Reversibility and Stochastic Networks

Erscheinungsjahr 2011
ISBN: 978-1-107-40115-0
Verlag: Cambridge University Press

Buch, Englisch, 238 Seiten, Format (B × H): 152 mm x 229 mm, Gewicht: 354 g

Reihe: Cambridge Mathematical Library

This classic in stochastic network modelling broke new ground when it was published in 1979, and it remains a superb introduction to reversibility and its applications. The book concerns behaviour in equilibrium of vector stochastic processes or stochastic networks. 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. The rest of the book focuses on the various applications of reversibility and the extent to which the assumption of reversibility can be relaxed without destroying the associated tractability. Now back in print for a new generation, this book makes enjoyable reading for anyone interested in stochastic processes thanks to the author's clear and easy-to-read style. Elementary probability is the only prerequisite and exercises are interspersed throughout.

Autoren/Hrsg.

Kelly, F. P.

Fachgebiete

• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung Verteilte Systeme (Netzwerke)
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
• Mathematik | Informatik Mathematik Stochastik Stochastische Prozesse
• Mathematik | Informatik EDV | Informatik Informatik Mathematik für Informatiker

Inhaltsverzeichnis

1. Markov processes and reversibility; 2. Migration processes; 3. Queueing networks; 4. Examples of queueing networks; 5. Electrical analogues; 6. Reversible migration processes; 7. Population genetics models; 8. Clustering processes; 9. Spatial processes; References; Symbol index; Subject index.

Über Autor(innen)

Kelly, F. P.
F. P. Kelly is Professor of the Mathematics of Systems in the Statistical Laboratory, University of Cambridge.

F. P. Kelly is Professor of the Mathematics of Systems in the Statistical Laboratory, University of Cambridge.