融合信任机制和HBMO算法的WSN能耗均衡分簇方法

针对无线传感器网络(WSN)中的能耗和安全问题,提出一种融合蜜蜂交配优化(HBMO)算法和轻量级信任机制的WSN分簇方法(LWT-HBM).首先,将WSN分成若干个小区,通过HBMO算法选择各自最优的簇头;然后,构建分簇结构,根据簇头和基站的距离设置簇的大小.在簇头能量消耗殆尽前,会利用HBMO选择替代簇头,以此均衡网络能源.在选择簇头的同时,融入轻量级信任机制,根据直接信任和间接信任值来评估节点的可信任度,避免恶意节点被选择为簇头.同时给出了一种精确能耗模型用来计算系统的整体能耗.通过实验将此方法与LEACH和TBCMA方法进行比较,结果表明LWT-HBM方法具有更低的能耗,有效的延长了网络寿命.

An Energy Consumption Balance Clustering Method in WSN Fusing Trust Mechanism and HBMO Algorithm

In view of energy consumption and safety problems in Wireless Sensor Network (WSN), a WSN clustering method named LWT-HBM is proposed, with the fusion of Honey-bee Mating Optimization (HBMO) algorithm and Light Weight Trust (LWT) mechanism. First of all, the WSN is divided into several clusters, and the optimal head of each cluster is selected by HBMO algorithm. Then, the cluster structure is constructed, the size of each cluster is set according to the distance from cluster head to base station. And in order to balance the network energy, the alternative cluster head will be selected using HBMO, before the energy of cluster head depleted. At the same time of cluster head selection, a light weight trust mechanism is being fused and the node trustworthiness is assessed according to the direct and indirect trust value so as to avoid malicious node becoming a cluster head, and an accurate energy consumption model is given to calculate the overall energy consumption of the system. The experimental results show that, compared with the LEACH and TBCMA methods, LWT-HBM method has lower energy consumption, which can extend the network lifetime.