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Algorithms for minimizing weighted flow time
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Source Annual ACM Symposium on Theory of Computing archive
Proceedings of the thirty-third annual ACM symposium on Theory of computing table of contents
Hersonissos, Greece
Pages: 84 - 93  
Year of Publication: 2001
ISBN:1-58113-349-9
Authors
Chandra Chekuri  Bell Labs, 600 Mountain Ave, Murray Hill, NJ
Sanjeev Khanna  Dept. of CIS, University of Pennsylvania, Philadelphia, PA
An Zhu  Dept. of Computer Science, Stanford University, Stanford, CA
Sponsor
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 8,   Downloads (12 Months): 43,   Citation Count: 23
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ABSTRACT

We study the problem of minimizing weighted flow time on a single machine in the preemptive setting. We present an O(\log^2 P)-competitive semi-online algorithm where P is the ratio of the maximum and minimum processing times of jobs in the system. In the offline setting we show that a (2+\eps)-approximation is achievable in quasi-polynomial time. These are the first non-trivial results for the weighted versions of minimizing flow time. For multiple machines we show that no competitive randomized online algorithm exists for weighted flow time. We also present an improved online algorithm for minimizing total stretch (a special case of weighted flow time) on multiple machines.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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C. Chekuri and S. Khanna. Approximation schemes for preemptive weighted ow time. Manuscript, 2001.
 
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B. Kalyanasundaram and K. Pruhs. Speed is equivalent toclairvoyance. In Proceedings of the 36th Annual Symposium on Foundations of Computer Science, pages 115-124, 1995.
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J. K. Lenstra, A. H. G. Rinnooy Kan, and P. Brucker. Complexity ofmachine scheduling problems. Annals of Discrete Mathematics, 1:343-362, 1977.
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CITED BY  23

Collaborative Colleagues:
Chandra Chekuri: colleagues
Sanjeev Khanna: colleagues
An Zhu: colleagues