大规模无线传感器网络覆盖优化算法

Coverage optimization algorithm of large-scale WSNs

为了增强三峡库区水环境监测的大规模无线传感器网络(WSNs)覆盖效果和延长大规模WSNs生存时间,采用混沌人工鱼群算法。首先以最大化网络覆盖率作为优化目标,建立WSNs覆盖模型,将具有遍历性特点的混沌系统引入到人工鱼群算法中,能够有效避免算法长时间位于局部极值附近。仿真结果表明:改进的人工鱼群算法提高了网络的覆盖率,有效减低了网络的成本。

In order to enhance coverage effect of large-scale wireless sensor networks （WSNs） for water environment monitoring of the Three Gorges reservoir and prolong survival time of large-scale WSNs, using the chaos artificial fish swarm algorithm （AFSA）. First, using maximize network coverage as optimization objectives and establish WSNs coverage model, then apply the chaotic system which has characteristics of ergodicity to AFSA, the algorithm can effectively avoid to be located near the local extremum for a long time. Simulation results show that the improved AFSA improves network coverage rate, effectively reduces cost of the network.