Stochastic Discrete Event Systems: Modeling, Evaluation, Applications

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Springer Science & Business Media, 2008 M01 12 - 392 pages

Stochastic discrete-event systems (SDES) capture the randomness in choices due to activity delays and the probabilities of decisions.

This book delivers a comprehensive overview on modeling with a quantitative evaluation of SDES. It presents an abstract model class for SDES as a pivotal unifying result and details important model classes. The book also includes nontrivial examples to explain real-world applications of SDES.

 

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Contents

Contents
1
Applications
8
Stochastic Timed Automata
45
G Ciardo M Forno P Grieco and A Miner Comparing implicit represen
60
Queuing Models 65
64
G Ciardo R German and C Lindemann A characterization of the stochas
67
J M Colom and M Silva Convex geometry and semiflows in PT nets
73
Simple Petri Nets
79
System Optimization
223
ModelBased Direct Control 245
244
Software Tool Support
253
13
269
A L Reibman and K S Trivedi Transient analysis of cumulative measures
278
Petri nets for the design and operation of manufacturing systems
292
Summary and Outlook
341
List of Algorithms 357
356

Colored Petri Nets
99
7
127
An Iterative Approximation Method
157
Efficient Simulation of SDES Models
169

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About the author (2008)

Since fall 2006 Armin Zimmermann has held a deputy professorship for real-time systems and robotics at the faculty of electrical engineering and computer sciences of TU Berlin. He is the principal investigator of the research group Model-Based Evaluation of Discrete Real-Time Systems and coordinates the graduate college "Stochastic Modelling and Quantitative Analysis of Complex Systems in Engineering". Prior to that, he was research fellow from 1995 to 1999 and research assistant from 1999 to 2006 at TU Berlin. In 1997, he had received the Krone award, the Carl Ramsauer award, and the Chorafas Foundation award for his thesis on modelling and analysis of manufacturing systems with Petri nets.

His research interests include modelling, performance evaluation, optimization, and control of technical systems using discrete-event models as well as their tool support.

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