Abstract
The time required to find the exact solution of a product-form queueing network model of a computer system can be high. Faster and cheaper methods of solution, such as approximations, are natural alternatives. However, the errors incurred when using an approximation technique should be bounded. Several recent techniques have been developed which provide solution bounds. These bounding techniques have the added benefit that the bounds can be made tighter if extra computational effort is expended. Thus, a smooth tradeoff of cost and accuracy is available. These techniques are based upon mean value analysis. In this paper a new bounding technique based upon the convolution algorithm is presented. It provides a continuous range of cost versus accuracy tradeoffs for both upper and lower bounds. The bounds produced by the technique converge to the exact solution as the computational effort approaches that of convolution. Also, the technique may be used to improve any existing set of bounds.
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