Queuing Networks and Markov Chains: Modeling and Performance Evaluation With Computer Science Applications

The first book to address computer performance evaluation from the perspective of queueing theory and Markov chains.

Queueing Networks and Markov Chains provides comprehensive coverage of the theory and application of computer performance evaluation based on queueing networks and Markov chains. Progressing from basic concepts to more complex topics, this book offers a clear and concise treatment of the state of the art in this important field.

Essential reading for system designers and researchers as well as graduate students taking courses in computer performance analysis, this book contains:
* A basic introduction to probability theory
* An explanation of the characteristics of different types of Markov chains
* Simple examples of all algorithms
* Transient and steady-state solution algorithms
* Well-known solution techniques for queueing systems and networks
* A broad range of application studies-from client-server systems to ATM networks
* Hundreds of illustrations, exercises, and more.

As computer and communications systems become more complex, system designers are increasingly called upon to locate information bottlenecks or create optimal systems for specific needs. In a short period of time, performance modeling techniques have become an important tool for this type of work-and indispensable to anyone dealing with questions of reliability and quality in operations, communications, and manufacturing. Queueing Networks and Markov Chains is an up-to-date, application-driven guide to computer performance analysis. It is the only book currently available that combines theory and applications of computer performance evaluation with queueing networks and Markov chains, and offers an abundance of performance-evaluation algorithms, applications, and case studies.

Entirely self-contained, Queueing Networks and Markov Chains introduces probability theory and clearly explains basic concepts before moving to advanced topics. It examines Markov chains and solution algorithms, building on results obtained in the Markov chain chapter to derive the basic relationship for queueing networks. Modeling and evaluation are discussed in the context of a variety of systems-including client-server systems, pulling systems, operating systems, ATM networks, and more. The authors present new queueing and optimization techniques for queueing networks, as well as multilevel methods for the solution of Markovian systems of equations. They show how to find an appropriate solution algorithm for a given problem using the queueing network tool PEPSY and how to determine benefits or limitations of queueing networks and Markov chains using the Markov analyzer MOSES.

In addition, the book provides numerous illustrations and exercises, gives simple examples for all algorithms, and compares various methods for their computation time, storage requirement, accuracy, and applicability.

Timely and comprehensive, Queueing Networks and Markov Chains is essential for practitioners and researchers working in this rapidly evolving field, as well as for graduate students in computer science departments.

Dr. GUNTER BOLCH is Academic Director of the Department of Computer Science at the University of Erlangen in Germany. He is a coauthor of MOSEL, a new and powerful specification language based on Markov chains. Dr. Bolch has published three books and dozens of articles on performance evaluation, computer systems analysis, and process automation. His books are widely regarded as standard references in the field.

Dipl.-Inf. STEFAN GREINER is a researcher in the Department of Computer Science at the University of Erlangen and Daimler Benz AG in Stuttgart, Germany. A coauthor of MOSEL, he has published a number of articles on performance modeling and is the recipient of a best-paper award at the ESS94 conference.

Dr. HERMANN DE MEER is an assistant professor in the Department of Computer Science at the University of Hamburg in Germany. He has written more than 30 articles on performance modeling, optimization, and high-speed networks with multimedia applications.

SHOR S. TRIVEDI is a professor in the Department of Electrical and Computer Engineering and the Department of Computer Science at Duke University. The author of the bestselling textbook, Probability and Statistics with Reliability, Queueing and Computer Science Applications and coauthor of Performance and Reliability Analysis of Computer Systems, Professor Trivedi has also published more than 200 articles.