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- W1967051149 abstract "Clustering techniques are widely recommended tools for workload classification. The k-means algorithm is widely accepted as the standard technique of detecting workload classes automatically from measurement data. This paper examines validity of the obtained workload classes, when the current system and workload is analyzed by a queueing network model and mean value analysis. Our results, based on one week's accounting data of a VAX 8600, indicate that the results of queueing network analysis are not stable when the classes of workload are constructed through the k-means algorithm. Therefore, we cannot recommended that the most widely used clustering technique should be used in any workload characterization study without careful validation." @default.
- W1967051149 created "2016-06-24" @default.
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- W1967051149 date "1993-05-01" @default.
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- W1967051149 title "Cluster analysis and workload classification" @default.
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- W1967051149 doi "https://doi.org/10.1145/155775.155781" @default.
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