Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/18104
Title: Fault-tolerant algorithms for detecting event regions in wireless sensor networks using statistical hypothesis test
Authors: Cao, D
Jin, B
Cao, J 
Keywords: Event region detection
Fault tolerance
Statistical hypothesis test
Temporal correlation examining
Wireless sensor network
Issue Date: 2008
Source: Proceedings of the International Conference on Parallel and Distributed Systems - ICPADS, 2008, 4724374, p. 631-638 How to cite?
Abstract: Detecting event regions in a monitored environment is a canonical task of wireless sensor networks (WSNs). It is a hard problem because sensor nodes are prone to failures and have scarce energy. In this paper, we seek distributed and localized algorithms for fault-tolerant event region detection. Most existing algorithms only assume that events are spatially correlated, but we argue that events are usually both spatially and temporally correlated. By examining the temporal correlation of sensor measurements, we propose two detection algorithms by applying statistical hypothesis test (SHT). Our analyses show that SHT-based algorithm is more accurate in detecting event regions. Moreover, it is more energy efficient since it gets rid of frequent measurement exchanges. In order to improve the capability of fault recognition, we extend SHT-based algorithm by examining both spatial and temporal correlations of sensor measurements, and our analyses show that extended SHT-based algorithm can recognize almost all faults when sensor network is densely deployed.
Description: 2008 14th IEEE International Conference on Parallel and Distributed Systems, ICPADS'08, Melbourne, VIC, 8-10 December 2008
URI: http://hdl.handle.net/10397/18104
ISSN: 1521-9097
DOI: 10.1109/ICPADS.2008.64
Appears in Collections:Conference Paper

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