Synopses & Reviews
An accessible introduction to probability, stochastic processes, and statistics for computer science and engineering applications
This updated and revised edition of the popular classic relates fundamental concepts in probability and statistics to the computer sciences and engineering. The author uses Markov chains and other statistical tools to illustrate processes in reliability of computer systems and networks, fault tolerance, and performance.
This edition features an entirely new section on stochastic Petri nets?as well as new sections on system availability modeling, wireless system modeling, numerical solution techniques for Markov chains, and software reliability modeling, among other subjects. Extensive revisions take new developments in solution techniques and applications into account and bring this work totally up to date. It includes more than 200 worked examples and self-study exercises for each section.
Probability and Statistics with Reliability, Queuing and Computer Science Applications, Second Edition offers a comprehensive introduction to probability, stochastic processes, and statistics for students of computer science, electrical and computer engineering, and applied mathematics. Its wealth of practical examples and up-to-date information makes it an excellent resource for practitioners as well.
Review
"I highly recommend this book for academics for use as a textbook and for researchers and professionals in the field as a useful reference.” (
Interfaces, September/ October 2004)
"This introduction...uses Markov chains and other statistical tools to illustrate process in reliability of computer systems, fault tolerance, and performance." (SciTech Book News, Vol. 26, No. 2, June 2002)
Probability and Statistics with Reliability, Queuing and Computer Science Applications 2e
"...an excellent self-contained book…I recommend the book to beginners and veterans in the field..." (Computer Journal, Vol.45, No.6, 2002)
"This book is a tour de force of clear, virtually error-free exposition of probability as it is applied in a host of up-to-date contexts.... It will richly reward the...reader.... Read this book cover to cover. It’s worth the effort." (Technometrics, Vol. 45, No. 1, February 2003)
Synopsis
This book relates fundamental concepts in probability and statistics to the computer sciences. The author uses Markov chains and other statistical tools to illustrate processes such as reliability of computer systems and fault tolerance. This new, revised edition includes a new chapter on Stochastic Petri Nets.
About the Author
KISHOR S. TRIVEDI, PhD, is the Hudson Professor of Electrical and Computer Engineering at Duke University, Durham, North Carolina. His research interests include computer networks, fault-tolerant computing, modeling tools, and reliability modeling.
Table of Contents
Introduction.
Discrete Random Variables.
Continuous Random Variables.
Expectation.
Conditional Distribution and Expectation.
Stochastic Processes.
Discrete-Time Markov Chains.
Continuous-Time Markov Chains.
Networks of Queues.
Statistical Inference.
Regression and Analysis of Variance.
Appendix A: Bibliography.
Appendix B: Properties of Distributions.
Appendix C: Statistical Tables.
Appendix D: Laplace Transforms.
Appendix E: Program Performance Analysis.