采用粒子群优化的WSN非均匀网格划分机制

为了均衡消耗网络能量,提出了一种采用粒子群优化的无线传感器网络非均匀网格划分机制(NuGPM).将网络分为k层,相同层的网格长度相同,不同层之间的网格宽度不同,且离基站越近的层其网格宽度越大,采用粒子群优化算法搜索各层网格的最优宽度组合.该机制能使离基站越近的网格拥有越多的节点,从而拥有越多的能量转发上层网格的数据,进而改善基站附近的"热点"问题.仿真结果表明,NuGPM能均衡消耗网络能量,有效改善基站附近的热点问题,延长网络寿命.

Non-Uniform Grid Partition Mechanism Using Particle Swarm Optimization for Wireless Sensor Networks

In order to balance energy consumption of network, a non-uniform grid partition mechanism (NuGPM) based on particle swarm optimization is proposed to improve network’s performance in wireless sensor networks. In NuGPM, network is split into k layers, the grids of the same layer have the same length, and the grids in different layers have different width. If the layer is closer to base station, its grid has bigger width. The particle swarm optimization algorithm is adopted to search the best width-combination of grids in all layers. The mechanism is able to make grids which are closer to base station have more nodes. By adopting this method, the grids near base station will have more energy to forward packets from grids of upper layer, and the hot spot problem near base station can be improved. The simulation results show that the proposed mechanism is able to balance the energy consumption of whole network, improve the hot spot problem near base station effectively, and extend the network’s lifetime.