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Wireless Personal Communications
Erschienen in: Wireless Personal Communications 1/2020

22.04.2020

Novel Fault Management Framework Using Markov Chain in Wireless Sensor Networks: FMMC

verfasst von: Elham Moridi, Majid Haghparast, Mehdi Hosseinzadeh, Somayyeh Jafarali Jassbi

Erschienen in: Wireless Personal Communications | Ausgabe 1/2020

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Abstract

Due to using wireless sensor nodes (WSNs) in inaccessible areas and applying limitations in making nodes to reduce costs, these networks are prone to faults. The performance and efficiency of the networks should not be affected by faults so that fault tolerance is a required feature. To improve fault tolerance and ensure optimal performance of network, fault detection and recovery or fault management is essential. This paper represents a fault management framework based on clustering algorithms to detect and recover faults in WSNs. In the proposed method, on self-detecting and diagnosing faults, all faults are modeled through Markov chain. In recovery phase, the status of nodes is defined based on the type of fault so that the faults are recovered. The results of simulation reveal that the proposed fault management framework results in improved energy consumption, increased number of alive nodes, improved detection accuracy, and reduced false alarm rate compared with other frameworks.
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Metadaten
Titel
Novel Fault Management Framework Using Markov Chain in Wireless Sensor Networks: FMMC
verfasst von
Elham Moridi
Majid Haghparast
Mehdi Hosseinzadeh
Somayyeh Jafarali Jassbi
Publikationsdatum
22.04.2020
Verlag
Springer US
Erschienen in
Wireless Personal Communications / Ausgabe 1/2020
Print ISSN: 0929-6212
Elektronische ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-020-07383-2

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