Online algorithms for maximizing weighted throughput of unit jobs with temperature constraints

Martin Birks (), Daniel Cole (), Stanley P. Y. Fung () and Huichao Xue ()
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Martin Birks: University of Leicester
Daniel Cole: University of Pittsburgh
Stanley P. Y. Fung: University of Leicester
Huichao Xue: University of Pittsburgh

Journal of Combinatorial Optimization, 2013, vol. 26, issue 2, No 2, 237-250

Abstract: Abstract We consider a temperature-aware online deadline scheduling model. The objective is to schedule a number of unit jobs, with release dates, deadlines, weights and heat contributions, to maximize the weighted throughput subject to a temperature threshold. We first give an optimally competitive randomized algorithm. Then we give a constant competitive randomized algorithm that allows a tradeoff between the maximum heat contribution of jobs and the competitiveness. Finally we consider the multiple processor case and give several tight upper and lower bounds.

Keywords: Online algorithms; Scheduling; Competitive analysis; Temperature; Resource augmentation (search for similar items in EconPapers)
Date: 2013
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DOI: 10.1007/s10878-012-9543-2

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