M. Akdere, U. Çetintemel, M. Riondato, E. Upfal, and S. B. Zdonik, Learning-based query performance modeling and prediction, International Conference on Data Engineering, pp.390-401, 2012.

M. Armbrust, A. Fox, R. Griffith, A. D. Joseph, R. Katz et al., Ariel Rabkin, Ion Stoica, and Matei Zaharia. 2010. A View of Cloud Computing, Commun. ACM, vol.53, pp.50-58, 2010.

, Amazon Web Services Website, AWS 2018, 2018.

, Microsoft Azure Website, 2018.

L. S. Batista, Performance Assessment of Multiobjective Evolutionary Algorithms, 2012.

L. Breiman, Bagging predictors, Machine Learning, vol.24, pp.123-140, 1996.

C. A. Coello, D. A. Van-veldhuizen, and G. B. Lamont, Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation), 2002.

J. Dean and S. Ghemawat, MapReduce: Simplified Data Processing on Large Clusters, Commun. ACM, vol.51, pp.107-113, 2008.

K. Deb and H. Jain, An Evolutionary Many-Objective Optimization Algorithm Using Reference-point Based Non-dominated Sorting Approach, Part I: Solving Problems with Box Constraints, IEEEXplore, vol.18, 2013.

K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan, A fast and elitist multiobjective genetic algorithm: NSGA-II, IEEE Trans. Evol. Comput, vol.6, pp.182-197, 2002.

K. Doka, N. Papailiou, D. Tsoumakos, C. Mantas, and N. Koziris, IReS: Intelligent, Multi-Engine Resource Scheduler for Big Data Analytics Workflows, SIGMOD '15, 2015.

H. M. Fard, R. Prodan, J. J. Barrionuevo, and T. Fahringer, A Multiobjective Approach for Workflow Scheduling in Heterogeneous Environments, 2012.

C. M. Fonseca and P. J. Fleming, An Overview of Evolutionary Algorithms in Multiobjective Optimization, Evolutionary Computation, vol.3, issue.1, pp.1-16, 1995.

. Galactica, The Galactica Website, 2018.

A. Ganapathi, H. Kuno, U. Dayal, J. L. Wiener, A. Fox et al., Predicting Multiple Metrics for Queries: Better Decisions Enabled by Machine Learning, IEEE 25th International Conference on Data Engineering, pp.592-603, 2009.

. Google, Google Cloud Website, 2018.

F. Helff and L. Orazio, Weighted Sum Model for MultiObjective Query Optimization for Mobile-Cloud Database Environments, EDBT/ICDT Workshops, 2016.

, The Hive Website, 2018.

H. Jain and K. Deb, An evolutionary many-objective optimization algorithm using reference-point based nondominated sorting approach, Part II: Handling constraints and extending to an adaptive approach, IEEE Transactions on Evolutionary Computation, vol.18, pp.602-622, 2014.

S. A. Khan and S. Rehman, Iterative non-deterministic algorithms in on-shore wind farm design: A brief survey, Renewable and Sustainable Energy Reviews, vol.19, pp.370-384, 2013.

J. Knowles and D. Corne, The Pareto archived evolution strategy: a new baseline algorithm for Pareto multiobjective optimisation, Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406), vol.1, pp.98-105, 1999.

T. Le, V. Kantere, and L. Orazio, An efficient multi-objective genetic algorithm for cloud computing: NSGA-G, International Workshop on Benchmarking, Performance Tuning and Optimization for Big Data Applications (BPOD@BigData), 2018.
URL : https://hal.archives-ouvertes.fr/hal-01962235

T. Nykiel, M. Potamias, C. Mishra, G. Kollios, and N. Koudas, MRShare: sharing across multiple queries in MapReduce, 2010.

, The PostgreSQL Website, 2018.

J. Peter, A. M. Rousseeuw, and . Leroy, Robust regression and outlier detection, 1987.

S. Sidhanta, W. Golab, and S. Mukhopadhyay, OptEx: A Deadline-Aware Cost Optimization Model for Spark, IEEE/ACM, 2016.

T. Tsu and . Soong, Fundamentals of probability and statistics for engineers, 2004.

, The Spark Website, 2018.

N. Srinivas and K. Deb, Muiltiobjective Optimization Using Nondominated Sorting in Genetic Algorithms, Evolutionary Computation, vol.2, pp.221-248, 1994.

S. Tozer, T. Brecht, and A. Aboulnaga, Q-Cop: Avoiding bad query mixes to minimize client timeouts under heavy loads, International Conference on Data Engineering, pp.397-408, 2010.

. Tpc-h, The TPC-H Website, 2018.

I. Trummer and C. Koch, Multi-objective parametric query optimization, VLDB J, vol.8, 2016.

. Weka, The Weka Website, 2018.

W. Wu, Y. Chi, S. Zhu, J. Tatemura, H. Hacigümüs et al., Predicting query execution time: Are optimizer cost models really unusable?, IEEE 29th International Conference on Data Engineering (ICDE), 2013.

P. Xiong, F. Drive, and Y. Chi, ActiveSLA : A ProfitOriented Admission Control Framework for Database-as-a-Service Providers Categories and Subject Descriptors, 2nd ACM Symposium on Cloud Computing SOCC, vol.11, pp.1-14, 2011.

Q. Zhang and H. Li, MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition, IEEE Transactions on Evolutionary Computation, vol.11, pp.712-731, 2007.

E. Zitzler, M. Laumanns, and L. Thiele, SPEA2: Improving the strength Pareto evolutionary algorithm, p.103, 2001.