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How to Schedule When You Have to Buy Your Energy

  • Conference paper
Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (RANDOM 2010, APPROX 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6302))

Abstract

We consider a situation where jobs arrive over time at a data center, consisting of identical speed-scalable processors. For each job, the scheduler knows how much income is lost as a function of how long the job is delayed. The scheduler also knows the fixed cost of a unit of energy. The online scheduler determines which jobs to run on which processors, and at what speed to run the processors. The scheduler’s objective is to maximize profit, which is the income obtained from jobs minus the energy costs. We give a (1 + ε)-speed O(1)-competitive algorithm, and show that resource augmentation is necessary to achieve O(1)-competitiveness.

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Author information

Authors and Affiliations

  1. Computer Science Department., University of Pittsburgh, Pittsburgh, PA, USA

    Kirk Pruhs

  2. Department of IEOR, Columbia University, New York, NY

    Cliff Stein

Authors
  1. Kirk Pruhs
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  2. Cliff Stein
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Editor information

Editors and Affiliations

  1. Universitat Politecnica de Catalunya, Departament de Llenguatges i Sistemes Informatics, Campus Nord - Ed Omega, Desp. 235, Jordi Girona, 1-3, 08034, Barcelona, Spain

    Maria Serna

  2. Department of Computer Science, University of Haifa, Mount Carmel, 31905, Haifa, Israel

    Ronen Shaltiel

  3. Department of Computer Science, University of Kiel, Olshausenstrasse 40, 24098, Kiel, Germany

    Klaus Jansen

  4. University of Geneva, Centre Universitaire d’Informatique, Battelle Bat. A, 7 rte de Drize, 1227, Carouge, Switzerland

    José Rolim

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© 2010 Springer-Verlag Berlin Heidelberg

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Pruhs, K., Stein, C. (2010). How to Schedule When You Have to Buy Your Energy. In: Serna, M., Shaltiel, R., Jansen, K., Rolim, J. (eds) Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques. RANDOM APPROX 2010 2010. Lecture Notes in Computer Science, vol 6302. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15369-3_27

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  • DOI: https://doi.org/10.1007/978-3-642-15369-3_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15368-6

  • Online ISBN: 978-3-642-15369-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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