]. M. Andreolini, S. Casolari, M. Colajanni, and M. Messori, Dynamic Load Management of Virtual Machines in Cloud Architectures, LNICST, vol.34, pp.201-214, 2010.
DOI : 10.1007/978-3-642-12636-9_14

]. M. Armbrust, A. Fox, R. Griffith, A. D. Joseph, R. H. Katz et al., Above the Clouds: A Berkeley View of Cloud Computing, 2009.

]. P. Barham, B. Dragovic, K. Fraser, S. Hand, T. Harris et al., Xen and the art of virtualization, SOSP, pp.164-177, 2003.

]. D. Borgetto, H. Casanova, G. Da-costa, and J. Pierson, Energy-aware service allocation, Future Generation Computer Systems, vol.28, issue.5, pp.769-779, 2012.
DOI : 10.1016/j.future.2011.04.018

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.309.8953

]. D. Borgetto, M. Maurer, G. Da-costa, J. Pierson, and I. Brandic, Energy-efficient and SLA-aware management of IaaS clouds, Proceedings of the 3rd International Conference on Future Energy Systems Where Energy, Computing and Communication Meet, e-Energy '12, pp.1-25, 2012.
DOI : 10.1145/2208828.2208853

]. D. Bozdag, U. Catalyurek, and F. Ozguner, A task duplication based bottom-up scheduling algorithm for heterogeneous environments, Proceedings 20th IEEE International Parallel & Distributed Processing Symposium, pp.132-137, 2006.
DOI : 10.1109/IPDPS.2006.1639389

]. D. Bunde, Power-aware scheduling for makespan and flow, Proc. the eighteenth annual ACM symposium on Parallelism in algorithms and architectures, p.131, 2006.

]. T. Burd and R. W. Brodersen, Energy efficient CMOS microprocessor design, Proceedings of the Twenty-Eighth Annual Hawaii International Conference on System Sciences, pp.288-297, 1995.
DOI : 10.1109/HICSS.1995.375385

]. J. Burge-2007, P. Burge, J. L. Ranganathan, and . Wiener, Cost-aware scheduling for heterogeneous enterprise machines (CASH’EM), 2007 IEEE International Conference on Cluster Computing, pp.481-487, 2007.
DOI : 10.1109/CLUSTR.2007.4629273

]. R. Buyya, C. Shin-yeo, and S. Venugopal, Market-Oriented Cloud Computing: Vision, Hype, and Reality for Delivering IT Services as Computing Utilities, 2008 10th IEEE International Conference on High Performance Computing and Communications, pp.5-13, 2008.
DOI : 10.1109/HPCC.2008.172

]. R. Buyya, S. Pandey, and C. Vecchiola, Cloudbus Toolkit for Market-Oriented Cloud Computing, Cloud Computing, pp.24-44, 2009.
DOI : 10.1007/978-3-642-10665-1_4

S. Cahon, N. Melab, and E. Talbi, ParadisEO: A Framework for the Reusable Design of Parallel and Distributed Metaheuristics, Journal of Heuristics, vol.10, issue.3, pp.357-380, 2004.
DOI : 10.1023/B:HEUR.0000026900.92269.ec

]. K. Cameron, Trading in Green IT, Computer, vol.43, issue.3, pp.83-85, 2010.
DOI : 10.1109/MC.2010.81

]. R. Campbell, I. Gupta, M. Heath, S. Y. Ko, M. Kozuch et al., Open Cirrus cloud computing testbed: federated data centers for open source systems and services research, Proceedings of the conference on Hot topics in cloud computing (HotCloud), 2009.

]. S. Chaisiri, . Bu-sung, D. Lee, and . Niyato, Optimal virtual machine placement across multiple cloud providers, 2009 IEEE Asia-Pacific Services Computing Conference (APSCC), pp.103-110, 2009.
DOI : 10.1109/APSCC.2009.5394134

]. J. Chen and T. W. Kuo, Multiprocessor Energy-Efficient Scheduling for Real-Time Tasks with Different Power Characteristics, International Bibliography Conference on Parallel Processing (ICPP), pp.13-20, 2005.

]. Y. Chen, A. Das, W. Qin, A. Sivasubramaniam, Q. Wang et al., Managing server energy and operational costs in hosting centers, ACM SIGMETRICS Performance Evaluation Review, vol.33, issue.1, pp.303-314, 2005.
DOI : 10.1145/1071690.1064253

]. J. Chen, C. Wang, B. B. Zhou, L. Sun, Y. C. Lee et al., Tradeoffs Between Profit and Customer Satisfaction for Service Provisioning in the Cloud, Proceedings of the 20th international symposium on High performance distributed computing, HPDC '11, pp.229-238, 2011.
DOI : 10.1145/1996130.1996161

]. B. Chun and D. E. Culler, User-Centric Performance Analysis of Market-Based Cluster Batch Schedulers, 2nd IEEE/ACM International Symposium on Cluster Computing and the Grid (CCGRID'02), p.30, 2002.
DOI : 10.1109/CCGRID.2002.1017109

]. J. Cohoon, S. U. Hedge, W. N. Martin, and D. Richards, Punctuated equilibria : A parallel genetic algorithm, Proceedings of the Second International Conference on Genetic Algorithms, p.148, 1987.

]. T. Cormen, C. E. Leiserson, and R. L. Rivest, Introduction to Algorithms, 1990.

]. T. Crainic and M. Toulouse, Parallel Strategies for Meta-Heuristics, Handbook of Metaheuristics of International Series in Operations Research & Management Science, pp.475-513, 2003.
DOI : 10.1007/0-306-48056-5_17

]. S. Darbha and D. P. , Optimal scheduling algorithm for distributed-memory machines, IEEE Transactions on Parallel and Distributed Systems, vol.9, issue.1, pp.87-95, 1998.
DOI : 10.1109/71.655248

]. K. Deb, Multi-objective optimization using evolutionary algorithms, 2001.

]. K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan, A fast and elitist multiobjective genetic algorithm: NSGA-II, IEEE Transactions on Evolutionary Computation, vol.6, issue.2, pp.182-197, 2002.
DOI : 10.1109/4235.996017

]. E. Elmroth, F. G. Marquez, D. Henriksson, and D. P. Ferrera, Accounting and Billing for Federated Cloud Infrastructures, 2009 Eighth International Conference on Grid and Cooperative Computing, pp.268-275, 2009.
DOI : 10.1109/GCC.2009.37

]. E. Feller, L. Rilling, and C. Morin, Snooze: A Scalable and Autonomic Virtual Machine Management Framework for Private Clouds, 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012), pp.482-489, 2012.
DOI : 10.1109/CCGrid.2012.71

URL : https://hal.archives-ouvertes.fr/hal-00651542

]. I. Foster, Y. Zhao, I. Raicu, and S. Lu, Cloud Computing and Grid Computing 360-Degree Compared, 2008 Grid Computing Environments Workshop, pp.1-10, 2008.
DOI : 10.1109/GCE.2008.4738445

M. R. Garey and D. S. Johnson, Computers and intractability: A guide to the theory of np-completeness, pp.67-91, 1979.

S. Garg, P. Konugurthi, and R. Buyya, A Linear Programming Driven Genetic Algorithm for Meta-Scheduling on Utility Grids, Advanced Computing and Communications. ADCOM. 16th International Conference on, pp.19-26, 2008.

]. S. Garg, C. S. Yeo, A. Anandasivam, and R. Buyya, Environmentconscious scheduling of HPC applications on distributed Cloud-oriented data centers, Press, Corrected Proof, pp.26-31, 2010.

]. R. Ge, X. Feng, and K. W. Cameron, Performance-constrained Distributed DVS Scheduling for Scientific Applications on Power-aware Clusters, ACM/IEEE SC 2005 Conference (SC'05), pp.34-44, 2005.
DOI : 10.1109/SC.2005.57

S. Greenberg, E. Mills, B. Tschudi, P. Rumsey, and B. Myatt, Best practices for data centers: results from benchmarking 22 data centers, Proceedings of the ACEEE Summer Study on Energy Efficiency in Buildings, 2006.

M. Guzek, C. Diaz, J. Pecero, P. Bouvry, and A. Y. Zomaya, Impact of Voltage Levels Number for Energy-Aware Bi-objective DAG Scheduling for Multi-processors Systems, Borworn Papasratorn, pp.70-80
DOI : 10.1007/978-3-642-35076-4_7

]. J. Hamilton, Cooperative Expendable Micro-Slice Servers (CEMS): Low Cost, Low Power Servers for Internet-Scale Services, Proceedings of 4th Biennial Conference on Innovative Date Systems Research (CIDR), 2009.

]. D. Irwin, L. E. Grit, and J. S. Chase, Balancing risk and reward in a market-based task service, Proceedings. 13th IEEE International Symposium on High performance Distributed Computing, 2004., pp.160-169, 2004.
DOI : 10.1109/HPDC.2004.1323519

]. M. Iverson, F. Özgüner, and L. C. Potter, Statistical prediction of task execution times through analytic benchmarking for scheduling in a heterogeneous environment, IEEE Transactions on Computers, vol.48, issue.12, pp.1374-1379, 1999.
DOI : 10.1109/12.817403

]. D. Johnson, Near-optimal bin packing algorithms, 1973.

]. K. Keahey, T. Freeman, J. Lauret, and D. Olson, Virtual workspaces for scientific applications, Journal of Physics: Conference Series, vol.78, issue.1, 2007.
DOI : 10.1088/1742-6596/78/1/012038

M. Keijzer, J. J. Merelo, G. Romero, and M. Schoenauer, Evolving Objects: A General Purpose Evolutionary Computation Library, Artificial Evolution Lecture Notes in Computer Science, vol.2310, pp.231-242, 2002.
DOI : 10.1007/3-540-46033-0_19

]. S. Khan and I. Ahmad, A Cooperative Game Theoretical Technique for Joint Optimization of Energy Consumption and Response Time in Computational Grids, IEEE Transactions on Parallel and Distributed Systems, vol.20, issue.3, pp.346-360, 2009.
DOI : 10.1109/TPDS.2008.83

]. K. Kim, R. Buyya, and J. Kim, Power Aware Scheduling of Bag-of-Tasks Applications with Deadline Constraints on DVS-enabled Clusters, Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07), p.131, 2007.
DOI : 10.1109/CCGRID.2007.85

]. S. Kim, S. Lee, and J. Hahm, Push-Pull: Deterministic Search-Based DAG Scheduling for Heterogeneous Cluster Systems, IEEE Transactions on Parallel and Distributed Systems, vol.18, issue.11, pp.1489-1502, 2007.
DOI : 10.1109/TPDS.2007.1106

]. D. Kliazovich, P. Bouvry, and S. U. Khan, Simulating communication processes in energy-efficient cloud computing systems, 2012 IEEE 1st International Conference on Cloud Networking (CLOUDNET), pp.215-217, 2012.
DOI : 10.1109/CloudNet.2012.6483687

]. G. Koch, Discovering multi-core: Extending the benefits of Moore's law, Technology@Intel Magazine, 2005.

]. J. Koomey, Estimating total power consumption by servers in the U.S. and the world, pp.34-86, 2008.

]. Y. Kwok and I. Ahmad, Benchmarking the task graph scheduling algorithms, Proceedings of the First Merged International Parallel Processing Symposium and Symposium on Parallel and Distributed Processing, pp.531-537, 1998.
DOI : 10.1109/IPPS.1998.669967

]. G. Laszewski, L. Wang, and J. Andrew, Younge and Xi He. Power-Aware Scheduling of Virtual Machines in DVFS-enabled Clusters, Cluster Computing and Workshops (CLUSTER), IEEE International Conference on, pp.1-10, 2009.

]. Y. Lee and A. Y. Zomaya, A Productive Duplication-Based Scheduling Algorithm for Heterogeneous Computing Systems, Proceedings of the First international conference on High Performance Computing and Communications (HPCC), pp.203-212, 2005.
DOI : 10.1007/11557654_26

]. Y. Lee and A. Y. Zomaya, A Novel State Transition Method for metaheuristic-Based Scheduling in Heterogeneous Computing Systems, pp.1215-1223, 2008.

]. Y. Lee and A. Zomaya, Minimizing Energy Consumption for Precedence-Constrained Applications Using Dynamic Voltage Scaling, 2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid, pp.92-99, 2009.
DOI : 10.1109/CCGRID.2009.16

]. Y. Lee, C. Wang, A. Y. Zomaya, and B. B. Zhou, Profit-Driven Service Request Scheduling in Clouds, 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing, pp.15-24, 2010.
DOI : 10.1109/CCGRID.2010.83

]. Y. Lee and A. Zomaya, Energy efficient utilization of resources in cloud computing systems, The Journal of Supercomputing, vol.21, issue.4, pp.1-13, 2010.
DOI : 10.1007/s11227-010-0421-3

A. Liefooghe, L. Jourdan, and E. Talbi, A Unified Model for Evolutionary Multiobjective Optimization and its Implementation in a General Purpose Software Framework: ParadisEO-MOEO. Rapport de recherche RR-6906, 2009.
URL : https://hal.archives-ouvertes.fr/inria-00376770

]. J. Lucas-simarro-2012, R. Luis-lucas-simarro, R. S. Moreno-vozmediano, I. M. Montero, and . Llorente, Scheduling strategies for optimal service deployment across multiple clouds, Future Generation Computer Systems, vol.29, issue.6, pp.2012-2038
DOI : 10.1016/j.future.2012.01.007

]. G. Mankiw, Principles of economics. Sourth-Western Pub, p.66, 2008.

M. Mezmaz, N. Melab, Y. Kessaci, Y. C. Lee, E. Talbi et al., A parallel bi-objective hybrid metaheuristic for energy-aware scheduling for cloud computing systems, Press, Corrected Proof, p.2011
DOI : 10.1016/j.jpdc.2011.04.007

URL : https://hal.archives-ouvertes.fr/hal-00639966

]. K. Mills, J. Filliben, and C. Dabrowski, Comparing VM-Placement Algorithms for On-Demand Clouds, 2011 IEEE Third International Conference on Cloud Computing Technology and Science, pp.91-98, 2011.
DOI : 10.1109/CloudCom.2011.22

]. D. Milojicic, I. M. Llorente, and R. S. Montero, OpenNebula: A Cloud Management Tool, IEEE Internet Computing, vol.15, issue.2, pp.11-14, 2011.
DOI : 10.1109/MIC.2011.44

]. R. Min, T. Furrer, and A. Chandrakasan, Dynamic voltage scaling techniques for distributed microsensor networks, Proceedings IEEE Computer Society Workshop on VLSI 2000. System Design for a System-on-Chip Era, pp.43-46, 2000.
DOI : 10.1109/IWV.2000.844528

]. D. Nurmi, R. Wolski, C. Grzegorczyk, G. Obertelli, S. Soman et al., The Eucalyptus Open-Source Cloud-Computing System, 2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid, pp.124-131, 2009.
DOI : 10.1109/CCGRID.2009.93

]. Orgerie, L. Lefevre, and J. Gelas, Save Watts in Your Grid: Green Strategies for Energy-Aware Framework in Large Scale Distributed Systems, 2008 14th IEEE International Conference on Parallel and Distributed Systems, pp.171-178, 2008.
DOI : 10.1109/ICPADS.2008.97

URL : https://hal.archives-ouvertes.fr/ensl-00474726

V. Pareto, Cours d'économie politique. Rouge, p.12, 1896.

]. P. Pillai and K. G. Shin, Real-time dynamic voltage scaling for lowpower embedded operating systems, Proceedings of the eighteenth ACM symposium on Operating systems principles (SOSP), pp.89-102, 2001.

]. D. Rajpathak, Knowledge Media Institute Intelligent scheduling -A Literature Review, 2001.

]. B. Rimal, E. Choi, and I. Lumb, A Taxonomy and Survey of Cloud Computing Systems, 2009 Fifth International Joint Conference on INC, IMS and IDC, pp.44-51, 2009.
DOI : 10.1109/NCM.2009.218

]. N. Rizvandi, J. Taheri, A. Y. Zomaya, and Y. C. Lee, Linear Combinations of DVFS-Enabled Processor Frequencies to Modify the Energy- Aware Scheduling Algorithms. Cluster Computing and the Grid, IEEE International Symposium on, vol.0, issue.28, pp.388-397, 2010.

]. B. Rountree, D. K. Lowenthal, S. Funk, V. W. Freeh, B. R. De-supinski et al., Bounding energy consumption in large-scale MPI programs, Proceedings of the 2007 ACM/IEEE conference on Supercomputing , SC '07, p.131, 2007.
DOI : 10.1145/1362622.1362688

]. S. Srikantaiah, A. Kansal, and F. Zhao, Energy Aware Consolidation for Cloud Computing, Proceedings of Workshop on Power Aware Computing and Systems (HotPower). USENIX, 2008.

]. Talbi, Metaheuristics : from design to implementation. The Sciences Po series in international relations and political economy, pp.16-45, 2009.
DOI : 10.1002/9780470496916

URL : https://hal.archives-ouvertes.fr/hal-00750681

]. G. Tesauro, R. Das, H. Chan, J. O. Kephart, D. Levine et al., Managing Power Consumption and Performance of Computing Systems Using Reinforcement Learning, NIPS, 2007.

H. Topcuouglu, S. Hariri, and M. Y. Wu, Performance-effective and low-complexity task scheduling for heterogeneous computing, IEEE Transactions on Parallel and Distributed Systems, vol.13, issue.3, pp.260-274, 2002.
DOI : 10.1109/71.993206

]. J. Tordsson, R. S. Montero, R. Moreno-vozmediano, and I. M. Llorente, Cloud brokering mechanisms for optimized placement of virtual machines across multiple providers, Future Generation Computer Systems, vol.28, issue.2, pp.358-367, 2012.
DOI : 10.1016/j.future.2011.07.003

]. V. Venkatachalam and M. Franz, Power reduction techniques for microprocessor systems, ACM Computing Surveys, vol.37, issue.3, pp.195-237, 2005.
DOI : 10.1145/1108956.1108957

]. S. Venugopal, X. Chu, and R. Buyya, A Negotiation Mechanism for Advance Resource Reservations Using the Alternate Offers Protocol, 2008 16th Interntional Workshop on Quality of Service, pp.40-49, 2008.
DOI : 10.1109/IWQOS.2008.10

]. A. Verma, P. Ahuja, and A. Neogi, pMapper: Power and Migration Cost Aware Application Placement in Virtualized Systems, Lecture Notes in Computer Science, vol.36, issue.12, pp.243-264, 2008.
DOI : 10.1109/MC.2003.1250880

]. L. Wang and Y. Lu, Efficient Power Management of Heterogeneous Soft Real-Time Clusters, 2008 Real-Time Systems Symposium, pp.323-332, 2008.
DOI : 10.1109/RTSS.2008.31

]. L. Wang, G. Von-laszewski, and J. Dayal, Towards Energy Aware Scheduling for Precedence Constrained Parallel Tasks in a Cluster with DVFS, 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing, pp.17-20, 2010.
DOI : 10.1109/CCGRID.2010.19

Z. Wu, X. Liu, Z. Ni, D. Yuan, and Y. Yang, A market-oriented hierarchical scheduling strategy in??cloud workflow systems, The Journal of Supercomputing, vol.14, issue.3???4, pp.256-293, 2013.
DOI : 10.1007/s11227-011-0578-4

]. J. Xu and J. A. Fortes, Multi-Objective Virtual Machine Placement in Virtualized Data Center Environments, 2010 IEEE/ACM Int'l Conference on Green Computing and Communications & Int'l Conference on Cyber, Physical and Social Computing, pp.179-188, 2010.
DOI : 10.1109/GreenCom-CPSCom.2010.137

]. J. Yu and R. Buyya, Scheduling Scientific Workflow Applications with Deadline and Budget Constraints Using Genetic Algorithms, Scientific Programming, pp.217-230, 2006.
DOI : 10.1155/2006/271608

]. X. Zhong and C. Xu, Energy-Aware Modeling and Scheduling for Dynamic Voltage Scaling with Statistical Real-Time Guarantee, IEEE Transactions on Computers, vol.56, issue.3, pp.358-372, 2007.
DOI : 10.1109/TC.2007.48

]. D. Zhu, R. Melhem, and B. R. Childers, Scheduling with dynamic voltage/speed adjustment using slack reclamation in multiprocessor real-time systems, IEEE Trans. Parallel Dist. Systems, vol.14, issue.137, pp.686-700, 2003.

D. Zhu, D. Mosse, and R. Melhem, Power-aware scheduling for AND/OR graphs in real-time systems, IEEE Transactions on Parallel and Distributed Systems, vol.15, issue.9, pp.849-864, 2004.
DOI : 10.1109/TPDS.2004.45

]. J. Zhuo and C. Chakrabarti, Energy-efficient dynamic task scheduling algorithms for DVS systems, ACM Transactions on Embedded Computing Systems, vol.7, issue.2, pp.1-17, 2008.
DOI : 10.1145/1331331.1331341

]. A. Zomaya, C. Ward, and B. S. Macey, Genetic scheduling for parallel processor systems: comparative studies and performance issues, IEEE Transactions on Parallel and Distributed Systems, vol.10, issue.8, pp.795-812, 1999.
DOI : 10.1109/71.790598