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Reliability evaluation of wireless multimedia sensor networks based on instantaneous availability

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  • Yi Yang
  • Sixin Wang
  • Wei Xu
  • Kunlun Wei

Abstract

With the widespread application of wireless multimedia sensor networks, the issue of network reliability has attracted more and more attention. In this article, a new reliability evaluation method of wireless multimedia sensor network is proposed. The failure is regarded as a percolation process, and the percolation threshold is taken as the failure indicator in this method. Accordingly, instantaneous availability model of wireless multimedia sensor network is established combining percolation theory and Markov process on the basis of reliability characteristics analysis. By Laplace transformation, the analytic solution is worked out, and one numerical example is given to verify the model comparing with existing studies. Finally, numerical simulation analyses are used to show the impact of different parameters on instantaneous availability, and the ways to suppress fluctuations are obtained by comparing with fluctuation images.

Suggested Citation

  • Yi Yang & Sixin Wang & Wei Xu & Kunlun Wei, 2018. "Reliability evaluation of wireless multimedia sensor networks based on instantaneous availability," International Journal of Distributed Sensor Networks, , vol. 14(11), pages 15501477188, November.
    • Handle: RePEc:sae:intdis:v:14:y:2018:i:11:p:1550147718810692
    DOI: 10.1177/1550147718810692
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    References listed on IDEAS

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    1. Hui Zhang & Cheng-Xiang Zhuge & Xiang Zhao & Wen-Bo Song, 2018. "Assessing transfer property and reliability of urban bus network based on complex network theory," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 29(01), pages 1-13, January.
    2. Fink, Olga & Zio, Enrico & Weidmann, Ulrich, 2014. "Predicting component reliability and level of degradation with complex-valued neural networks," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 198-206.
    3. Raimund Kovacevic & Alois Pichler, 2015. "Tree approximation for discrete time stochastic processes: a process distance approach," Annals of Operations Research, Springer, vol. 235(1), pages 395-421, December.
    4. Mi, Jinhua & Li, Yan-Feng & Yang, Yuan-Jian & Peng, Weiwen & Huang, Hong-Zhong, 2016. "Reliability assessment of complex electromechanical systems under epistemic uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 1-15.
    5. Li, Daqing & Zhang, Qiong & Zio, Enrico & Havlin, Shlomo & Kang, Rui, 2015. "Network reliability analysis based on percolation theory," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 556-562.
    6. Xiao Jia & Jin-Song Hong & Ya-Chun Gao & Hong-Chun Yang & Chun Yang & Chuan-Ji Fu & Jian-Quan Hu, 2016. "Percolation phase transition of static and growing networks under a weighted function," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 27(07), pages 1-8, July.
    7. Kim, Youngsuk & Kang, Won-Hee, 2013. "Network reliability analysis of complex systems using a non-simulation-based method," Reliability Engineering and System Safety, Elsevier, vol. 110(C), pages 80-88.
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