Reversibility and Stochastic Networks

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.

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.

This classic in stochastic network modelling is back in print for a new generation. The author's clear and easy-to-read style makes it enjoyable reading for anyone interested in stochastic processes. Elementary probability is the only prerequisite and exercises are interspersed throughout.

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