3-D Terrains Deployment of Wireless Sensors Network by Utilizing Parallel Gases Brownian Motion Optimization

Abstract

With the development of Wireless Sensor Network (WSN), more and more researchers pay their attention to the deployment of sensor nodes, especially for the coverage of WSN in three dimension space. However, getting the maximum for coverage rate in WSN quickly and accurately is still a front issue. Firstly, this paper proposes a modified GBMO algorithm combining with the concept of parallel, so that the time efficiency and convergency improve to a large extend, and the search for global optimum is capable of getting faster. Then, the improvement in search and convergency efficiency of proposed PGBMO is demonstrated according to 23 benchmark functions composed of unimodal, multimodal and fixed-dimension function. Finally, a novel WSN 3-D terrain deployment scheme optimized by PGBMO is proposed to improve the coverage of the network. Experimental results demonstrate that the performance on the coverage of WSN gets efficient improvement compared to traditional particle swarm optimization (PSO) and original GBMO.