Energy Efficient Scheduling of MapReduce Jobs

  • Evripidis Bampis
  • Vincent Chau
  • Dimitrios Letsios
  • Giorgio Lucarelli
  • Ioannis Milis
  • Georgios Zois
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8632)


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.


Completion Time Precedence Constraint Feasible Schedule Linear Programming Relaxation Total Weighted Completion Time 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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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

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