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Network reliability evaluation
Author(s) -
Sahinoglu Mehmet,
Rice Benjamin
Publication year - 2010
Publication title -
wiley interdisciplinary reviews: computational statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.693
H-Index - 38
eISSN - 1939-0068
pISSN - 1939-5108
DOI - 10.1002/wics.81
Subject(s) - reliability (semiconductor) , reliability engineering , computer science , calculator , weibull distribution , reliability block diagram , monte carlo method , block (permutation group theory) , software quality , scalability , network topology , derating , simple (philosophy) , software , engineering , mathematics , statistics , software development , philosophy , database , voltage , operating system , power (physics) , geometry , epistemology , quantum mechanics , programming language , fault tree analysis , physics , electrical engineering
This article, beyond presenting a spectrum of network reliability methods studied in the past decades, describes a scalable innovative ‘overlap technique’ to tackle large complex networks' reliability evaluation difficulties, which cannot be handled by straightforward reliability block diagramming (RBD) techniques used for the simple parallel‐series topologies. Examples are shown on how to apply the overlap algorithm to compute the ingress‐egress reliability. Monte Carlo simulations demonstrate the methods discussed. (1) Static (time independent), (2) dynamic (time dependent) using a versatile Weibull distribution to represent the multiple stages of network components from infancy to useful life period and to wear‐out, and (3) multistate versions to include derated behavior beyond conventional working and nonworking states, are illustrated for calculating the directional source‐target (s‐t) reliability of complex networks by using the Java software ERBDC: Exact Reliability Block Diagramming Calculator . Copyright © 2010 John Wiley & Sons, Inc. This article is categorized under: Statistical and Graphical Methods of Data Analysis > Reliability, Survivability, and Quality Control