基于粒子群优化的WSN非均匀分簇路由算法

分簇算法对大规模无线传感器网络(WSN)远程监控系统具有较好的节能性，簇首间通过多跳通信的方式将数据传送至基站，靠近基站的簇首由于需要转发大量其他簇首的数据而负载过重，可能因过早耗尽能量而失效，这将导致整个网络分割。针对现有无线传感器网络分簇算法存在的能耗不均衡问题，提出一种基于粒子群优化的非均匀分簇算法(PSO-UCA)。它采用PSO算法将所有节点划分为多个规模大小非均匀的簇，靠近基站的簇的规模小于远离基站的簇，因此靠近基站的簇首可为簇间的数据转发预留能量。仿真结果表明，与LEACH算法相比较，该分簇算法可使网络的生存时间延长30%。

Uneven clustering routing algorithm for WSN based on particle swarm optimization

Clustering algorithm provides an effective way to save energy for the large-scale Wireless Sensor Network (WSN) remote monitoring system. Cluster-heads communicate data to the base-station through the multihop routing way. The cluster-heads closer to the base-station may be over-loaded due to transmitting lots of other cluster-heads data, which may consume all the energy and be early dead so as to cause the entire networks partition. Concerning the uneven energy consumption in wireless sensor networks clustering algorithm, an uneven clustering algorithm based on Particle Swarm Optimization (PSO) was proposed. By using the PSO algorithm, PSO-UCA partitioned all nodes into clusters of unequal size, which the clusters closer to the base-station have smaller size. Thus, the cluster-heads closer to the base-station can preserve more energy for the inter-cluster relay traffic. The simulation results demonstrate that, compared with LEACH algorithm, the clustering algorithm can prolong the network lifetime by 30%.