Queuing network models of modern computing systems must consider a large number of components (e.g., Web servers, DB servers, application servers, firewall, routers, networks) and hundreds of customers with very different resource requirements. The complexity of such models makes the application of exact solution techniques prohibitively expensive, motivating research on approximate methods. This paper proposes an interpolation-matching framework that allows a unified view of approximate solution techniques for closed product-form queuing networks. Depending upon the interpolating functional form and the matching populations selected, a large versatile family of new approximations can be generated. It is shown that all the known approximation strategies, including Linearizer, are instances of the interpolation-matching framework. Furthermore, a new approximation technique, based on a third-order polynomial, is obtained using the interpolation-matching framework. The new technique is shown to be more accurate than other known methods.
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