无线传感网络布局的虚拟力导向微粒群优化策略

Dynamic Sensor Deployment Strategy Based on Virtual Force-Directed Particle Swarm Optimization in Wireless Sensor Networks

无线传感网络通常由固定传感节点和少量移动传感节点构成,动态无线传感网络布局优化有利于提高无线传感网络覆盖率和目标检测概率,是无线传感网络研究的关键问题之一.传统的虚拟力算法在优化过程中容易受固定传感节点的影响,无法实现全局优化.本文结合虚拟力算法和微粒群算法,提出一种面向无线传感网络布局的虚拟力导向微粒群优化策略.该策略通过无线传感节点间的虚拟力影响微粒群算法的速度更新过程,指导微粒进化,加快算法收敛.实验表明,虚拟力导向微粒群优化策略能快速有效地实现无线传感节点布局优化.与微粒群算法和虚拟力算法相比,虚拟力导向微粒群优化策略不仅网络覆盖率高,且收敛速度快,耗时少.

Wireless sensor networks（WSNs）always consist of many mobile and stationary sensor nodes.Dynamic sensor deployment is one of the key topics addressed in the research of WSNs,which is adopted to improve the coverage and detection probability of WSNs.The performance of virtual force（VF）algorithm may be deteriorated because the stationary sensor nodes will confine the global optimal searching ability.This paper proposes a dynamic sensor deployment strategy for WSNs,so-called virtual force-directed panicle swarm optimization（VFPSO）.VFPSO combines the VF with particle swarm optimization（PSO）,where the velocity of each particle is updated according to not only the historical local optimal solutions and global optimal solutions but also the virtual forces of sensor nodes.The key motivation of this strategy is to use the virtual force to direct the updating of PSO for improving the convergence speed,and PSO is used to enhance the global searching ability.Simulation results demonstrate that VFPSO has better performance on regional convergence and global searching than VF algorithm and PSO algorithm,and it can implement dynamic sensor deployment efficiently and rapidly.