Art of Computer Systems Performance Analysis

RAJ JAIN is a Senior Consulting Engineer in the Distributed Systems Architecture and Performance Group at Digital Equipment Corporation. With over sixteen years of experience in the field of computer systems performance, he is currently responsible for analyzing various design alternatives for DEC's networking architecture. He received the Ph.D. degree from Harvard and has taught courses on performance at Massachusetts Institute of Technology. "Dr. Jain is a Fellow of the IEEE and is listed in Who's Who in the Computer Industry, 1989."

"At last, a welcome and needed text for computer professionals who require practical, ready-to-apply techniques for performance analysis. Highly recommended!" -Dr. Leonard Kleinrock University of California, Los Angeles "An entirely refreshing text which has just the right mixture of theory and real world practice. The book is ideal for both classroom instruction and self-study." -Dr. Raymond L. Pickholtz President, IEEE Communications Society "An extraordinarily comprehensive treatment of both theoretical and practical issues." -Dr. Jeffrey P. Buzen Internationally recognized performance analysis expert ". it is the most thorough book available to date" -Dr. Erol Gelenbe Universite Rene Descartes, Paris ". an extraordinary book. A worthy addition to the bookshelf of any practicing computer or communications engineer" -Dr. Vinton G. Cerf Chairman, ACM SIGCOMM "This is an unusual object, a textbook that one wants to sit down and peruse. The prose is clear and fluent, but more important, it is witty." -Allison Mankin The Mitre Washington Networking Center Newsletter

• Partial table of contents: AN OVERVIEW OF PERFORMANCE EVALUATION. Common Mistakes and How to Avoid Them. Selection of Techniques and Metrics. MEASUREMENT TECHNIQUES AND TOOLS. Types of Workloads. Workload Characterization Techniques. Monitors. Ratio Games. PROBABILITY THEORY AND STATISTICS. Summarizing Measured Data. Simple Linear Regression Models. Other Regression Models. EXPERIMENTAL DESIGN AND ANALYSIS. One-Factor Experiments. Two-Factor Full Factorial Design without Replications. Two-Factor Full Factorial Design with Replications. SIMULATION. Analysis of Simulation Results. Testing Random-Number Generators. Commonly Used Distributions. QUEUEING MODELS. Analysis of a Single Queue. Operational Laws. Convolution Algorithm. Appendix. Solutions to Selected Exercises. References. Author Index. Subject Index.