About this book
The behavior of many technical systems important in everyday life can be described using discrete states and state-changing events. Stochastic discrete-event systems (SDES) capture the randomness in choices and over time due to activity delays and the probabilities of decisions. The starting point for the evaluation of quantitative issues like performance and dependability is a formal description of the system of interest in a model.
Armin Zimmermann delivers a coherent and comprehensive overview on modeling with and quantitative evaluation of SDES. An abstract model class for SDES is presented as a pivotal unifying result. Several important model classes, including queuing networks, Petri nets and automata, are detailed together with their formal translation into this abstract model class. Standard and recently developed algorithms for the performance evaluation, optimization and control of SDES are presented in the context of the abstract model class. The necessary software tool support is also covered. The book is completed with nontrivial examples from areas like manufacturing control, performance of communication systems, and supply-chain management, highlighting the application of the techniques presented.
For researchers and graduate students this monograph summarizes the body of knowledge for modeling and evaluating SDES, while bringing it to a new abstraction level with the introduction of a new and unifying framework. In addition, the extensive reference list is an excellent starting point for further detailed reading and research.
- Book Title Stochastic Discrete Event Systems
- Book Subtitle Modeling, Evaluation, Applications
- DOI https://doi.org/10.1007/978-3-540-74173-2
- Copyright Information Springer Berlin Heidelberg 2008
- Publisher Name Springer, Berlin, Heidelberg
- eBook Packages Computer Science Computer Science (R0)
- Hardcover ISBN 978-3-540-74172-5
- Softcover ISBN 978-3-642-09350-0
- eBook ISBN 978-3-540-74173-2
- Edition Number 1
- Number of Pages XVI, 392
- Number of Illustrations 86 b/w illustrations, 0 illustrations in colour
Probability and Statistics in Computer Science
Probability Theory and Stochastic Processes
System Performance and Evaluation
Simulation and Modeling
Mathematical Modeling and Industrial Mathematics
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