传感器网络中时空关联的脏数据过滤技术

摘要

The problem of filtering dirty data in wireless sensor network is studied. To solve the problem, the technique of filtering dirty data based on temporal-spatial correlation is proposed. The technique takes advantage of the temporal-spatial correlations of sensed data, and builds a temporal-spatial correlation model that filters out the dirty data First of all. Local nodes carry out the first-time filter to filter temporary error data through temporal correlation. Secondly, second-time filter is performed to filter permanent error data in a cluster through spatial correlation, Experiments verify the feasibility and effectiveness of the technique.%研究了无线传感器网络中脏数据过滤问题,提出了基于时空关联的脏数据过滤技术.该技术利用无线传感器网络中感知教据的时空关联特性,建立了时空关联脏数据过滤模型,通过其来过滤无线传感器节点产生的错误数据即脏数据.本地节点通过时间关联进行一次过滤,过滤掉暂时性错误数据；并在一个簇中采用空间关联进行二次过滤,过滤掉永久性错误数据.实验结果表明了该技术的合理性和有效性.