【摘要】 现有的无线传感器网络节点之间关联规则提取研究算法不多见,针对如何高效地处理传感器网络的海量数据,提取有用的数据,成为新的挑战。提出了一种改进的关联规则挖掘算法,利用集合的特征来分析节点关联性,对传感器网络进行数据融合起到了很大的帮助。仿真实验结果表明,该算法比AFET算法[1]有更高的运行效率,该算法进一步减少了计算所耗费的能量和占用的内存空间,延长了网络的寿命。更多还原

【Abstract】 The algorithm of mining node association rule in wireless sensor networks is little.How to process the large data streams in sensor networks efficiently and how to find interesting knowledge become new challenge.An improved node association rule mining algorithm in wireless sensor networks is proposed.The set characteristic is used to analyse the relation of nodes,this approach can help users in carring data aggregation greatly.In simulation experiment,it shows that the efficiency of the algorithm is higher than AFET [1].This algorithm reduces communication energy and usage of memory,prolongs the network lifetime.更多还原