Hyperspherical cluster based distributed anomaly detection in wireless sensor networks
Data(s) |
01/01/2014
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Resumo |
This article describes a distributed hyperspherical cluster based algorithm for identifying anomalies in measurements from a wireless sensor network, and an implementation on a real wireless sensor network testbed. The communication overhead incurred in the network is minimised by clustering sensor measurements and merging clusters before sending a compact description of the clusters to other nodes. An evaluation on several real and synthetic datasets demonstrates that the distributed hyperspherical cluster-based scheme achieves comparable detection accuracy with a significant reduction in communication overhead compared to a centralised scheme, where all the sensor node measurements are communicated to a central node for processing. . |
Identificador | |
Idioma(s) |
eng |
Publicador |
Elsevier |
Relação |
http://dro.deakin.edu.au/eserv/DU:30089205/rajasegarar-highresolution-2014.pdf http://www.dx.doi.org/10.1016/j.jpdc.2013.09.005 |
Direitos |
2014, Elsevier |
Palavras-Chave | #Distributed processing #Wireless sensor networks #Anomaly detection |
Tipo |
Journal Article |