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针对无线传感网中经典的分簇路由协议LEACH分簇数量随机和分簇不均匀导致网络能耗大的问题,提出基于K-Means的均匀分簇路由(KUCR)算法。KUCR算法在网络初始化时由基站采用K-Means聚类算法,根据所有节点的地理位置和节点ID计算并形成k个均匀分簇并通告给网络节点,分簇后簇内节点采用分布式方法基于自身剩余能量和距基站的距离竞选簇首,剩余能量高且距离近的节点成为簇头。至此完成网络初始化,此后网络运行的每一轮中不再重新分簇只是在簇内更新簇首。簇首负责簇内数据收集并发送给基站。通过仿真比较KUCR、LEACH与LEACH-C,KUCR使得无线传感网中各个节点能耗更均衡,网络生存期更长,并降低了网络时延。
Aiming at the problem of large energy consumption of LEACH clustering in wireless sensor networks, which is caused by the random number and clustering unevenness, a K-Means-based uniform clustering routing (KUCR) algorithm is proposed. The KUCR algorithm uses the K-Means clustering algorithm at the initial stage of the network, calculates and forms k uniform clusters according to the geographical positions and node IDs of all the nodes, and announces them to the network nodes. The clustered nodes in the cluster are distributed based on the distributed method The remaining energy of itself and the distance from the base station are chosen as cluster heads. The nodes with high residual energy and close distance become cluster heads. So far to complete the network initialization, after each run of the network is no longer re-clustering update cluster head only in the cluster. The cluster heads are responsible for collecting data in the cluster and sending it to the base station. Compared with KUCR, LEACH, LEACH-C and KUCR, the energy consumption of each node in wireless sensor network is more balanced, the network lifetime is longer and the network delay is reduced.