Virtual Force and Glowworm Swarm Optimization Based Node Deployment Strategy for WSNs

Abstract

Wireless Sensor Networks (WSNs) can be viewed as a network with hundreds or thousands of randomly deployed sensors, whose coverage control problem has the characteristics of self-organized groups. This paper studies the coverage optimization strategy based on swarm intelligence for wireless sensor networks. In WSNs, the random deployment of nodes causes the coverage of the blind area and the redundancy of the coverage. We propose a new algorithm based on virtual force and glowworm swarm optimization algorithm. Firstly, the utilization rate of the nodes and the effective coverage of the network are the optimization objectives and the corresponding mathematical model is established. Then, the virtual force algorithm and the glowworm swarm optimization algorithm are used to solve the problem of modeling, and the optimal coverage scheme for WSNs is obtained. Simulation results show that the virtual force and glowworm swarm optimization algorithm can effectively improve the coverage of WSNs nodes, reduce the redundancy of sensor nodes, and reduce the cost of network effectively. Besides, the network survival time can get prolonged.