WSN中基于能量和距离的自适应分层路由算法

摘要

Aiming at the problem of energy limitation in wireless sensor networks (WSN),this paper presented an energy sa-ving and load balancing clustering routing (EDUC)algorithm.EDUC generated candidate cluster-heads by using energy-based and distance-based probability model.At the same time,EDUC utilized timer to make the candidate cluster-heads with high residual energy in local area become cluster-heads.In addition,EDUC calculated clusters’radius on the basis of energy and distance.Moreover,ordinary nodes calculated candidate nodes’weight on the basis of energy and distance,and then they joined the cluster-head with the biggest weight.Furthermore,at the phase of constructing multi-hop routing,cluster-heads considered tentative nodes’residual energy,costs of inter-cluster and intra-cluster communication to select an optimal relay node.Simulation results on OMNet++show that EDUC can efficiently balance energy consumption,reduce the speed of nodes dying and prolong the network lifetime compared with other algorithms.%针对无线传感器网络中能量受限的问题，提出了节能的、负载均衡的分层路由算法EDUC（energy-based and distance-based unequal clustering algorithm）。EDUC用基于能量和距离的概率模型产生候选簇头；同时，EDUC利用定时器，使局部区域内剩余能量多的候选簇头成为簇头，并且根据能量和距离计算簇的半径。普通节点根据能量和距离计算候选节点的权值，加入权值最大的簇头。在构建多跳路由时，簇头根据候选节点的剩余能量、簇内和簇间通信代价选择最优的中继节点。在OMNet＋＋平台上的仿真结果表明，与其他算法相比，EDUC能够有效地均衡能量消耗，降低节点死亡速度，从而延长网络生命周期。