You are not logged in.

Hyperspherical cluster based distributed anomaly detection in wireless sensor networks

Rajasegarar, Sutharshan, Leckie, Christopher and Palaniswami, Marimuthu 2014, Hyperspherical cluster based distributed anomaly detection in wireless sensor networks, Journal of parallel and distributed computing, vol. 74, no. 1, pp. 1833-1847, doi: 10.1016/j.jpdc.2013.09.005.

Attached Files
Name Description MIMEType Size Downloads

Title Hyperspherical cluster based distributed anomaly detection in wireless sensor networks
Author(s) Rajasegarar, Sutharshan
Leckie, Christopher
Palaniswami, Marimuthu
Journal name Journal of parallel and distributed computing
Volume number 74
Issue number 1
Start page 1833
End page 1847
Total pages 15
Publisher Elsevier
Place of publication Amsterdam, The Netherlands
Publication date 2014-01-01
ISSN 0743-7315
Keyword(s) Distributed processing
Wireless sensor networks
Anomaly detection
Summary 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. .
Language eng
DOI 10.1016/j.jpdc.2013.09.005
Field of Research 080109 Pattern Recognition and Data Mining
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category C1.1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2014, Elsevier
Persistent URL http://hdl.handle.net/10536/DRO/DU:30089205

Document type: Journal Article
Collection: School of Information Technology
Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 12 times in TR Web of Science
Scopus Citation Count Cited 18 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 4 Abstract Views, 1 File Downloads  -  Detailed Statistics
Created: Wed, 23 Nov 2016, 11:26:51 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.