传感器网络中时空关联的脏数据过滤技术

Technique of filtering dirty data based on temporal-spatial correlation in sensor network

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数据的时空关联特性,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。

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.