Markov Chains and Dependability Theory

Nonfiction, Science & Nature, Technology, Engineering, Mathematics
Cover of the book Markov Chains and Dependability Theory by Gerardo Rubino, Bruno Sericola, Cambridge University Press
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Author: Gerardo Rubino, Bruno Sericola ISBN: 9781139984911
Publisher: Cambridge University Press Publication: June 12, 2014
Imprint: Cambridge University Press Language: English
Author: Gerardo Rubino, Bruno Sericola
ISBN: 9781139984911
Publisher: Cambridge University Press
Publication: June 12, 2014
Imprint: Cambridge University Press
Language: English

Dependability metrics are omnipresent in every engineering field, from simple ones through to more complex measures combining performance and dependability aspects of systems. This book presents the mathematical basis of the analysis of these metrics in the most used framework, Markov models, describing both basic results and specialised techniques. The authors first present both discrete and continuous time Markov chains before focusing on dependability measures, which necessitate the study of Markov chains on a subset of states representing different user satisfaction levels for the modelled system. Topics covered include Markovian state lumping, analysis of sojourns on subset of states of Markov chains, analysis of most dependability metrics, fundamentals of performability analysis, and bounding and simulation techniques designed to evaluate dependability measures. The book is of interest to graduate students and researchers in all areas of engineering where the concepts of lifetime, repair duration, availability, reliability and risk are important.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Dependability metrics are omnipresent in every engineering field, from simple ones through to more complex measures combining performance and dependability aspects of systems. This book presents the mathematical basis of the analysis of these metrics in the most used framework, Markov models, describing both basic results and specialised techniques. The authors first present both discrete and continuous time Markov chains before focusing on dependability measures, which necessitate the study of Markov chains on a subset of states representing different user satisfaction levels for the modelled system. Topics covered include Markovian state lumping, analysis of sojourns on subset of states of Markov chains, analysis of most dependability metrics, fundamentals of performability analysis, and bounding and simulation techniques designed to evaluate dependability measures. The book is of interest to graduate students and researchers in all areas of engineering where the concepts of lifetime, repair duration, availability, reliability and risk are important.

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