认知视角下能量感知的ZigBee网络树型路由优化算法

为解决ZigBee Cluster-Tree路由算法路径选择不优的问题,提出了一种能量感知的ZigBee树型路由EZTR(Energy-Aware ZigBee tree routing)算法.该算法利用每个节点感知的地址信息,按照ZigBee网络树型结构计算下一跳邻居节点到目的节点之间的跳数可避免网络的环路效应,通过引入认知概念,在跳数集合中选出最短路径以降低跳数.在ZigBee网络节点能量的感知过程中,当所选路径存在低能量节点时,及时启用备用节点,从而避免节点因能量过度消耗成为失效节点.NS2(Network simulator version 2)仿真实验表明,EZTR算法可提高网络分组递交率,有效减少节点转发跳数和平均网络延时,减小网络整体能耗,为提高网络的实时性和延长网络生命周期提供理论支持.

Energy-aware tree routing optimization algorithm for ZigBee networks: a cognitive perspective

To improve the problem of failing to well select optimal path for ZigBee Cluster-Tree routing algorithm, ZigBee routing based on Energy-Aware (EZTR) algorithm was proposed. Firstly, using each node perceiving its own address, this algorithm calculated packet forwarding hop-counts that the next hop of node to destination node according to tree structure for avoiding the loop response, by introducing the concept of cognitive for ZigBee network, and selected the shortest routing in hop-counts set to reduce hop-counts. Besides, in order to avoid excessive energy consumption of nodes, which caused nodes to be ineffective, through energy cognitive processing, when there is a low energy nodes selected path, EZTR algorithm timely adopted alternate node. Through comparative analysis of NS2 simulation experiments, packet delivery ratio is improved, hop-counts and average delay are reduced, and network energy consumption is saved, which can provide theoretical support for improving network real-time and extend network lifetime.