Stochastic Discrete Event Systems: Modeling, Evaluation, Applications - Tapa blanda

Acerca del autor

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.

De la contraportada

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.