Reversibility and Stochastic Networks

Examines the behavior in equilibrium of vector stochastic processes or stochastic networks, considering a wide range of applications by discussing stochastic models that arise in fields such as operational research, biology, and polymer science.

**Tag(s):**
Operations Research

**Publication date**: 12 Dec 1979

**ISBN-10**:
0471276014

**ISBN-13**:
9780471276012

**Paperback**:
238 pages

**Views**: 11,810

Reversibility and Stochastic Networks

Examines the behavior in equilibrium of vector stochastic processes or stochastic networks, considering a wide range of applications by discussing stochastic models that arise in fields such as operational research, biology, and polymer science.

Terms and Conditions:

Book Excerpts:

The main topic of this book is the study of the behaviour in equilibrium of vector stochastic processes, or stochastic networks. Such processes have a wide range of applications: to give some examples, the components of the vector may represent queue sizes in a queueing network, gene frequencies in a population, or the condition of fruit trees in an orchard. When a stochastic network is reversible its analysis is greatly simplified, and the first chapter is devoted to a discussion of the concept of reversibility. Two themes emerge from the remainder of the book: first, the various uses of reversibility, in the study of the output from a queue, the flow of current in a conductor, the age of an allele, or the equilibrium distribution of a polymerization process; second, the extent to which the assumption of reversibility can be relaxed without destroying the associated tractability.

Prerequisites:

The main prerequisite is an understanding of Markov processes at about the level of Feller's Introduction to Probability Theory and Its Applications, Volume I. In Section 1.1 the necessary material is very briefly reviewed, primarily to establish terminology and notation.

Frank P. Kelly wrote:The book (published by Wiley, Chichester, 1979, reprinted 1987, 1994) is now out of print, and the copyright has reverted to the author. Permission is granted for the material to be freely downloaded and distributed for instructional non-profit purposes.

Book Excerpts:

The main topic of this book is the study of the behaviour in equilibrium of vector stochastic processes, or stochastic networks. Such processes have a wide range of applications: to give some examples, the components of the vector may represent queue sizes in a queueing network, gene frequencies in a population, or the condition of fruit trees in an orchard. When a stochastic network is reversible its analysis is greatly simplified, and the first chapter is devoted to a discussion of the concept of reversibility. Two themes emerge from the remainder of the book: first, the various uses of reversibility, in the study of the output from a queue, the flow of current in a conductor, the age of an allele, or the equilibrium distribution of a polymerization process; second, the extent to which the assumption of reversibility can be relaxed without destroying the associated tractability.

Prerequisites:

The main prerequisite is an understanding of Markov processes at about the level of Feller's Introduction to Probability Theory and Its Applications, Volume I. In Section 1.1 the necessary material is very briefly reviewed, primarily to establish terminology and notation.

Tweet

About The Author(s)

No information is available for this author.

Book Categories

Computer Science
Introduction to Computer Science
Introduction to Computer Programming
Algorithms and Data Structures
Artificial Intelligence
Computer Vision
Machine Learning
Neural Networks
Game Development and Multimedia
Data Communication and Networks
Coding Theory
Computer Security
Information Security
Cryptography
Information Theory
Computer Organization and Architecture
Operating Systems
Image Processing
Parallel Computing
Concurrent Programming
Relational Database
Document-oriented Database
Data Mining
Big Data
Data Science
Digital Libraries
Compiler Design and Construction
Functional Programming
Logic Programming
Object Oriented Programming
Formal Methods
Software Engineering
Agile Software Development
Information Systems
Geographic Information System (GIS)

Mathematics
Mathematics
Algebra
Abstract Algebra
Linear Algebra
Number Theory
Numerical Methods
Precalculus
Calculus
Differential Equations
Category Theory
Proofs
Discrete Mathematics
Theory of Computation
Graph Theory
Real Analysis
Complex Analysis
Probability
Statistics
Game Theory
Queueing Theory
Operations Research
Computer Aided Mathematics

Supporting Fields
Web Design and Development
Mobile App Design and Development
System Administration
Cloud Computing
Electric Circuits
Embedded System
Signal Processing
Integration and Automation
Network Science
Project Management

Operating System
Programming/Scripting
Ada
Assembly
C / C++
Common Lisp
Forth
Java
JavaScript
Lua
Microsoft .NET
Rexx
Perl
PHP
Python
R
Rebol
Ruby
Scheme
Tcl/Tk

Miscellaneous
Sponsors