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Modulo Based Data Placement Algorithm for Energy Consumption Optimization of MapReduce System

Abstract : With the explosion of data production, the efficiency of data management and analysis has been concerned by both industry and academia. Meanwhile, more and more energy is consumed by the IT infrastructure especially the larger scale distributed systems. In this paper, a novel idea for optimizing the Energy Consumption (EC for short) of MapReduce system is proposed. We argue that a fair data placement is helpful to save energy, and then we propose three goals of data placement, and a modulo based Data Placement Algorithm (DPA for short) which achieves these goals. Afterwards, the correctness of the proposed DPA is proved from both theoretical and experimental perspectives. Three different systems which implement MapReduce model with different DPAs are compared in our experiments. Our algorithm is proved to optimize EC effectively, without introducing the additional costs and delaying data loading. With the help of our DPA, the EC for the WordCount , Sort and MRBench can be reduced by 10.9 %, 8.3 % and 17 % respectively, and time consumption is reduced by 7 %, 6.3 % and 7 % respectively.
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Jie Song, Hongyan He, Zhi Wang, Ge yu, Jean-Marc Pierson. Modulo Based Data Placement Algorithm for Energy Consumption Optimization of MapReduce System. Journal of Grid Computing, Springer Verlag, 2016, 1, pp.1-16. ⟨10.1007/s10723-016-9370-2⟩. ⟨hal-01514611⟩

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