Includes exercises and bibliographical notes at chapter ends, bibliographical references (pages 589-601), and index.

Part I. Basic concepts ; Performance measures and evaluation techniques -- Measurement techniques -- Experiment design and data analysis -- Fundamentals of queuing models -- Elementary stochastic analysis -- Product-form queuing network models -- Basic algorithms for product-form networks -- Aggregation and approximate modeling -- Part II. Advanced topics ; Advanced stochastic analysis -- Algorithms for networks with specialized features -- Bounds on performance -- Petri net-based performance modeling -- Selected applications -- Part III. Appendices ; A. Notation -- B. Introduction to probability theory -- C. A suggested modeling project -- D. Performance tuning using Solver -- E. Selected tables.

This book provides an up-to-date treatment of the fundamental techniques and algorithms of computer system performance modeling and evaluation. The field of performance evaluation has progressed rapidly in the past ten years, only now beginning to approach maturity, and consequently developments are covered in technical journals. Analytic performance modeling is peculiar with regard to its mathematical content, which is rarely advanced, but the proliferation of mathematical symbols and nonstandard notation often makes it look unapproachable. Performance evaluation includes measurement, simulation, and analytic modeling to include model calibration and data analysis. The selection of the material has been guided by these goals and problems.