K-covered wireless sensor network optimization

Abstract

In this paper, a k-covered wireless sensor network optimization problem is considered to improve the quality of surveillance. In order to maximize the coverage area of wireless sensor network with k-covered hotspots and connected sensor nodes, a novel stochastic optimization technique named particle filter optimization (PFO) is proposed to obtain an optimal sensor placement. Simulation results indicate that the proposed algorithm is effective and efficient. Finally, it is demonstrated that the proposed algorithm exhibits a significant performance improvement over other benchmark methods, for example, genetic algorithm (GA) and particle swarm optimization (PSO) method.