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A Monte-Carlo Markov chain approach for coverage-area reliability of mobile wireless sensor networks with multistate nodes

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  • Chakraborty, Suparna
  • Goyal, N.K.
  • Mahapatra, S.
  • Soh, Sieteng

Abstract

A mobile Wireless Sensor Network (mWSN) is composed of a large number of tiny, inexpensive resource-constrained sensors scattered in the field of interest, with the sink node or the data collector moving around the field. One fundamental concern of an mWSN is to provide application-specific coverage of the area under surveillance. The reliability of an mWSN depends on sensing area coverage, network connectivity, and data handling capacity of the mWSN in the presence of multi-state sensors. To mention here, each sensor node during its life cycle may exist in ACTIVE, SLEEP, RELAY, IDLE or FAIL states due to hardware failure, random duty cycle and/or energy limitations. Under such constraints, to quantify application-specific coverage oriented reliability, a new coverage-reliability index, CORE, is introduced. CORE gives a measure of the ability of a sensor network with multi-state nodes to satisfy the application-specific coverage area requirement with reliable data delivery to the mobile sink. A Monte-Carlo Markov Chain simulation approach is proposed for evaluating CORE. The conducted computational experiments are carried on mWSNs of various sizes to demonstrate the versatility of the proposed approach.

Suggested Citation

  • Chakraborty, Suparna & Goyal, N.K. & Mahapatra, S. & Soh, Sieteng, 2020. "A Monte-Carlo Markov chain approach for coverage-area reliability of mobile wireless sensor networks with multistate nodes," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    • Handle: RePEc:eee:reensy:v:193:y:2020:i:c:s0951832019300353
    DOI: 10.1016/j.ress.2019.106662
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    References listed on IDEAS

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    1. Cook, Jason L. & Ramirez-Marquez, Jose Emmanuel, 2008. "Reliability analysis of cluster-based ad-hoc networks," Reliability Engineering and System Safety, Elsevier, vol. 93(10), pages 1512-1522.
    2. Jason Cook & Jose Ramirez-Marquez, 2009. "Mobility and reliability modeling for a mobile network," IISE Transactions, Taylor & Francis Journals, vol. 41(1), pages 23-31.
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    4. Yeh, Wei-Chang, 2007. "An improved sum-of-disjoint-products technique for the symbolic network reliability analysis with known minimal paths," Reliability Engineering and System Safety, Elsevier, vol. 92(2), pages 260-268.
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    4. F. C. S. Eiras & W. L. Zucchi, 2021. "A simulation model for area coverage and loss probability on mobile sensor networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 76(1), pages 3-16, January.
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    9. Xiang, Shihu & Yang, Jun, 2023. "A novel adaptive deployment method for the single-target tracking of mobile wireless sensor networks," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    10. Fu, Xiuwen & Yang, Yongsheng, 2020. "Modeling and analysis of cascading node-link failures in multi-sink wireless sensor networks," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
    11. Amir Masoud Rahmani & Saqib Ali & Mohammad Sadegh Yousefpoor & Efat Yousefpoor & Rizwan Ali Naqvi & Kamran Siddique & Mehdi Hosseinzadeh, 2021. "An Area Coverage Scheme Based on Fuzzy Logic and Shuffled Frog-Leaping Algorithm (SFLA) in Heterogeneous Wireless Sensor Networks," Mathematics, MDPI, vol. 9(18), pages 1-41, September.
    12. Yeh, Wei-Chang & Hao, Zhifeng & Forghani-elahabad, Majid & Wang, Gai-Ge & Lin, Yih-Lon, 2021. "Novel Binary-Addition Tree Algorithm for Reliability Evaluation of Acyclic Multistate Information Networks," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
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    14. Cui, Hongjun & Wang, Fei & Ma, Xinwei & Zhu, Minqing, 2022. "A novel fixed-node unconnected subgraph method for calculating the reliability of binary-state networks," Reliability Engineering and System Safety, Elsevier, vol. 226(C).

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