a model for workload characterization
A major problem in the evaluation of the performance of a multiprogrammed, time-sharing computer system is the development of an accurate description of its normal workload. In evaluating the performance of a computer system, the validity of the analyzed data can be no better than the degree to which the test workload represents the real workload. The paper reports on the research aimed at developing a probabilistic model of the workload which can be validated with respect to the real workload and is easy to use in a performance evaluation study. In this characterization, the workload is modelled as a mixture of a number of classes. The distribution of load in each class is described by a unimodal distribution of various resource loadings. Therefore, the workload is modelled as a mixture distribution in an appropriately chosen n-dimensional space. By increasing the number of classes the mixture distribution model allows us to model a complex multimodal distribution. At present, we are studying the workloads on the Univac 1108/1106 computer at the Computer Science Center of the University of Maryland. This installation is used for educational and research computing by the students and faculty at the University and handles a workload of several thousand processes during a typical day. Some results of this study are presented.
model workload workload characterization characterization evaluation performance computation systems developer normalization validation data test paper research probabilistic models use performance evaluation class distributed resource space complexity multimodality computer science install education student faculty process timing sharing