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

Author

Listed:
  • Martin Birks

    (University of Leicester)

  • Daniel Cole

    (University of Pittsburgh)

  • Stanley P. Y. Fung

    (University of Leicester)

  • Huichao Xue

    (University of Pittsburgh)

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.

Suggested Citation

  • Martin Birks & Daniel Cole & Stanley P. Y. Fung & Huichao Xue, 2013. "Online algorithms for maximizing weighted throughput of unit jobs with temperature constraints," Journal of Combinatorial Optimization, Springer, vol. 26(2), pages 237-250, August.
    • Handle: RePEc:spr:jcomop:v:26:y:2013:i:2:d:10.1007_s10878-012-9543-2
    DOI: 10.1007/s10878-012-9543-2
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