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

Authors :
Zhi Wang
Jie Song
Jean-Marc Pierson
Hongyan He
Ge Yu
Northeastern University [Shenyang]
Système d’exploitation, systèmes répartis, de l’intergiciel à l’architecture (IRIT-SEPIA)
Institut de recherche en informatique de Toulouse (IRIT)
Université Toulouse 1 Capitole (UT1)
Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3)
Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP)
Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse 1 Capitole (UT1)
Université Fédérale Toulouse Midi-Pyrénées
Centre National de la Recherche Scientifique - CNRS (FRANCE)
Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
Université Toulouse III - Paul Sabatier - UT3 (FRANCE)
Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université Toulouse 1 Capitole - UT1 (FRANCE)
Northeastern University (CHINA)
Institut de Recherche en Informatique de Toulouse - IRIT (Toulouse, France)
Institut National Polytechnique de Toulouse - INPT (FRANCE)
Source :
Journal of Grid Computing, Journal of Grid Computing, Springer Verlag, 2016, 1, pp.1-16. ⟨10.1007/s10723-016-9370-2⟩
Publication Year :
2016
Publisher :
Springer Science and Business Media LLC, 2016.

Abstract

International audience; 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.

Details

ISSN :
15729184 and 15707873
Volume :
16
Database :
OpenAIRE
Journal :
Journal of Grid Computing
Accession number :
edsair.doi.dedup.....4baf02a6fcec63ca5bdb635beabba82a