifetime and scalability of WSN. When compared to the EECHIGWO, SSMOECHS, LEACH-PRO and FGWSTERP protocols, the proposed methodology improves network stability by 57.28 %, 324.5 %, 571.72 % and 91.37 % respectively.