Overview

Originally published in 1995, Large Deviations for Performance Analysis consists of two synergistic parts. The first half develops the theory of large deviations from the beginning, through recent results on the theory for processes with boundaries, keeping to a very narrow path: continuous-time, discrete-state processes. By developing only what is needed for the applications, the theory is kept to a manageable level, both in terms of length and in terms of difficulty. Within its scope, the treatment is detailed, comprehensive and self-contained. As the book shows, there are sufficiently many interesting applications of jump Markov processes to warrant a special treatment. The second half is a collection of applications developed at Bell Laboratories. The applications cover large areas of the theory of communication networks: circuit switched transmission, packet transmission, multiple access channels, and the M/M/1 queue. Aspects of parallel computation are covered as well including, basics of job allocation, rollback-based parallel simulation, assorted priority queueing models that might be used in performance models of various computer architectures, and asymptotic coupling of processors. These applications are thoroughly analysed using the tools developed in the first half of the book.

Full Product Details

Author:   Alan Weiss ,  Adam Shwartz
Publisher:   Taylor & Francis Ltd
Imprint:   Routledge
Weight:   0.970kg
ISBN:  

9781138318106

ISBN 10:   1138318108
Pages:   556
Publication Date:   31 March 2021
Audience:   College/higher education ,  Professional and scholarly ,  Tertiary & Higher Education ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

What this Book Is, and What It Is Not 1. Large Deviations of Random Variables 2. General Principles 3. Random Walks, Branching Processes 4. Poisson and Related Processes 5. Large Deviations for Processes 6. Freidlin-Wentzell Theory 7. Applications and Extensions 8. Boundary Theory Applications 9. Allocating Independent Subtasks 10. Parallel Algorithms: Rollback 11. The M/M/1 Queue 12. Erlang’s Mode 13. The Anick-Mitra-Sondhi Model 14. Aloha 15. Priority Queues 16. The Flatto-Hahn-Wright model A. Analysis and Probability B. Discrete-Space Markov Processes C. Calculus of Variations D. Large Deviations Techniques References Index

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