An adaptive particle swarm optimization for the coverage of wireless sensor network

Abstract

The coverage problem is a crucial issue in wireless sensor networks (WSN); however, a high coverage rate ensures a high quality of service in WSN. This paper presents control of the coverage problem optimization via the adaptive particle swarm optimization (APSO) approach. The proper selection of inertia weight of APSO gives balance between global and local searching, and the research of this paper shows that the larger weight helps to increase convergence speed while the smaller one benefits convergence accuracy, decreasing the algorithm operation times. Finally, the current paper presents examples to illustrate the effectiveness of the proposed APSO methodology. The simulation results show that the APSO algorithm achieves a good coverage solution with enhanced time efficiency. © 2011 Springer-Verlag Berlin Heidelberg.