M. Avgerinou, P. Bertoldi, and L. Castellazzi, Trends in Data Centre Energy Consumption under the European Code of Conduct for Data Centre Energy Efficiency, 2017.

C. Reiss, J. Wilkes, and J. L. Hellerstein, Google cluster-usage traces: format + schema, 2011.

J. Wilkes, More Google cluster data, Google research blog, 2011.

B. Liu, Y. Lin, and Y. Chen, Quantitative workload analysis and prediction using Google cluster traces, 2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), pp.935-940, 2016.

J. J. Prevost, K. Nagothu, B. Kelley, and M. Jamshidi, Prediction of cloud data center networks loads using stochastic and neural models, 6th International Conference on System of Systems Engineering, pp.276-281, 2011.

M. S. Yoon, A. E. Kamal, and Z. Zhu, Adaptive data center activation with user request prediction, Comput Netw, vol.122, pp.191-204, 2017.

S. Mazumdar and A. S. Kumar, Forecasting Data Center Resource Usage: An Experimental Comparison with Time-Series Methods, Proceedings of the Eighth International Conference on Soft Computing and Pattern Recognition, 2016.

N. Ben-hassine, R. Milocco, and P. Minet, ARMA based Popularity Prediction for Caching in Content Delivery Networks, IEEE Communications Society, 2017.

M. Alam, K. A. Shakil, and S. Sethi, Analysis and Clustering of Workload in Google Cluster Trace based on Resource Usage, 2015.

O. Beaumont, L. Eyraud-dubois, and J. A. Lorenzo-del-castillo, Analyzing real cluster data for formulating allocation algorithms in Cloud platforms, 2nd International Symposium on Computer architecture and High Performance Computing (SBAC-PAD), 2014.
URL : https://hal.archives-ouvertes.fr/hal-01094388

C. Reiss, A. Tumanov, G. R. Ganger, R. H. Katz, and M. A. Kozuch, Heterogeneity and dynamicity of clouds at scale: Google trace analysis, ACM Symposium on Cloud Computing (SoCC), 2012.

S. Yousif and . Al-dulaimy, Clustering Cloud Workload Traces to Improve the Performance of Cloud Data Centers, Proceedings of the World Congress on Engineering, 2017.

S. Di, D. Kondo, and W. Cirne, Host Load Prediction in a Google Compute Cloud with a Bayesian Model, Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis, SC'12, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00788002

P. Minet, E. Renault, I. Khoufi, and S. Boumerdassi, Analyzing traces from a Google data center, 14th International Wireless Communications and Mobile Computing Conference (IWCMC 2018), 2018.
URL : https://hal.archives-ouvertes.fr/hal-01870216

C. Liu, Y. Wan, L. Tian, Y. Zhou, and J. Shi, Base station sleeping control with energy-stability tradeoff in centralized radio access networks, IEEE Global Communications Conference (GLOBECOM), 2015.

K. Boulos, M. E. Helou, M. Ibrahim, K. Khawam, H. Sawaya et al., Interference-aware clustering in cloud radio access networks, 2017 IEEE 6th International Conference on Cloud Networking (CloudNet), 2017.

D. G. Manolakis, K. Vinay, S. M. Ingle, and . Kogon, Statistical and Adaptive Signal Processing

L. Ljung, System Identification: Theory for the User, 1999.

C. W. Granger, Investigating Causal Relations by Econometric Models and Cross-spectral Methods, Econometrica, vol.37, issue.3, pp.424-438, 1969.