S. Gilbert and N. Lynch, Brewer's conjecture and the feasibility of consistent, available, partition-tolerant web services, ACM SIGACT News, vol.33, issue.2, pp.51-59, 2002.
DOI : 10.1145/564585.564601

Y. Koren, Factorization meets the neighborhood, Proceeding of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining, KDD 08, pp.426-434, 2008.
DOI : 10.1145/1401890.1401944

E. Torres, G. Molto, D. Segrelles, and I. Blanquer, A replicated information system to enable dynamic collaborations in the Grid, Concurrency and Computation: Practice and Experience, vol.25, issue.8, pp.1668-1683, 2012.
DOI : 10.1002/cpe.1915

S. Venugopal, R. Buyya, and K. Ramamohanarao, A taxonomy of Data Grids for distributed data sharing, management, and processing, ACM Computing Surveys, vol.38, issue.1, 2006.
DOI : 10.1145/1132952.1132955

W. Zhou, Fault management in distributed systems, 2010.

I. Rish, M. Brodie, S. Ma, N. Odintsova, A. Beygelzimer et al., Adaptive Diagnosis in Distributed Systems, IEEE Transactions on Neural Networks, vol.16, issue.5, pp.1088-1109, 2005.
DOI : 10.1109/TNN.2005.853423

P. Barham, A. Donnelly, R. Isaacs, and R. Mortier, Using magpie for request extraction and workload modelling, OSDI, pp.18-18, 2004.

M. Y. Chen, E. Kiciman, E. Fratkin, A. Fox, and E. Brewer, Pinpoint: problem determination in large, dynamic Internet services, Proceedings International Conference on Dependable Systems and Networks, pp.595-604, 2002.
DOI : 10.1109/DSN.2002.1029005

P. Reynolds, C. E. Killian, J. L. Wiener, J. C. Mogul, M. A. Shah et al., Pip: Detecting the unexpected in distributed systems, NSDI, pp.115-128, 2006.

R. Fonseca, G. Porter, R. H. Katz, S. Shenker, and I. Stoica, X-trace: A pervasive network tracing framework, Proceedings of the 4th USENIX conference on Networked systems design & implementation. USENIX Association, pp.20-20, 2007.

X. Liu, Z. Guo, X. Wang, F. Chen, X. Lian et al., D3s: Debugging deployed distributed systems, NSDI, pp.423-437, 2008.

]. D. Geels, G. Altekar, P. Maniatis, T. Roscoe, and I. Stoica, Friday: Global comprehension for distributed replay, NSDI, pp.285-298, 2007.

X. Liu, W. Lin, A. Pan, and Z. Zhang, Wids checker: Combating bugs in distributed systems, NSDI, 2007.

C. Killian, J. W. Anderson, R. Jhala, and A. Vahdat, Life, death, and the critical transition: Finding liveness bugs in systems code, NSDI 07: Networked Systems Design and Implementation, pp.243-256, 2007.

A. Quiroz, M. Parashar, N. Gnanasambandam, and N. Sharma, Design and evaluation of decentralized online clustering, ACM Transactions on Autonomous and Adaptive Systems, vol.7, issue.3, pp.1-3431, 2012.
DOI : 10.1145/2348832.2348837

X. Zhang, C. Furtlehner, C. Germain-renaud, and M. Sebag, Data Stream Clustering With Affinity Propagation, IEEE Transactions on Knowledge and Data Engineering, vol.26, issue.7, 2014.
DOI : 10.1109/TKDE.2013.146

URL : https://hal.archives-ouvertes.fr/hal-00862941

D. Feng, C. Germain-renaud, and T. Glatard, Efficient distributed monitoring with active Collaborative Prediction, Future Generation Computer Systems, vol.29, issue.8, pp.2272-2283, 2013.
DOI : 10.1016/j.future.2013.06.001

URL : https://hal.archives-ouvertes.fr/hal-00784038

I. Rish and G. Tesauro, Estimating End-to-End Performance by Collaborative Prediction with Active Sampling, 2007 10th IFIP/IEEE International Symposium on Integrated Network Management, pp.294-303, 2007.
DOI : 10.1109/INM.2007.374794

E. J. Candès and T. Tao, The Power of Convex Relaxation: Near-Optimal Matrix Completion, IEEE Transactions on Information Theory, vol.56, issue.5, pp.2053-2080, 2010.
DOI : 10.1109/TIT.2010.2044061

B. Recht, A simpler approach to matrix completion, J. Mach. Learn. Res, vol.12, pp.3413-3430, 2011.

N. Srebro, J. D. Rennie, and T. S. Jaakola, Maximum-margin matrix factorization, Advances in Neural Information Processing Systems 17, pp.1329-1336, 2005.

E. Laure, Programming the Grid with gLite*, Computational Methods in Science and Technology, vol.12, issue.1, pp.33-45, 2006.
DOI : 10.12921/cmst.2006.12.01.33-45

I. Foster, The globus toolkit for grid computing, Proceedings First IEEE/ACM International Symposium on Cluster Computing and the Grid, 2001.
DOI : 10.1109/CCGRID.2001.923160

M. Ellert, Advanced Resource Connector middleware for lightweight computational Grids, Future Generation Computer Systems, vol.23, issue.2, pp.219-240, 2007.
DOI : 10.1016/j.future.2006.05.008

A. Tsaregorodtsev, DIRAC3 ??? the new generation of the LHCb grid software, Journal of Physics: Conference Series, vol.219, issue.6, p.62029, 2009.
DOI : 10.1088/1742-6596/219/6/062029

URL : https://hal.archives-ouvertes.fr/in2p3-00383712

J. T. Moscicki, Diane -distributed analysis environment for gridenabled simulation and analysis of physics data, Nuclear Science Symposium Conference Record, pp.1617-1620, 2003.

S. Bagnasco, AliEn: ALICE environment on the GRID, Journal of Physics: Conference Series, vol.119, issue.6, p.62012, 2008.
DOI : 10.1088/1742-6596/119/6/062012

URL : http://cds.cern.ch/record/1069097/files/Poster-2007-012.pdf

T. Maeno, PanDA: distributed production and distributed analysis system for ATLAS, Journal of Physics: Conference Series, vol.119, issue.6, p.62036, 2008.
DOI : 10.1088/1742-6596/119/6/062036

S. Andreozzi, Glue Schema Specification, V.2.0, Open Grid Forum, 2009.

T. Joachims, A support vector method for multivariate performance measures, Proceedings of the 22nd international conference on Machine learning , ICML '05, pp.377-384, 2005.
DOI : 10.1145/1102351.1102399

C. Scott, Performance Measures for Neyman–Pearson Classification, IEEE Transactions on Information Theory, vol.53, issue.8, pp.2852-2863, 2007.
DOI : 10.1109/TIT.2007.901152

D. Feng, Efficient end-to-end monitoring for fault management in distributed systems, 2014.
URL : https://hal.archives-ouvertes.fr/tel-01017083

J. D. Rennie and N. Srebro, Fast maximum margin matrix factorization for collaborative prediction, Proceedings of the 22nd international conference on Machine learning , ICML '05, pp.713-719, 2005.
DOI : 10.1145/1102351.1102441

W. Wang and M. Sebag, Hypervolume indicator and dominance reward based multi-objective Monte-Carlo Tree Search, Machine Learning, pp.403-429, 2013.
DOI : 10.1007/s10994-013-5369-0

URL : https://hal.archives-ouvertes.fr/hal-00852048