Ebook: Stochastic Discrete Event Systems: Modeling, Evaluation, Applications

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.

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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.

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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.

Content:
Front Matter....Pages I-XV
Introduction....Pages 1-14
A Unified Description for Stochastic Discrete Event Systems....Pages 17-43
Stochastic Timed Automata....Pages 45-63
Queuing Models....Pages 65-78
Simple Petri Nets....Pages 79-98
Colored Petri Nets....Pages 99-124
Standard Quantitative Evaluation Methods for SDES....Pages 127-156
An Iterative Approximation Method....Pages 157-168
Efficient Simulation of SDES Models....Pages 169-222
System Optimization....Pages 223-243
Model-Based Direct Control....Pages 244-252
Software Tool Support....Pages 253-266
Optimization of a Manufacturing System....Pages 269-285
Communication System Performability Evaluation....Pages 287-305
Supply Chain Performance Evaluation and Design....Pages 307-323
Model-Based Design and Control of a Production Cell....Pages 325-340
Summary and Outlook....Pages 341-343
Back Matter....Pages 345-391

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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.

Content:
Front Matter....Pages I-XV
Introduction....Pages 1-14
A Unified Description for Stochastic Discrete Event Systems....Pages 17-43
Stochastic Timed Automata....Pages 45-63
Queuing Models....Pages 65-78
Simple Petri Nets....Pages 79-98
Colored Petri Nets....Pages 99-124
Standard Quantitative Evaluation Methods for SDES....Pages 127-156
An Iterative Approximation Method....Pages 157-168
Efficient Simulation of SDES Models....Pages 169-222
System Optimization....Pages 223-243
Model-Based Direct Control....Pages 244-252
Software Tool Support....Pages 253-266
Optimization of a Manufacturing System....Pages 269-285
Communication System Performability Evaluation....Pages 287-305
Supply Chain Performance Evaluation and Design....Pages 307-323
Model-Based Design and Control of a Production Cell....Pages 325-340
Summary and Outlook....Pages 341-343
Back Matter....Pages 345-391
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