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.
Original language | English |
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Article number | 4724374 |
Pages (from-to) | 631-638 |
Number of pages | 8 |
Journal | Proceedings of the International Conference on Parallel and Distributed Systems - ICPADS |
DOIs | |
Publication status | Published - 1 Dec 2008 |
Event | 2008 14th IEEE International Conference on Parallel and Distributed Systems, ICPADS'08 - Melbourne, VIC, Australia Duration: 8 Dec 2008 → 10 Dec 2008 |
Keywords
- Event region detection
- Fault tolerance
- Statistical hypothesis test
- Temporal correlation examining
- Wireless sensor network
ASJC Scopus subject areas
- Hardware and Architecture