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Formalizing SMART scheduling

Published: 01 September 2004 Publication History

Abstract

It is well-known that policies which bias towards small job sizes or jobs with small remaining service times perform well with respect to mean response time and mean slowdown. This idea has been fundamental in many system implementations including the case of Web servers, where it has been shown that by giving priority to requests for small files, a Web server can significantly reduce mean response time and mean slowdown [1]. The heuristic has also been applied to other application areas; for example, scheduling in supercomputing centers.

References

[1]
M. Harchol-Balter, B. Schroeder, N. Bansal, and M. Agrawal. Implementation of SRPT scheduling in web servers. ACM Transactions on Computer Systems, 21(2), May 2003.
[2]
L. Kleinrock. Queueing Systems, volume II. Computer Applications. John Wiley & Sons, 1976.
[3]
L. E. Schrage. A proof of the optimality of the shortest remaining processing time discipline. Operations Research, 16:678--690, 1968.
[4]
L. E. Schrage and L. W. Miller. The queue M/G/I with the shortest remaining processing time discipline. Operations Research, 14:670--684, 1966.
[5]
A. Wierman and M. Harchol-Balter. Bounding the performance of SMART scheduling policies. Technical Report CMU-CS-03-199, Carnegie Mellon University, 2003.

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Published In

cover image ACM SIGMETRICS Performance Evaluation Review
ACM SIGMETRICS Performance Evaluation Review  Volume 32, Issue 2
September 2004
53 pages
ISSN:0163-5999
DOI:10.1145/1035334
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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 September 2004
Published in SIGMETRICS Volume 32, Issue 2

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