Hierarchical Deployment Optimization for Wireless Sensor Networks

Abstract

Sensor nodes deployment is very crucial for wireless sensor networks (WSNs). Current methods are apt to enlarge the coverage by achieving a nearly even deployment with similar density in the whole network. However, in some specific applications, the even distribution may not satisfy the sensing requirements. This paper proposes a virtual force directed coevolutionary particle swarm optimization (VFCPSO) algorithm, which uses a combined objective function to achieve the tradeoff of coverage and energy consumption. By considering deployment as an optimization problem, VFCPSO is more reliable and flexible for WSNs, since it can satisfy the combined requirements instead of only enlarging coverage. For investigating the performance of different paradigms, centralized VFCPSO is extended to distributed VFCPSO, heterogeneous hierarchical VFCPSO and homogeneous hierarchical VFCPSO (Homo-H-VFCPSO), and the solution of preferential deployment in interested region is also analyzed. Simulation results show that the Homo-H-VFCPSO has the best performance, i.e., it is more efficient than other three VFCPSO algorithms and the VF-style algorithms in terms of computation time, coverage and efficient moving energy consumption. It is obvious that the Homo-H-VFCPSO has good global searching ability and scalability, and it can rapidly and effectively achieve the sensor nodes deployment in WSNs.