Speed Scaling to Manage Temperature

  • Leon Atkins
  • Guillaume Aupy
  • Daniel Cole
  • Kirk Pruhs
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6595)


We consider the speed scaling problem where the quality of service objective is deadline feasibility and the power objective is temperature. In the case of batched jobs, we give a simple algorithm to compute the optimal schedule. For general instances, we give a new online algorithm, and obtain an upper bound on the competitive ratio of this algorithm that is an order of magnitude better than the best previously known bound upper bound on the competitive ratio for this problem.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Leon Atkins
    • 1
  • Guillaume Aupy
    • 2
  • Daniel Cole
    • 3
  • Kirk Pruhs
    • 4
  1. 1.Department of Computer ScienceUniversity of BristolUK
  2. 2.Computer Science DepartmentENS LyonFrance
  3. 3.Computer Science DepartmentUniversity of PittsburghUSA
  4. 4.Computer Science DepartmentUniversity of PittsburghUSA

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