Network Reliability Modeling Based on a Geometric Counting Process

Author:

Zarezadeh Somayeh,Ashrafi Somayeh,Asadi Majid

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.

Funder

IPM

Publisher

MDPI AG

Subject

General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

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3. Marginal and joint failure importance for K-terminal network edges under counting process;Reliability Engineering & System Safety;2022-07

4. Reliability Simulation Evaluation Technology of Network System with Hardware and Software Combined;2022 Asia Conference on Algorithms, Computing and Machine Learning (CACML);2022-03

5. Discrete time dynamic reliability modeling for systems with multistate components;Reliability Engineering & System Safety;2021-05

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