A Validated Distributed System Performance Model
Performance '83 Proceedings of the 9th International Symposium on Computer Performance Modelling, Measurement and Evaluation
Multiple class memory constrained queueing networks
SIGMETRICS '82 Proceedings of the 1982 ACM SIGMETRICS conference on Measurement and modeling of computer systems
Fast approximate solution of multiprogramming models
SIGMETRICS '82 Proceedings of the 1982 ACM SIGMETRICS conference on Measurement and modeling of computer systems
A Clustering Approximation Technique for Queueing Network Models with a Large Number of Chains
IEEE Transactions on Computers
On the applicability of using multiprogramming level distributions
SIGMETRICS '85 Proceedings of the 1985 ACM SIGMETRICS conference on Measurement and modeling of computer systems
Analysis of Queueing Network Models with population size constraints and delayed blocked customers
SIGMETRICS '84 Proceedings of the 1984 ACM SIGMETRICS conference on Measurement and modeling of computer systems
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There are two basic representations of workload populations in load independent, separable queueing network models. These correspond to the notions of open and closed classes, an open class being one in which customers may arrive and depart the model, and a closed class being one in which the number of customers is fixed. This paper examines the effect on mean system performance measures of the workload representation chosen. Open and closed representations are compared under the equivalency constraints that they result in identical system throughput or mean system population level for the class being considered. It is shown formally for a limited class of networks that the open representation results in larger system response times than equivalent closed representations, and that one of the closed representations results in the smallest system response time of those considered. Extensive numerical results show for a more general class of models that there is a strict ordering (in terms of system response time) of the natural class representations considered. These results can be used in at least two ways. One is to guide the initial representation of computer system workloads in performance models. The other application is as a component of approximate analysis techniques for queueing models that decompose individual networks into multiple submodels, each of which is then solved in isolation. Here the goal is to represent customer classes in each submodel in a way that is convenient computationally, and that results in performance measures closely matching those observed in the full network. It is this latter application that we assume in this paper. An example of the application of our results to an existing approximation technique is given.