基于布谷鸟优化K均值的WSN分簇路由算法

WSN clustering routing algorithm based on Cuckoo Search algorithm optimized K-means

为了延长无线传感器网络生命周期,提出了一种基于布谷鸟优化K均值(K-means)的无线传感器网络分簇路由算法。分簇阶段,使用布谷鸟算法选出初始聚类中心,使K-means算法的分簇结果更均匀,以均衡节点能耗;簇首选举综合考虑节点的剩余能量、与聚类中心的距离因素,并依据节点剩余能量动态调整权重,使选举的簇首更合理;数据通信阶段,为了进一步均衡簇首负载,综合考虑中继节点剩余能量及其负载、簇首路由能耗因素,结合布谷鸟算法为簇首规划路由。仿真结果表明,提出的算法在能耗均衡性方面比LEACH-K、LEACH-improve和DTK-means算法更优,以首节点死亡作为网络生命周期,网络寿命分别提高了173%、21%、6%,所提算法有效延长了网络生命周期。

In order to extend the lifetime of wireless sensor network(WSN),a clustering routing algorithm for WSN based on Cuckoo Search(CS)algorithm optimized K-means was presented.In the clustering stage,the initial cluster centers were selected by CS algorithm,which make the clustering results of the K-means algorithm more uniform to balance node energy consumption.The remaining energy of the node,the distance from the center of the cluster were comprehensively considered in the cluster election,and the weight according to the remaining energy of the node was dynamically adjusted.In the data communication stage,in order to further balance the load of the cluster head,the remaining energy of the relay node and its load,and the cluster head routing energy consumption were comprehensively considered,CS algorithm was combined to plan routing for the cluster head.The simulation results show that the proposed algorithm is better than LEACH-K,LEACH-improve and DTK-means in terms of energy consumption balance.With the death of the first node as the life cycle of the network,the network lifespan was increased by 173%,21%,and 6%respectively.The proposed algorithm effectively extending the network life cycle.