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.

This book constitutes the refereed proceedings of the 9th International Conference on Modeling Techniques and Tools for Computer Performance Evaluation, held in St. Malo, France, in June 1997.
The volume presents 17 revised full papers carefully selected by the program committee for the proceedings; also included is an extended abstract of an invited talk. The collection of papers presented represents state-of-the-art work in computer performance evaluation. Among the issues addressed are fully distributed systems, statistical multiplexing for high-speed networks, and implications of the concept of dependability.