中文摘要：

为解决现有无线传感器网络（WSN）分簇算法难以同时兼顾其异构性和移动性,从而引发网络寿命较短、网络数据吞吐量较低等问题,提出了基于节点等级的自适应分簇算法。该算法按轮运行,每轮分为自适应分簇、簇建立、数据传输三个阶段。为解决节点移动性引发的簇首数目和成簇规模不合理的问题,在自适应分簇阶段,根据子区域内节点数目变化对相应子区域进行细化或就近合并,以确保每个子区域内节点数目在合理范围内。在簇建立阶段,选举簇内等级最高的节点为簇首,解决异构性引发的部分节点能耗过快、网络寿命缩短的问题;节点等级除考虑节点剩余能量外,还结合WSN实际应用,由节点剩余能量、能量消耗速率、到基站的距离、到簇内其他节点的距离综合决定。基于OMNe T＋＋和Matlab的仿真实验结果表明,在节点移动速度为0~0.6 m/s的能量异构WSN环境下,较移动低功耗自适应集簇分层（LEACH-Mobile）算法和分布式能量有效分簇（DEEC）算法,运用所提算法分簇的WSN寿命延长了30.9%以上,网络数据吞吐量是其他两种算法分簇的网络的1.15倍以上。

英文摘要：

To solve the short life time and low network throughput problems caused by the heterogeneity and mobility of Wireless Sensor Network （WSN） clustering algorithm, an Adaptive Clustering Algorithm based on Grades （ACA_G） was proposed. The proposed algorithm was run on rounds, which was composed of three stages： the adaptive clustering stage, the cluster construction stage and the data transmission stage. In the adaptive clustering stage, every partition may be subdivided or united adjacently according to the change of the number of nodes in each partition to keep an appropriate number of nodes in it. The adaptive clustering measure could be able to solve the unreasonable problems of the number of cluster-heads and the scale of clusters caused by the node mobility in WSN. In order to deal with the phenomena of some nodes died too fast and the life time of WSN was shortened caused by the heterogeneity in WSN, the node with the highest grade was selected as the cluster-head in the cluster construction stage. In the WSN application, the grade of each node was calculated according to the node residual energy, the speed of energy consumption, the distance between the node and the base station, the accumulated distance between the node and other nodes in the same cluster. The experiment was simulated by OMNeT ＋ ＋ and Matlab on a WSN with energy heterogeneity, in which node＇s mobile speed is 0 ~ 0.6 m/s randomly. The experimental results show that, compared with the Low Energy Adaptive Clustering Hierarchy -Mobile （LEACH-Mobile） algorithm and the Distributed Energy- Efficient Clustering （DEEC） algorithm, the life time of WSN clustered by the proposed algorithm is 30.9% longer than the other two algorithms, its network throughout is 1.15 times at least as much as the other two algorithms.