Anomaly reading detection algorithm in WSN
无线传感器网络中异常读数检测算法研究

Found that the existing outlier detection algorithms in WSN are of some disadvantages such as lower detection precision, higher communication complexity and computational complexity due to not enough consideration of the spatio-temporal correlation of data and the characteristic of distribution networks. This paper proposed a novel distributed on-line outlier detection algorithm based on spatio-temporal correlation. In each sensor node, using sliding window technique generated a set of candidate outliers based time-correlated sensor readings, and using filtering technology generated a set of local outliers based spatial neighborhood. Ultimately, in sink sensor node, collecting whole local outliers in all nodes obtained the set of global outliers according to the outlying degree. Using spatial and temporal correlation improved the detection accuracy, and using distributed computing reduced the amount of communication and computation. Theoretical analysis and experimental results show that the proposed algorithm is superior to existing algorithms.