Elsevier

Performance Evaluation

Volume 4, Issue 4, November 1984, Pages 275-284
Performance Evaluation

An analysis of an approximation algorithm for queueing networks

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Abstract

Queueing network models have proved to be useful aids in computer system performance prediction. Numerous approximation algorithms have been devised to allow queueing networks to be analyzed with a reduced computational expense. In particular, for separable queueing networks several popular iterative approximation algorithms are available.

One disadvantage of these algorithms has been the lack of results concerning their behavior, such as whether or not iteration convergence is guaranteed. This paper presents an analysis of an approximate MVA algorithm proposed by Schweitzer (1979). It is proved that the equations defining the algorithm have a unique solution when there is only a single customer class, and iteration initializations that yield monotonic convergence to this solution are exhibited. It is also proved that the solution is pessimistic relative to the exact queueing network solution.

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This research has been supported in part by Grants from the Natural Science and Engineering Research Council of Canada.

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