Closed queuing network models representing computer systems with programs that have variation in concurrency level are discussed. For such models computation by existing approximation methods results in an explosion in the size of the state transition matrix. An innovative approximate analytic method based on the overall average concurrent level of programs is proposed. It is found that use of the proposed method considerably reduces the number of states and thus requires less memory. This average concurrency method is a fast algorithm for predicting performance levels of computer systems. Various examples were studied and the accuracy of the method was confirmed determined by comparison to the results of more exact simulations.
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