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Art of Computer Systems Performance Analysis: Techniques for Experimental Design, Measurement, Simulation and Modeling
Art of Computer Systems Performance Analysis: Techniques for Experimental Design, Measurement, Simulation and Modeling
Author: Jain, Raj
Edition/Copyright: 1991
ISBN: 0-471-50336-3
Publisher: John Wiley & Sons, Inc.
Type: Print On Demand
Used Print:  $86.25
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Author Bio
Summary
Table of Contents
 
  Author Bio

Jain, Raj : Digital Equipment Company

About the author 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.

 
  Summary

Based on the author's experience in industry, focuses on simple, straightforward techniques to solve everyday problems in systems design and analysis. Stressing both systems- and analysis-oriented approaches, it provides basic modeling, simulation and analysis background to systems analysts so that they will understand performance terminology, properly design performance experiments, use simple queueing and simulation models, and correctly interpret results. Covering a variety of systems, including networks, databases and distributed systems among others, emphasizes and comprehensively integrates all aspects of performance analysis. Also highlights experimental design techniques specifically intended to reduce analysis costs.

 
  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

 

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