W. Van-der-aalst and K. Van-hee, Workflow Management: Models, Methods, and Systems, 2002.

E. Deelman, D. Gannon, M. Shields, and I. Taylor, Workflows and e-Science: An overview of workflow system features and capabilities, Future Generation Computer Systems, vol.25, issue.5, pp.528-540, 2009.
DOI : 10.1016/j.future.2008.06.012

M. Mattoso, C. Werner, G. H. Travassos, V. Braganholo, L. Murta et al., Towards supporting the life cycle of large scale scientific experiments, International Journal of Business Process Integration and Management, vol.5, issue.1, pp.79-92, 2010.
DOI : 10.1504/IJBPIM.2010.033176

D. Hull, K. Wolstencroft, R. Stevens, C. Goble, M. R. Pocock et al., Taverna: a tool for building and running workflows of services, Nucleic Acids Research, vol.34, issue.Web Server, pp.729-732, 2006.
DOI : 10.1093/nar/gkl320

I. Altintas, C. Berkley, E. Jaeger, M. Jones, B. Ludascher et al., Kepler: an extensible system for design and execution of scientific workflows. Scientific and Statistical Database Management, pp.423-424, 2004.

S. P. Callahan, J. Freire, E. Santos, C. E. Scheidegger, C. T. Silva et al., VisTrails, Proceedings of the 2006 ACM SIGMOD international conference on Management of data , SIGMOD '06, pp.745-747, 2006.
DOI : 10.1145/1142473.1142574

Y. Gil, V. Ratnakar, E. Deelman, G. Mehta, and J. Kim, Wings for Pegasus: Creating Large-Scale Scientific Applications Using Semantic Representations of Computational Workflows, The National Conference On Artificial Intelligence, pp.1767-1774, 2007.

Y. Zhao, M. Hategan, B. Clifford, I. Foster, G. Von-laszewski et al., Swift: Fast, Reliable, Loosely Coupled Parallel Computation, 2007 IEEE Congress on Services (Services 2007), 2007.
DOI : 10.1109/SERVICES.2007.63

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.379.4068

E. Walker and C. Guiang, Challenges in executing large parameter sweep studies across widely distributed computing environments. Workshop on Challenges of large applications in distributed environments, pp.11-18, 2007.

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

E. Ogasawara, D. Oliveira, F. Chirigati, C. E. Barbosa, R. Elias et al., Exploring many task computing in scientific workflows, Proceedings of the 2nd Workshop on Many-Task Computing on Grids and Supercomputers, MTAGS '09, pp.1-10, 2009.
DOI : 10.1145/1646468.1646470

M. T. Özsu and P. Valduriez, Principles of Distributed Database Systems, 2011.

N. Russell, A. H. Ter-hofstede, W. M. Van-der-aalst, and N. Mulyar, Workflow control-flow patterns: A revised view

I. Foster and C. Kesselman, The Grid: Blueprint for a New Computing Infrastructure, 2004.

L. M. Vaquero, L. Rodero-merino, J. Caceres, and M. Lindner, A break in the clouds, ACM SIGCOMM Computer Communication Review, vol.39, issue.1, pp.50-55, 2009.
DOI : 10.1145/1496091.1496100

W. Gropp, E. L. Lusk, and A. Skjellum, Using MPI -2nd Edition: Portable Parallel Programming with the Message Passing Interface, 1999.

I. Raicu, I. T. Foster, and Y. Zhao, Many-task computing for grids and supercomputers, 2008 Workshop on Many-Task Computing on Grids and Supercomputers, pp.1-11, 2008.
DOI : 10.1109/MTAGS.2008.4777912

L. Bouganim, D. Florescu, and P. Valduriez, Dynamic load balancing in hierarchical parallel database systems, Proceedings of the 22nd International Conference on Very Large Databases, pp.436-447, 1996.
URL : https://hal.archives-ouvertes.fr/inria-00073877

S. Bharathi, A. Chervenak, E. Deelman, G. Mehta, M. Su et al., Characterization of scientific workflows, 2008 Third Workshop on Workflows in Support of Large-Scale Science, pp.1-10, 2008.
DOI : 10.1109/WORKS.2008.4723958

E. Ogasawara, J. Dias, D. Oliveira, F. Porto, P. Valduriez et al., An Algebraic Approach for Data-Centric Scientific Workflows, Proc. of VLDB Endowment22] ProvChallenge. Provenance Challenge Wiki, pp.1328-1339, 2010.
URL : https://hal.archives-ouvertes.fr/hal-00640431

F. Coutinho, E. Ogasawara, D. Oliveira, V. Braganholo, A. A. Lima et al., Many task computing for orthologous genes identification in protozoan genomes using Hydra, Concurrency and Computation: Practice and Experience, pp.232326-2337, 2011.
DOI : 10.1002/cpe.1786

H. González-vélez and M. Leyton, A survey of algorithmic skeleton frameworks: high-level structured parallel programming enablers, Software: Practice and Experience, vol.21, issue.6, pp.1135-1160, 2010.
DOI : 10.1002/spe.1026

W. Van-der-aalst, A. Hofstede, B. Kiepuszewski, and A. Barros, Workflow patterns. Distributed and Parallel Databases, pp.5-51, 2003.

S. Callaghan, P. Maechling, P. Small, K. Milner, G. Juve et al., Metrics for heterogeneous scientific workflows: A case study of an earthquake science application, International Journal of High Performance Computing Applications, vol.25, issue.3, pp.274-285, 2011.
DOI : 10.1177/1094342011414743

J. Yu and R. Buyya, A Taxonomy of Workflow Management Systems for Grid Computing, Journal of Grid Computing, vol.15, issue.5???6, pp.171-200, 2006.
DOI : 10.1007/s10723-005-9010-8

R. Prodan and T. Fahringer, Dynamic scheduling of scientific workflow applications on the grid, Proceedings of the 2005 ACM symposium on Applied computing , SAC '05, pp.687-694, 2005.
DOI : 10.1145/1066677.1066835

C. Pautasso and G. Alonso, Parallel computing patterns for Grid workflows Workflows in Support of Large-Scale Science, WORKS '06. Workshop on, pp.1-10, 2006.

D. Abramson, C. Enticott, and I. Altinas, Nimrod/K: Towards massively parallel dynamic Grid workflows, 2008 SC, International Conference for High Performance Computing, Networking, Storage and Analysis, pp.1-11, 2008.
DOI : 10.1109/SC.2008.5215726

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.422.2120

E. Deelman, G. Mehta, G. Singh, M. Su, and K. Vahi, Pegasus: Mapping Large-Scale Workflows to Distributed Resources. Workflows for e-Science, 32] SWB. SWB -Homepage, pp.376-394, 2007.
DOI : 10.1007/978-1-84628-757-2_23

D. Thain, J. Bent, A. C. Arpaci-dusseau, R. H. Arpaci-dusseau, and M. Livny, Pipeline and batch sharing in grid workloads, High Performance Distributed Computing, 2003. Proceedings. 12th IEEE International Symposium on, pp.152-161, 2003.
DOI : 10.1109/HPDC.2003.1210025

S. Ostermann, R. Prodan, T. Fahringer, R. Iosup, and D. Epema, On the Characteristics of Grid Workflows, Proceedings of the CoreGRID Workshop on Integrated Research in Grid Computing (CGIW'08), pp.431-442, 2008.

M. Gillmann, R. Mindermann, and G. Weikum, Benchmarking and Configuration of Workflow Management Systems, Cooperative Information Systems, 7th International Conference, pp.186-197, 2000.
DOI : 10.1007/10722620_19

P. Vassiliadis, A. Karagiannis, V. Tziovara, and A. , Simitsis, and I. Hellas. Towards a Benchmark for ETL Workflows, 2007.

A. Goderis, U. Sattler, P. Lord, and C. Goble, Seven Bottlenecks to Workflow Reuse and Repurposing. The Semantic Web ? ISWC, pp.323-337, 2005.

B. F. Cooper, A. Silberstein, E. Tam, R. Ramakrishnan, and R. Sears, Benchmarking cloud serving systems with YCSB, Proceedings of the 1st ACM symposium on Cloud computing, SoCC '10, pp.143-154, 2010.
DOI : 10.1145/1807128.1807152

A. Petitet, R. Whaley, J. Dongarra, and A. Cleary, HPL -A Portable Implementation of the High-Performance Linpack Benchmark for Distributed-Memory Computers Available at, 2010.

D. H. Bailey, E. Barszcz, J. T. Barton, D. S. Browning, R. L. Carter et al., The Nas Parallel Benchmarks, International Journal of High Performance Computing Applications, vol.5, issue.3, pp.63-73, 1991.
DOI : 10.1177/109434209100500306

K. Kim, K. Jeon, H. Han, S. Kim, H. Jung et al., MRBench: A Benchmark for MapReduce Framework, 2008 14th IEEE International Conference on Parallel and Distributed Systems, pp.11-18, 2008.
DOI : 10.1109/ICPADS.2008.70

S. Huang, J. Huang, J. Dai, T. Xie, and B. Huang, The HiBench benchmark suite: Characterization of the MapReduce-based data analysis, IEEE 26th International Conference on Data Engineering Workshops (ICDEW), pp.41-51, 2010.