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Speed is as powerful as clairvoyance
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Source Journal of the ACM (JACM) archive
Volume 47 ,  Issue 4  (July 2000) table of contents
Pages: 617 - 643  
Year of Publication: 2000
ISSN:0004-5411
Authors
Bala Kalyanasundaram  Univ. of Pittsburgh, Pittsburgh, PA
Kirk Pruhs  Univ. of Pittsburgh, Pittsburgh, PA
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 11,   Downloads (12 Months): 81,   Citation Count: 51
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ABSTRACT

We introduce resource augmentation as a method for analyzing online scheduling problems. In resource augmentation analysis the on-line scheduler is given more resources, say faster processors or more processors, than the adversary. We apply this analysis to two well-known on-line scheduling problems, the classic uniprocessor CPU scheduling problem 1 |ri, pmtn|&Sgr; Fi, and the best-effort firm real-time scheduling problem 1|ri, pmtn| &Sgr; wi( 1- Ui). It is known that there are no constant competitive nonclairvoyant on-line algorithms for these problems. We show that there are simple on-line scheduling algorithms for these problems that are constant competitive if the online scheduler is equipped with a slightly faster processor than the adversary. Thus, a moderate increase in processor speed effectively gives the on-line scheduler the power of clairvoyance. Furthermore, the on-line scheduler can be constant competitive on all inputs that are not closely correlated with processor speed. We also show that the performance of an on-line scheduler is best-effort real time scheduling can be significantly improved if the system is designed in such a way that the laxity of every job is proportional to its length.


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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CITED BY  51


REVIEW

"Albert Alkins Mullin : Reviewer"

The title of this paper is a reference to an important paper by Berman and Coulston [1]. Here, the authors show that for interesting classes of complex problems, there are simple online scheduling algorithms that are constant competitive if th  more...

Collaborative Colleagues:
Bala Kalyanasundaram: colleagues
Kirk Pruhs: colleagues