Energy Efficient Scheduling of MapReduce Jobs

Abstract : MapReduce is 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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https://hal.archives-ouvertes.fr/hal-01020100
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Submitted on : Monday, July 7, 2014 - 5:06:35 PM
Last modification on : Monday, October 28, 2019 - 10:50:21 AM

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Evripidis Bampis, Vincent Chau, Dimitrios Letsios, Giorgio Lucarelli, Ioannis Milis, et al.. Energy Efficient Scheduling of MapReduce Jobs. 20th International Conference on Parallel Processing (Euro-Par 2014), Aug 2014, Porto, Portugal. pp.198-209, ⟨10.1007/978-3-319-09873-9_17⟩. ⟨hal-01020100⟩

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