Genetic Algorithm versus Discrete Particle Swarm Optimization Algorithm for Energy-Efficient Moving Object Coverage Using Mobile Sensors

This paper addresses the challenge of moving objects in a mobile wireless sensor network, considering deployment limited number nodes within predetermined area to provide coverage for traveling on trajectory. Because insufficient and sensing range sensors, entire object’s trajectory cannot be covered by all deployed sensors. To address this problem complete coverage, sensors must move from one point another. The frequent movement quickly depletes sensors’ batteries. Therefore, solving object requires an optimized repertoire where (1) total distance is minimized (2) remaining energy also as balanced possible sensing. Herein, we used genetic algorithm (GA) discrete particle swarm optimization (DPSO) manage complexity problem, compute feasible quasi-optimal trajectories determine demand among nodes. Simulations revealed that GA produced significantly superior those DPSO terms traveled balance residual energy.