Malfunction Detection and Localization Algorithm for Wireless Sensor Network

Recently, the graph signal processing paves a new way to analyze the data residing in the networks. In this letter, the graph signal processing theory is applied to detect and localize the malfunctioning sensors caused by the sheer quality and complicated deploying environment of wireless sensor networks. Based on the high-pass graph filter and the history data information, a two-channel graph filtering structure is constructed to not only detect the malfunctioning phenomenon but also determine the positions of the malfunctioning sensors. The proposed scheme is operated on vertex domain, in which the graph Fourier transform is not required. Numerical examples conducted on the real-world data on sensor networks and artificial attack on IEEE bus grids demonstrate the effectiveness of the proposed algorithm.