Overview
Part of the book series: International Series in Operations Research & Management Science (ISOR, volume 11)
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Table of contents (8 chapters)
Keywords
About this book
The book consistently takes the point of view of focusing on one sample path of a stochastic process. Hence, it is devoted to providing pure sample-path arguments. With this approach it is possible to separate the issue of the validity of a relationship from issues of existence of limits and/or construction of stationary framework. Generally, in many cases of interest in queueing theory, relations hold, assuming limits exist, and the proofs are elementary and intuitive. In other cases, proofs of the existence of limits will require the heavy machinery of stochastic processes. The authors feel that sample-path analysis can be best used to provide general results that are independent of stochastic assumptions, complemented by use of probabilistic arguments to carry out a more detailed analysis. This book focuses on the first part of the picture. It does however, provide numerous examples that invoke stochastic assumptions, which typically are presented at the ends of the chapters.
Reviews
Short Book Reviews, 19:2 (1999)
`... this monograph is well written, fairly comprehensive and a welcome addition to the growing number of books on queuing theory. It is of interest to a wide audience of operations researchers, applied probabilists and engineers.'
Mathematical reviews, 2002d
Authors and Affiliations
Bibliographic Information
Book Title: Sample-Path Analysis of Queueing Systems
Authors: Muhammad El-Taha, Shaler Stidham
Series Title: International Series in Operations Research & Management Science
DOI: https://doi.org/10.1007/978-1-4615-5721-0
Publisher: Springer New York, NY
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eBook Packages: Springer Book Archive
Copyright Information: Springer Science+Business Media New York 1999
Hardcover ISBN: 978-0-7923-8210-2Published: 31 August 1998
Softcover ISBN: 978-1-4613-7620-0Published: 08 October 2012
eBook ISBN: 978-1-4615-5721-0Published: 06 December 2012
Series ISSN: 0884-8289
Series E-ISSN: 2214-7934
Edition Number: 1
Number of Pages: XIII, 295
Topics: Operations Research/Decision Theory, Probability Theory and Stochastic Processes, Optimization