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

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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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Authors and Affiliations

  1. Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

    Elham Moridi & Somayyeh Jafarali Jassbi

  2. Department of Computer Engineering, Yadegar-e-Imam Khomeini (RAH) Shahre Rey Branch, Islamic Azad University, Tehran, Iran

    Majid Haghparast

  3. Institute of Research and Development, Duy Tan University, Da Nang, 550000, Vietnam

    Mehdi Hosseinzadeh

  4. Health Management and Economics Research Center, Iran University of Medical Sciences, Tehran, Iran

    Mehdi Hosseinzadeh

Authors
  1. Elham Moridi
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  2. Majid Haghparast
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  3. Mehdi Hosseinzadeh
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  4. Somayyeh Jafarali Jassbi
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Correspondence to Majid Haghparast.

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Moridi, E., Haghparast, M., Hosseinzadeh, M. et al. Novel Fault Management Framework Using Markov Chain in Wireless Sensor Networks: FMMC. Wireless Pers Commun 114, 583–608 (2020). https://doi.org/10.1007/s11277-020-07383-2

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  • DOI: https://doi.org/10.1007/s11277-020-07383-2

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