Online Scheduling of Equal-Length Jobs: Randomization and Restarts Help
The input of the studied scheduling problem is a set of jobs with equal processing times, where each job is specified by its release time and deadline. The goal is to determine a single-processor, non-preemptive schedule that maximizes the number of completed jobs. In the online version, each job ar...
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Format: | Buchkapitel |
Sprache: | eng |
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Zusammenfassung: | The input of the studied scheduling problem is a set of jobs with equal processing times, where each job is specified by its release time and deadline. The goal is to determine a single-processor, non-preemptive schedule that maximizes the number of completed jobs. In the online version, each job arrives at its release time.
First, we give a barely random \documentclass[12pt]{minimal}
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\begin{document}$\frac{5}{3}$\end{document}-competitive algorithm that uses only one random bit; we also show a lower bound of \documentclass[12pt]{minimal}
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\begin{document}$\frac{3}{2}$\end{document} for barely random algorithms that choose one of two deterministic algorithms. Second, we give a deterministic \documentclass[12pt]{minimal}
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\begin{document}$\frac{3}{2}$\end{document}-competitive algorithm in the model that allows restarts, and we show that in this model the ratio \documentclass[12pt]{minimal}
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\begin{document}$\frac{3}{2}$\end{document} is optimal. |
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ISSN: | 0302-9743 1611-3349 |
DOI: | 10.1007/978-3-540-27836-8_32 |