Markov Chains and Dependability Theory
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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 specialized 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 life-time, repair duration, availability, reliability and risk are important.Read more
- Provides up-to-date coverage of topics related to space state partitions and dependability metrics, as opposed to classical books which are limited to reliability aspects
- Covers the mathematical foundations of dependability and combined performance and dependability analysis
- Includes two self-contained chapters on Markov chains and a wide range of topics from theoretical problems to practical issues
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- Date Published: May 2014
- format: Adobe eBook Reader
- isbn: 9781139989534
- contains: 32 b/w illus. 24 tables
- availability: This ISBN is for an eBook version which is distributed on our behalf by a third party.
Table of Contents
2. Discrete time Markov chains
3. Continuous time Markov chains
4. State aggregation of Markov chains
5. Sojourn times in subsets of states
6. Occupation times
8. Stationary detection
9. Simulation of dependability models
10. Bounding techniques.
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