CHEN Huan-huan, HUANG Jian, WANG Kai, et al. Research on WSNs fault detection method based on node similarity[J]. 2014, 33(4): 10-13. DOI: 10.13873/j.1000-97872014.04.019.
Aiming at present distributed fault detection algorithms for wireless sensor networks( WSNs) have assume that the fault node are based on outliers data
it have limitations. Present a method based on similarity comparison of nodes of WSNs fault detection
according to correlation of time and space of node data within the cluster
the cluster head nodes measure the similarity among cluster nodes
and adjust node confidence level realtime
calculate the optimal threshold value which is 0. 8 by using optimal function in current experiments to judge fault node. Through simulation experiments show that aiming at different fault model
the algorithm keep in good ability of fault detection
and solve the problem of generality in a certain extent.
Distributed online outlier detection in wireless sensor networks using ellipsoidal support vector machine [J] . Yang Zhang,Nirvana Meratnia,Paul J.M. Havinga. Ad Hoc Networks . 2012
Sensor network data fault types [J] . Kevin Ni,Nithya Ramanathan,Mohamed Nabil Hajj Chehade,Laura Balzano,Sheela Nair,Sadaf Zahedi,Eddie Kohler,Greg Pottie,Mark Hansen,Mani Srivastava. ACM Transactions on Sensor Networks (TOSN) . 2009 (3)
Measuring quality of similarity functions in approximate data matching [J] . Roberto da Silva,Raquel Stasiu,Viviane Moreira Orengo,Carlos A. Heuser. Journal of Informetrics . 2006 (1)