M. D. Dikaiakos, D. Katsaros, P. Mehra, G. Pallis, and A. Vakali, Cloud Computing: Distributed Internet Computing for IT and Scientific Research, IEEE Internet Computing, vol.13, issue.5, pp.10-13, 2009.
DOI : 10.1109/MIC.2009.103

A. Danak and S. Mannor, Efficient Bidding in Dynamic Grid Markets, IEEE Transactions on Parallel and Distributed Systems, vol.22, issue.9, pp.1483-1496, 2011.
DOI : 10.1109/TPDS.2011.29

Y. Lan, W. Tong, Z. Liu, and Y. Hou, Multi-unit continuous double auction based resource allocation method, 2012 Third International Conference on Intelligent Control and Information Processing, pp.773-777, 2012.
DOI : 10.1109/ICICIP.2012.6391559

Z. Tan and J. R. Gurd, Market-based grid resource allocation using a stable continuous double auction, 2007 8th IEEE/ACM International Conference on Grid Computing, pp.283-290, 2007.
DOI : 10.1109/GRID.2007.4354144

R. Prodan, M. Wieczorek, and H. M. Frad, Double Auction-based Scheduling of Scientific Applications in Distributed Grid and Cloud Environments, Journal of Grid Computing, vol.3, issue.3???4, pp.531-548, 2011.
DOI : 10.1007/s10723-011-9196-x

F. Teng and F. Magoules, Resource Pricing and Equilibrium Allocation Policy in Cloud Computing, 2010 10th IEEE International Conference on Computer and Information Technology, pp.195-202, 2010.
DOI : 10.1109/CIT.2010.70

URL : https://hal.archives-ouvertes.fr/hal-00828268

A. Mutz and R. Wolski, Efficient auction-based grid reservations using dynamic programming, 2008 SC, International Conference for High Performance Computing, Networking, Storage and Analysis, pp.1-8, 2008.
DOI : 10.1109/SC.2008.5219747

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.571.6549

L. J. Wang and M. Q. Meng, A game theoretical bandwidth allocation mechanism for cloud robotics, Proceedings of the 10th World Congress on Intelligent Control and Automation, pp.3828-3833, 2012.
DOI : 10.1109/WCICA.2012.6359111

S. Rajasegarar, C. Leckie, J. C. Bezdek, and M. Palaniswami, Centered Hyperspherical and Hyperellipsoidal One-Class Support Vector Machines for Anomaly Detection in Sensor Networks, IEEE Transactions on Information Forensics and Security, vol.5, issue.3, pp.518-533, 2010.
DOI : 10.1109/TIFS.2010.2051543

Y. Z. Xing, On Issues and Applications for Least Squares Support Vector Machine, Nanjing University of Science and Technology, 2009.

Y. H. Zweiri, L. D. Seneviratne, and K. Althoefer, Stability analysis of a three-term backpropagation algorithm, Neural Networks, vol.18, issue.10, pp.1341-1347, 2005.
DOI : 10.1016/j.neunet.2005.04.007

S. Suresh, S. N. Omkar, and V. Mani, Parallel implementation of back-propagation algorithm in networks of workstations, IEEE Transactions on Parallel and Distributed Systems, vol.16, issue.1, pp.24-34, 2005.
DOI : 10.1109/TPDS.2005.11

F. Zhang and H. Y. Chang, Employing BP Neural Networks to Alleviate the Sparsity Issue in Collaborative Filtering Recommendation Algorithms, Journal of Computer Research and Development, vol.43, issue.4, pp.667-672, 2006.
DOI : 10.1360/crad20060415

L. Li, The Research of Intrusion Detection Technology Based on Artificial Neural Network, National University of Defense Technology, 2008.

A. Azamimi, Y. Uwate, and Y. Nishio, Effect of chaos noise on the learning ability of back propagation algorithm in feed forward neural network, 2010 6th International Colloquium on Signal Processing & its Applications, pp.1-4, 2010.
DOI : 10.1109/CSPA.2010.5545250

I. Erlich, G. K. Venayagamoorthy, and N. Worawat, A Mean-Variance Optimization algorithm, IEEE Congress on Evolutionary Computation, pp.1-6, 2010.
DOI : 10.1109/CEC.2010.5586027