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Network Reliability Modeling Based on a Geometric Counting Process

Author

Listed:
  • Somayeh Zarezadeh

    (Department of Statistics, Shiraz University, Shiraz 71454, Iran)

  • Somayeh Ashrafi

    (Department of Statistics, University of Isfahan, Isfahan 81744, Iran)

  • Majid Asadi

    (Department of Statistics, University of Isfahan, Isfahan 81744, Iran
    School of Mathematics, Institute of Research in Fundamental Sciences (IPM), P.O. Box 19395-5746, Tehran, Iran)

Abstract

In this paper, we investigate the reliability and stochastic properties of an n -component network under the assumption that the components of the network fail according to a counting process called a geometric counting process (GCP). The paper has two parts. In the first part, we consider a two-state network (with states up and down ) and we assume that its components are subjected to failure based on a GCP. Some mixture representations for the network reliability are obtained in terms of signature of the network and the reliability function of the arrival times of the GCP. Several aging and stochastic properties of the network are investigated. The reliabilities of two different networks subjected to the same or different GCPs are compared based on the stochastic order between their signature vectors. The residual lifetime of the network is also assessed where the components fail based on a GCP. The second part of the paper is concerned with three-state networks. We consider a network made up of n components which starts operating at time t = 0 . It is assumed that, at any time t > 0 , the network can be in one of three states up , partial performance or down . The components of the network are subjected to failure on the basis of a GCP, which leads to change of network states. Under these scenarios, we obtain several stochastic and dependency characteristics of the network lifetime. Some illustrative examples and plots are also provided throughout the article.

Suggested Citation

  • Somayeh Zarezadeh & Somayeh Ashrafi & Majid Asadi, 2018. "Network Reliability Modeling Based on a Geometric Counting Process," Mathematics, MDPI, vol. 6(10), pages 1-17, October.
    • Handle: RePEc:gam:jmathe:v:6:y:2018:i:10:p:197-:d:174837
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    References listed on IDEAS

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    1. Belzunce, Félix & Mercader, José-Angel & Ruiz, José-María & Spizzichino, Fabio, 2009. "Stochastic comparisons of multivariate mixture models," Journal of Multivariate Analysis, Elsevier, vol. 100(8), pages 1657-1669, September.
    2. Francisco J. Samaniego, 2007. "System Signatures and their Applications in Engineering Reliability," International Series in Operations Research and Management Science, Springer, number 978-0-387-71797-5, March.
    3. Zarezadeh, S. & Asadi, M. & Balakrishnan, N., 2014. "Dynamic network reliability modeling under nonhomogeneous Poisson processes," European Journal of Operational Research, Elsevier, vol. 232(3), pages 561-571.
    4. S. Ashrafi & M. Asadi, 2015. "On the stochastic and dependence properties of the three-state systems," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 78(3), pages 261-281, April.
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    Cited by:

    1. Hayat D. Bedru & Chen Zhang & Feng Xie & Shuo Yu & Iftikhar Hussain, 2023. "CLARA: citation and similarity-based author ranking," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(2), pages 1091-1117, February.
    2. Ma, Chengye & Du, Yongjun & Zhang, Yuchun & Cai, Zhiqiang, 2022. "Marginal and joint failure importance for K-terminal network edges under counting process," Reliability Engineering and System Safety, Elsevier, vol. 223(C).

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