A fault inference mechanism in sensor networks using Markov Chain

Elhadi Shakshuki, Xing Xinyu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

The reliability of communication and sensor devices has been recognized as one of the crucial issues in Wireless Sensor Networks (WSNs). In distributed environments, micro-sensors are subject to high-frequency faults. To provide high stability and availability of large scale sensor networks, we propose a fault inference mechanism based on reverse multicast tree to evaluate sensor nodes' fault probabilities. This mechanism is formulated as maximization- likelihood estimation problem. Due to the characteristics (energy awareness, constraint bandwidth and so on) of wireless sensor networks; it is infeasible for each sensor to announce its working state to a centralized node. Therefore, maximum likelihood estimates of fault parameters depend on unobserved latent variables. Hence, our proposed inference mechanism is abstracted as Nondeterministic Finite Automata (NFA). It adopts iterative computation under Markov Chain to infer the fault probabilities of nodes in reverse multicast tree. Through our theoretical analysis and simulation experiments, we were able to achieve an accuracy of fault inference mechanism that satisfies the necessity of fault detection.

Original languageEnglish (US)
Title of host publicationProceedings - 22nd International Conference on Advanced Information Networking and Applications, AINA 2008
Pages628-635
Number of pages8
DOIs
StatePublished - Sep 1 2008
Event22nd International Conference on Advanced Information Networking and Applications, AINA 2008 - Gino-wan, Okinawa, Japan
Duration: Mar 25 2008Mar 28 2008

Publication series

NameProceedings - International Conference on Advanced Information Networking and Applications, AINA
ISSN (Print)1550-445X

Other

Other22nd International Conference on Advanced Information Networking and Applications, AINA 2008
CountryJapan
CityGino-wan, Okinawa
Period3/25/083/28/08

Fingerprint

Markov processes
Sensor networks
Wireless sensor networks
Sensors
Finite automata
Fault detection
Sensor nodes
Maximum likelihood
Availability
Bandwidth
Communication
Experiments

All Science Journal Classification (ASJC) codes

  • Engineering(all)

Cite this

Shakshuki, E., & Xinyu, X. (2008). A fault inference mechanism in sensor networks using Markov Chain. In Proceedings - 22nd International Conference on Advanced Information Networking and Applications, AINA 2008 (pp. 628-635). [4482765] (Proceedings - International Conference on Advanced Information Networking and Applications, AINA). https://doi.org/10.1109/AINA.2008.36
Shakshuki, Elhadi ; Xinyu, Xing. / A fault inference mechanism in sensor networks using Markov Chain. Proceedings - 22nd International Conference on Advanced Information Networking and Applications, AINA 2008. 2008. pp. 628-635 (Proceedings - International Conference on Advanced Information Networking and Applications, AINA).
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Shakshuki, E & Xinyu, X 2008, A fault inference mechanism in sensor networks using Markov Chain. in Proceedings - 22nd International Conference on Advanced Information Networking and Applications, AINA 2008., 4482765, Proceedings - International Conference on Advanced Information Networking and Applications, AINA, pp. 628-635, 22nd International Conference on Advanced Information Networking and Applications, AINA 2008, Gino-wan, Okinawa, Japan, 3/25/08. https://doi.org/10.1109/AINA.2008.36

A fault inference mechanism in sensor networks using Markov Chain. / Shakshuki, Elhadi; Xinyu, Xing.

Proceedings - 22nd International Conference on Advanced Information Networking and Applications, AINA 2008. 2008. p. 628-635 4482765 (Proceedings - International Conference on Advanced Information Networking and Applications, AINA).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Shakshuki E, Xinyu X. A fault inference mechanism in sensor networks using Markov Chain. In Proceedings - 22nd International Conference on Advanced Information Networking and Applications, AINA 2008. 2008. p. 628-635. 4482765. (Proceedings - International Conference on Advanced Information Networking and Applications, AINA). https://doi.org/10.1109/AINA.2008.36