. Auvergrid, 4] Sharcnet grid project: online at https://www

. Llnl, Grid workloads archive (gwa): online at http://gwa.ewi.tudelft.nl/pmwiki/. [10] Parallel workload archive (pwa): online at http

D. G. Feitelson, Workload Modeling for Computer Systems Performance Evaluation, 2011.
DOI : 10.1017/CBO9781139939690

R. Koch, The 80/20 principle: the secret of achieving more with less, 1997.

R. K. Jain, The Art of Computer Systems Performance Analysis: Techniques for Experimental Design, Measurement, Simulation and Modelling, 1991.

P. S. Diniz, Adaptive Filtering: Algorithms and Practical Implementation, softcover reprint of hardcover 3rd ed, 2008.

B. Sharma, V. Chudnovsky, J. L. Hellerstein, R. Rifaat, and C. R. Das, Modeling and synthesizing task placement constraints in Google compute clusters, Proceedings of the 2nd ACM Symposium on Cloud Computing, SOCC '11, pp.1-3, 2011.
DOI : 10.1145/2038916.2038919

H. Li, Workload dynamics on clusters and grids, The Journal of Supercomputing, vol.81, issue.10, pp.1-20, 2009.
DOI : 10.1007/s11227-008-0189-x

H. Li, R. Heusdens, M. Muskulus, and L. Wolters, Analysis and synchesis of pseudo-periodic job arrivals in grids: A matching pursuit approach, 7th IEEE International Symposium on Cluster Computing and the Grid (CCGrid07), pp.183-196, 2007.

E. Afgan and P. Bangalore, Exploiting performance characterization of BLAST in the grid, Cluster Computing, vol.25, issue.6, 2010.
DOI : 10.1007/s10586-010-0121-z

D. Kondo, G. Fedak, F. Cappello, A. A. Chien, and H. Casanova, Characterizing resource availability in enterprise desktop grids, Future Generation Computer Systems, vol.23, issue.7, pp.888-903, 2006.
DOI : 10.1016/j.future.2006.11.001

B. Calder, A. A. Chien, J. Wang, and D. Yang, The entropia virtual machine for desktop grids, Proceedings of the 1st ACM/USENIX international conference on Virtual execution environments , VEE '05, pp.186-196, 2005.
DOI : 10.1145/1064979.1065005

C. Germain, V. Néri, G. Fedak, and F. Cappello, XtremWeb: Building an Experimental Platform for Global Computing, 1st ACM/IEEE International Conference on Grid Computing, pp.91-101, 2000.
DOI : 10.1007/3-540-44444-0_9
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.22.7358

Q. Zhang, J. L. Hellerstein, and R. Boutaba, Characterizing task usage shapes in google compute clusters, Large Scale Distributed Systems and Middleware Workshop (LADIS'11), 2011.

B. J. Barnes, B. Rountree, D. K. Lowenthal, J. Reeves, B. De-supinski et al., A regression-based approach to scalability prediction, Proceedings of the 22nd annual international conference on Supercomputing , ICS '08, pp.368-377, 2008.
DOI : 10.1145/1375527.1375580

A. Khan, X. Yan, S. Tao, and N. Anerousis, Workload characterization and prediction in the cloud: A multiple time series approach, 2012 IEEE Network Operations and Management Symposium, 2012.
DOI : 10.1109/NOMS.2012.6212065