Self-Improved Jellyfish Optimization for Extending Coverage in WSN

Abstract

Recently, the vast advantages in networking technology paves its way in various arena. In WSN, the network consists of spatially distributed sensor nodes with base stations. In real-time, the sensors in WSN monitors physical and environmental conditions including temperature, pressure, etc. The sensor nodes in the network are functioned as router and originator. In WSNs nodal coverage problem is one of the major problem. This issue limited the sensing coverage of nodes while monitoring or tracking specific conditions. That’s why this work is intended to solve this issue using coverage optimization. This work is supposed to propose a novel efficient node coverage model for WSN using 2D distance evaluation in accordance with weighted Minkowski distance. Consequently, the optimal positioning of sensor nodes is determined by proposed SIJSO algorithm. Here, the proposed SIJSO algorithm for optimal positioning of sensor nodes is an implemented version of traditional JSO algorithm. The traditional JSO algorithm is a nature-based metaheuristic algorithm which mimics the behavioral aspects of jellyfish. In the conclusion, this proposed work proved its efficiency through various analysis.