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An examination of strategies for estimating capacity to share among private workstations

An examination of strategies for estimating capacity to share among private workstations The effective management of a cluster of private workstations requires an examination of the characteristics of the usage patterns of workstations. This paper analyzes workstation usage patterns in order to understand opportunities for exploiting idle capacity. Our study is based on traces of user workstation activity in a university environment. It identifies two areas where enhancements can be made. One identified area is the ability of a manager of the shared capacity of a workstation cluster to schedule jobs with deadline constraints. This opportunity is the result of an ability to make good predictions of the time-varying amount of capacity that is available for sharing. A simple prediction strategy is developed which is shown to have only a small amount of error. For the second area of enhancement, we show that it is feasible to allocate partitions of workstations for specific periods. This aids those users who on occasions need exclusive access to several machines. We examine the profile of periods during which exclusive access to partitions can be given, the rate that owners preempt users of partitions, and the distribution of inter-preemption intervals. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM SIGSMALL/PC Notes Association for Computing Machinery

An examination of strategies for estimating capacity to share among private workstations

Mutka, Matt W.
ACM SIGSMALL/PC Notes , Volume 18 (1-2) – Mar 1, 1992
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Publisher
Association for Computing Machinery
Copyright
Copyright © 1992 by ACM Inc.
ISSN
0893-2875
DOI
10.1145/134307.134334
Publisher site
See Article on Publisher Site

Abstract

The effective management of a cluster of private workstations requires an examination of the characteristics of the usage patterns of workstations. This paper analyzes workstation usage patterns in order to understand opportunities for exploiting idle capacity. Our study is based on traces of user workstation activity in a university environment. It identifies two areas where enhancements can be made. One identified area is the ability of a manager of the shared capacity of a workstation cluster to schedule jobs with deadline constraints. This opportunity is the result of an ability to make good predictions of the time-varying amount of capacity that is available for sharing. A simple prediction strategy is developed which is shown to have only a small amount of error. For the second area of enhancement, we show that it is feasible to allocate partitions of workstations for specific periods. This aids those users who on occasions need exclusive access to several machines. We examine the profile of periods during which exclusive access to partitions can be given, the rate that owners preempt users of partitions, and the distribution of inter-preemption intervals.

Journal

ACM SIGSMALL/PC Notes – Association for Computing Machinery

Published: Mar 1, 1992

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