无线传感器网络能量高效数据收集的分簇算法*

传感器网络所具有的集中式数据收集、多跳数据传输、多对一流量模式这三种特征会造成漏斗效应的出现,这会导致严重的包碰撞、网络拥塞、包丢失,甚至拥塞崩溃,还会导致能量消耗的热点出现，使某些节点甚至整个网络过早死亡。利用感知数据的空间相关性，将相邻的节点分组，每组选出一个簇首作为整个组的代表，将其传送给基站来缓解漏斗效应问题。在CAG算法的基础上利用感知数据的空间特性提出了一个改进的节点分簇算法，该算法可以有效减少簇首数量，从而降低传输能量消耗。实验结果也验证了算法的有效性。

Energy-efficient clustering algorithm for data gathering in WSN

Wireless sensor networks are characterized by centralized data gathering, multi-hop communication and many-to-one traffic pattern. These three characteristics may give rise to funneling effects that can lead to severe packet collision, network congestion, packet loss and even congestion collapse. This can also result in hotspots of energy consumption that may cause premature death of sensor nodes and even premature death of entire network.Exploiting spatial correlation of nodes to form clusters of nodes sensing similar values,and only cluster head sensor reading was transmit to sink, such could efficiently alleviate the funneling effects. Based on the CAG algorithm,proposed a novelty clustering algorithm which could greatly reduce the number of cluster heads. Experimental results validate the effectiveness of this approach.