Optimal on-line algorithms to minimize makespan on two machines with resource augmentation

Leah Epstein; Arik Ganot

doi:10.1007/s00224-007-9007-8

Optimal on-line algorithms to minimize makespan on two machines with resource augmentation

Leah Epstein, Arik Ganot

Department of Mathematics

Research output: Contribution to journal › Article › peer-review

Abstract

We study the problem of on-line scheduling on two uniformly related machines where the on-line algorithm has resources different from those of the off-line algorithm. We consider three versions of this problem, preemptive semi-online, non-preemptive on-line and preemptive on-line scheduling. For all these cases we design algorithms with best possible competitive ratios as functions of the machine speeds.

Original language	English
Pages (from-to)	431-449
Number of pages	19
Journal	Theory of Computing Systems
Volume	42
Issue number	4
DOIs	https://doi.org/10.1007/s00224-007-9007-8
State	Published - May 2008

Keywords

Load balancing
Online algorithms
Resource augmentation
Scheduling

ASJC Scopus subject areas

Theoretical Computer Science
Computational Theory and Mathematics

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10.1007/s00224-007-9007-8

Cite this

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abstract = "We study the problem of on-line scheduling on two uniformly related machines where the on-line algorithm has resources different from those of the off-line algorithm. We consider three versions of this problem, preemptive semi-online, non-preemptive on-line and preemptive on-line scheduling. For all these cases we design algorithms with best possible competitive ratios as functions of the machine speeds.",

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Optimal on-line algorithms to minimize makespan on two machines with resource augmentation

Abstract

Keywords

ASJC Scopus subject areas

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