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Evaluation of the one-to-all-target-subsets reliability of a novel deterioration-effect acyclic multi-state information network

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  • Yeh, Wei-Chang

Abstract

It is assumed that information in a traditional multi-state information network (MIN) can be sent anywhere. However, in practical applications, the intensity of information (the capacity of information to be transmitted) is gradually reduced because of the deterioration effect. For example, a Wi-Fi signal decreases if the transmission distance is too great. Hence, a novel MIN model called the deterioration-effect acyclic MIN (AMINde) is proposed to meet real-world problems in which the intensity of information decreases by a given amount and transmits to a limited number of nodes. In addition, to counteractsome of the deterioration effect, a novel boost node is introduced toincreaseinformation temporarily. A very straightforward and easily programmed algorithm derived from the universal generating function method (UGFM) is used to evaluate the AMINde reliability, which is defined as the probability that information can be received by the target node through the AMINde. The computational complexity of the proposed algorithm is also analyzed. Finally, an example is provided to illustrate how the reliability of the AMINde is calculated using the proposed algorithm.

Suggested Citation

  • Yeh, Wei-Chang, 2017. "Evaluation of the one-to-all-target-subsets reliability of a novel deterioration-effect acyclic multi-state information network," Reliability Engineering and System Safety, Elsevier, vol. 166(C), pages 132-137.
    • Handle: RePEc:eee:reensy:v:166:y:2017:i:c:p:132-137
    DOI: 10.1016/j.ress.2016.11.012
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Xiu-Zhen Xu & Yi-Feng Niu & Qing Li, 2019. "Efficient Enumeration of - Minimal Paths in Reliability Evaluation of Multistate Networks," Complexity, Hindawi, vol. 2019, pages 1-10, March.
    2. Yeh, Wei-Chang, 2020. "A new method for verifying d-MC candidates," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    3. Niu, Yi-Feng & Wan, Xiao-Yu & Xu, Xiu-Zhen & Ding, Dong, 2020. "Finding all multi-state minimal paths of a multi-state flow network via feasible circulations," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    4. Hao, Zhifeng & Yeh, Wei-Chang & Zuo, Ming & Wang, Jing, 2020. "Multi-distribution multi-commodity multistate flow network model and its reliability evaluation algorithm," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    5. Niu, Yi-Feng, 2021. "Performance measure of a multi-state flow network under reliability and maintenance cost considerations," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    6. Hao, Zhifeng & Yeh, Wei-Chang & Tan, Shi-Yi, 2021. "One-batch preempt deterioration-effect multi-state multi-rework network reliability problem and algorithms," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    7. Hao, Zhifeng & Yeh, Wei-Chang & Liu, Zhenyao & Forghani-elahabad, Majid, 2020. "General multi-state rework network and reliability algorithm," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    8. 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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