Optimizing Connected Target Coverage in Wireless Sensor Networks Using Self-Adaptive Differential Evolution

Authors : Osman GÖKALP

Pages : 325-330

Doi:10.17694/bajece.624527

View : 24 | Download : 11

Publication Date : 2020-10-30

Article Type : Research Paper

Abstract :Wireless Sensor Networks insert ignore into journalissuearticles values(WSNs); are advanced communication technologies with many real-world applications such as monitoring of personal health, military surveillance, and forest wildfire; and tracking of moving objects. Coverage optimization and network connectivity are the critical design issues for many WSNs. In this study, the connected target coverage optimization in WSNs is addressed and it is solved using self-adaptive differential evolution algorithm insert ignore into journalissuearticles values(SADE); for the first time in literature. A simulation environment is set up to measure the performance of SADE for solving this problem. Based on the experimental settings employed, the numerical results show that SADE is highly successful for dealing with connected target coverage problem and can produce higher performance in comparison with other widely-used metaheuristic algorithms such as classical DE, ABC, and PSO.
Keywords : Connected Target Coverage, Metaheuristics, Optimization, Self Adaptive, Wireless Sensor Networks