A. Labrinidis and H. V. Jagadish, Challenges and opportunities with big data, Proceedings of the VLDB Endowment, vol.5, issue.12, pp.2032-2033, 2012.
DOI : 10.14778/2367502.2367572

J. Dean and S. Ghemawat, MapReduce, Communications of the ACM, vol.53, issue.1, pp.72-77, 2010.
DOI : 10.1145/1629175.1629198

J. Song, X. Liu, Z. Zhu, D. Zhao, and G. Yu, A Novel Task Scheduling Approach for Reducing Energy Consumption of MapReduce Cluster, IETE Technical Review, vol.43, issue.1, pp.65-74, 2014.
DOI : 10.3724/SP.J.1001.2012.04144

E. N. Elnozahy, M. Kistler, and R. Rajamony, Energy-Efficient Server Clusters, PACS, pp.179-196, 2002.
DOI : 10.1007/3-540-36612-1_12
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.19.6123

K. G. Lee, V. Bharadwaj, and V. Sivakumar, Design of fast and efficient Energy-Aware Gradient-Based scheduling algorithms heterogeneous embedded multiprocessor systems

D. Costa, G. Dias-de-assunçassunç?assunção, M. Gelas, J. Georgiou, Y. Lefèvre et al., Multi-facet approach to reduce energy consumption in clouds and grids, Proceedings of the 1st International Conference on Energy-Efficient Computing and Networking, e-Energy '10, pp.95-104, 2010.
DOI : 10.1145/1791314.1791329
URL : https://hal.archives-ouvertes.fr/ensl-00517185

W. Lang and J. M. Patel, Energy management for MapReduce clusters, Proceedings of the VLDB Endowment, vol.3, issue.1-2, pp.129-139, 2010.
DOI : 10.14778/1920841.1920862
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.174.289

N. Maheshwari, R. Nanduri, and V. Varma, Dynamic energy efficient data placement and cluster reconfiguration algorithm for MapReduce framework, Future Generation Computer Systems, vol.28, issue.1, pp.119-127, 2012.
DOI : 10.1016/j.future.2011.07.001
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.463.1797

W. Xiong and A. Kansal, Energy efficient data intensive distributed computing, IEEE Data Eng. Bull. (DEBU), vol.34, issue.1, pp.24-33, 2011.

B. Palanisamy, A. Singh, L. Liu, and B. Jain, Purlieus, Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis on, SC '11, pp.1-5811, 2011.
DOI : 10.1145/2063384.2063462

E. Pinheiro, R. Bianchini, V. C. Enrique, and T. Heath, Load balancing and unbalancing for power and performance in cluster-based systems, Workshop on compilers and operating systems for low power, pp.182-195, 2001.

Y. Chen, L. Keys, and R. H. Katz, Towards Energy Efficient MapReduce Available via http, 2008.

E. Pinheiro, R. Bianchini, E. V. Carrera, and T. Heath, Dynamic Cluster Reconfiguration for Power and Performance, pp.75-93, 2003.
DOI : 10.1007/978-1-4419-9292-5_5
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.12.2144

Y. Chen, S. Alspaugh, D. Borthakur, and R. Katz, Energy efficiency for large-scale MapReduce workloads with significant interactive analysis, Proceedings of the 7th ACM european conference on Computer Systems, EuroSys '12, pp.43-56, 2012.
DOI : 10.1145/2168836.2168842
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.357.5804

N. Yigitbasi, K. Datta, N. Jain, and T. Willke, Energy efficient scheduling of MapReduce workloads on heterogeneous clusters, Green Computing Middleware on Proceedings of the 2nd International Workshop, GCM '11, pp.1-6, 2011.
DOI : 10.1145/2088996.2088997

E. Pinheiro and R. Bianchini, Energy conservation techniques for disk array-based servers, ICS, pp.68-78, 2004.
DOI : 10.1145/2591635.2667185
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.2.3348

R. T. Kaushik, T. F. Abdelzaher, R. Egashira, and K. Nahrstedt, Predictive data and energy management in GreenHDFS, 2011 International Green Computing Conference and Workshops, pp.1-9, 2011.
DOI : 10.1109/IGCC.2011.6008563

D. Colarelli and D. Grunwald, Massive Arrays of Idle Disks For Storage Archives, ACM/IEEE SC 2002 Conference (SC'02), pp.1-11, 2002.
DOI : 10.1109/SC.2002.10058

D. R. Karger, E. Lehman, F. T. Leighton, R. Panigrahy, M. S. Levine et al., Consistent hashing and random trees, Proceedings of the twenty-ninth annual ACM symposium on Theory of computing , STOC '97, pp.654-663, 1997.
DOI : 10.1145/258533.258660

A. Brinkmann, K. Salzwedel, and C. Scheideler, Efficient, distributed data placement strategies for storage area networks (extended abstract), Proceedings of the twelfth annual ACM symposium on Parallel algorithms and architectures , SPAA '00, pp.119-128, 2000.
DOI : 10.1145/341800.341815
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.25.8572

C. Tao, X. Nong, and L. Fang, Clustering-Based And consistent Hashing-Aware data placement algorithm, J. Softw, vol.21, issue.12, pp.3175-3185, 2010.

D. Yuan, Y. Yang, X. Liu, and J. Chen, A data placement strategy in scientific cloud workflows, Future Generation Computer Systems, vol.26, issue.8, pp.1200-1214, 2010.
DOI : 10.1016/j.future.2010.02.004

Z. Liu, Efficient, balanced data placement algorithm in scalable storage clusters, Journal of Communication and Computer, issue.7, pp.8-17, 2007.

L. Ronald, Graham: Bounds on Multiprocessing Timing anoMalies, SIAM J. Appl. Math. (SIAMAM), vol.17, issue.2, pp.416-429, 1969.

S. Jie, T. Li, W. Zhi, and Z. Zhiliang, Study on energyconsumption regularities of cloud computing systems by a novel evaluation model, Computing, pp.1-19, 2013.

J. Dean and S. Ghemawat, MapReduce, Communications of the ACM, vol.51, issue.1, pp.107-113, 2008.
DOI : 10.1145/1327452.1327492