Approximate Methods for Analyzing Queueing Network Models of Computing Systems

The two primary issues in choosing a computing system model are credibility of the model and cost of developing and solving the model Credibility is determined by 1) the experience and biases of the persons using the model, 2) the extent to which the model represents system features, and 3) the accuracy of the solution technique. Queueing network models are widely used because they have proven effective and are inexpensive to solve. However, most queueing network models make strong assumptions to assure an exact numerical solution. When such assumptions severely affect credibility, simulation or other approaches are used, in spite of their relatively high cost. It is the contention of this paper that queueing network models with credible assumptions can be solved approximately to provide credible performance estimates at low cost This contention is supported by examples of approximate solutions of queueing network models. Two major approaches to approximate solution, aggregation (decomposition) and diffusion, are discussed