Energy Efficient Scheduling of MapReduce Jobs

  • Evripidis Bampis
  • Vincent Chau
  • Dimitrios Letsios
  • Giorgio Lucarelli
  • Ioannis Milis
  • Georgios Zois
Conference paper

DOI: 10.1007/978-3-319-09873-9_17

Volume 8632 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Bampis E., Chau V., Letsios D., Lucarelli G., Milis I., Zois G. (2014) Energy Efficient Scheduling of MapReduce Jobs. In: Silva F., Dutra I., Santos Costa V. (eds) Euro-Par 2014 Parallel Processing. Euro-Par 2014. Lecture Notes in Computer Science, vol 8632. Springer, Cham

Abstract

MapReduce has emerged as a prominent programming model for data-intensive computation. In this work, we study power-aware MapReduce scheduling in the speed scaling setting first introduced by Yao et al. [FOCS 1995]. We focus on the minimization of the total weighted completion time of a set of MapReduce jobs under a given budget of energy. Using a linear programming relaxation of our problem, we derive a polynomial time constant-factor approximation algorithm. We also propose a convex programming formulation that we combine with standard list scheduling policies, and we evaluate their performance using simulations.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Evripidis Bampis
    • 1
  • Vincent Chau
    • 2
  • Dimitrios Letsios
    • 1
  • Giorgio Lucarelli
    • 1
  • Ioannis Milis
    • 3
  • Georgios Zois
    • 1
    • 3
  1. 1.Sorbonne Universités, UPMC Univ Paris 06, UMR 7606, LIP6France
  2. 2.IBISCUniversité d’ÉvryFrance
  3. 3.Dept. of InformaticsAUEBAthensGreece