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


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.

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We thank the anonymous reviewers for their useful comments, and Kirk Pruhs for useful discussions.

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Correspondence to Stanley P. Y. Fung.

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Birks, M., Cole, D., Fung, S.P.Y. et al. Online algorithms for maximizing weighted throughput of unit jobs with temperature constraints. J Comb Optim 26, 237–250 (2013).

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  • Online algorithms
  • Scheduling
  • Competitive analysis
  • Temperature
  • Resource augmentation