Queuing Networks--Exact Computational Algorithms: A Unified Theory Based on Decomposition and Aggregation

In the last fifteen years queueing networks have come into widespread use as models of computer systems and computer-communication networks. Their popularity derives primarily from the particular class of product form queueing networks that make available a large variety of modeling features and for which a number of efficient computational algorithms have been developed. This book provides the first unified and current view of the principal exact computational algorithms that have been developed to date for the analysis of product form queueing networks.

The authors cover both recent important advances such as the Recursion by Chain Algorithm (RECAL), Mean Value Analysis by Chain (MVAC), and the Distribution Analysis by Chain (DAC) algorithms, and established algorithms such as the Convolution Algorithm and Mean Value Analysis within the context of a unified theory based on the notions of decomposition and aggregation.

The theory gives a useful general constructive methodology for the development of computational algorithms and unifies the seemingly unconnected developments that have taken place. It also provides intuitive insight into the problem of constructing efficient algorithms and suggests the existence of other even more efficient algorithms that might be developed.

Adrian E. Conway is Senior Member of Technical Staff at GTE Laboratories Incorporated. Nicolas D. Georganas is Dean of the Faculty of Engineering at the University of Ottawa. Queueing Networks: Exact Computational Algorithms is included in the Computer Systems series, edited by Herb Schwetman.