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A competitive algorithm for minimizing weighted flow time on unrelatedmachines with speed augmentation
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Annual ACM Symposium on Theory of Computing archive
Proceedings of the 41st annual ACM symposium on Theory of computing table of contents
Bethesda, MD, USA
SESSION: Approximation algorithms II table of contents
Pages 679-684  
Year of Publication: 2009
ISBN:978-1-60558-506-2
Authors
Jivitej S. Chadha  IIT Delhi, New Delhi, India
Naveen Garg  IIT Delhi, New Delhi, India
Amit Kumar  IIT Delhi, New Delhi, India
V. N. Muralidhara  IIT Delhi, New Delhi, India
Sponsors
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

We consider the online problem of scheduling jobs on unrelated machines so as to minimize the total weighted flow time. This problem has an unbounded competitive ratio even for very restricted settings. In this paper we show that if we allow the machines of the online algorithm to have ε more speed than those of the offline algorithm then we can get an O((1+ε-1)2)-competitive algorithm. Our algorithm schedules jobs preemptively but without migration. However, we compare our solution to an offline algorithm which allows migration. Our analysis uses a potential function argument which can also be extended to give a simpler and better proof of the randomized immediate dispatch algorithm of Chekuri-Goel-Khanna-Kumar for minimizing average flow time on parallel 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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S. Anand, Naveen Garg, and Amit Kumar. An O(log P) competitive algorithm for minimizing flow time on related machines. Unpublished manuscript, 2009.
 
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Naveen Garg and Amit Kumar. Better algorithms for minimizing average flow-time on related machines. In ICALP (1), pages 181--190, 2006.
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Collaborative Colleagues:
Jivitej S. Chadha: colleagues
Naveen Garg: colleagues
Amit Kumar: colleagues
V. N. Muralidhara: colleagues