基于能量的EBAPC分簇网络拓扑控制算法

低功耗自适应集簇分层型协议LEACH算法对簇头的选择具有随机性，并且没有综合考虑节点的剩余能量、分布位置。为此，提出一种基于能量的仿射传播聚类EBAPC分簇拓扑控制算法。对适应度因子重新进行定义，借鉴仿射传播AP聚类算法中聚类中心的选择策略，簇头选择综合考虑无线传感器网络节点的剩余能量和节点之间的距离因素。仿真实验结果表明，EBAPC算法较LEACH算法分簇更均匀，簇头选择更合理，网络中能量的消耗更均衡，从而延长网络寿命。

Clustering Network Topology Control Algorithm for EBAPC Based on Energy

Aiming at the disadvantages of Low Energy Adaptive Clustering Hierarchy(LEACH) algorithm that cluster head selection is random, without considering the residual energy and the location of node, this paper proposes an algorithm called Energy-based Affinity Propagation Clustering(EBAPC) topology control algorithm, which is based on energy affinity propagation clustering. In EBAPC algorithm, a new definition called fitness factor is presented, and the cluster center selection strategy in affinity propagation clustering algorithm is borrowed. Experimental results show that in EBAPC algorithm, the cluster head selection is better reasonable, and extends the network lifetime compared with LEACH algorithm.