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Title: Multiprocessor speed scaling for jobs with arbitrary sizes and deadlines
Authors: Bell, Paul C.
Wong, Prudence W.H.
Keywords: Online algorithms
Dynamic speed scaling
Competitive analysis
Multiprocessor scheduling
Deadline scheduling
Issue Date: 2015
Publisher: © Springer
Citation: BELL, P.C. and WONG, P.W.H., 2015. Multiprocessor speed scaling for jobs with arbitrary sizes and deadlines. Journal of Combinatorial Optimization, 29 (4), pp. 739 - 749
Abstract: In this paper we study energy efficient deadline scheduling on multiprocessors in which the processors consumes power at a rate of sα when running at speeds, where α ≥ 2. The problem is to dispatch jobs to processors and determine the speed and jobs to run for each processor so as to complete all jobs by their deadlines using the minimum energy. The problem has been well studied for the single processor case. For the multiprocessor setting, constant competitive online algorithms for special cases of unit size jobs or arbitrary size jobs with agreeable deadlines have been proposed by Albers et al. (2007). A randomized algorithm has been proposed for jobs of arbitrary sizes and arbitrary deadlines by Greiner et al. (2009). We propose a deterministic online algorithm for the general setting and show that it is O(logαP)-competitive, where P is the ratio of the maximum and minimum job size.
Description: This article was published in the journal, Journal of Combinatorial Optimization [© Springer]. The definitive version is available at: http://dx.doi.org/10.1007/s10878-013-9618-8. A preliminary version appeared in Proceedings of the 8th Annual Conference on Theory and Applications of Models of Computation, 2011, pp. 27–36.
Sponsor: This work is partially supported by EPSRC Grant EP/E028276/1.
Version: Accepted for publication
DOI: 10.1007/s10878-013-9618-8
URI: https://dspace.lboro.ac.uk/2134/18803
Publisher Link: http://dx.doi.org/10.1007/s10878-013-9618-8
ISSN: 1382-6905
Appears in Collections:Published Articles (Computer Science)

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