C. Hava-muntean and J. Mcmanis, Fine grained content-based adaptation mechanism for providing high end-user quality of experience with adaptive hypermedia systems, ACM Proc. of the 15th Int. Conf. on World Wide Web WWW, pp.53-62, 2006.

A. Vetro and C. Timmerer, Digital item adaptation: overview of standardization and research activities, IEEE Trans. Multimedia, vol.7, issue.3, pp.418-426, 2005.

R. K. Mok, W. Li, and R. K. Chang, IRate: Initial Video Bitrate Selection System for HTTP Streaming, IEEE Journal on Selected Areas in Communications, vol.34, issue.6, pp.1914-1928, 2016.
DOI : 10.1109/jsac.2016.2559078

M. Nagy, V. Singh, J. Ott, and L. Eggert, Congestion control using FEC for conversational multimedia communication, Proc. of ACM Multimedia Systems Conference (MMSys), pp.191-202, 2014.
DOI : 10.1145/2557642.2557649

URL : http://arxiv.org/pdf/1310.1582

W. Cai, R. Shea, C. Huang, K. Chen, J. Liu et al., A Survey on Cloud Gaming: Future of Computer Games, vol.4, pp.7605-7620, 2016.

T. Huang, R. Johari, N. Mckeown, M. Trunnell, and M. Watson, A bufferbased approach to rate adaptation: Evidence from a large video streaming service, ACM SIGCOMM Computer Communication Review, vol.44, issue.4, pp.187-198, 2015.

J. Chen, R. Mahindra, M. A. Khojastepour, S. Rangarajan, and M. Chiang, A scheduling framework for adaptive video delivery over cellular networks, 2013.
DOI : 10.1145/2500423.2500433

X. K. Zou, J. Erman, V. Gopalakrishnan, E. Halepovic, R. Jana et al., Can accurate predictions improve video streaming in cellular networks?, 2015.

F. Lu, H. Du, A. Jain, G. M. Voelker, A. C. Snoeren et al., CQIC: Revisiting Cross-Layer Congestion Control for Cellular Networks, 2015.

A. Samba, Y. Busnel, A. Blanc, P. Dooze, and G. Simon, Instantaneous Throughput Prediction in Cellular Networks: Which Information Is Needed?, IFIP/IEEE International Symposium on, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01535696

M. Mathis, J. Semke, J. Mahdavi, and T. Ott, The Macroscopic Behavior of the TCP Congestion Avoidance Algorithm, SIGCOMM Comput, Commun. Rev, vol.27, issue.3

J. Padhye, V. Firoiu, D. F. Towsley, and J. F. Kurose, Modeling TCP Reno Performance: A Simple Model and Its Empirical Validation, IEEE/ACM
DOI : 10.1109/90.842137

, Trans. Netw, vol.8, issue.2, pp.133-145, 2000.

N. Cardwell, S. Savage, T. Anderson, T. Modeling, and . Latency, Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies, vol.3, pp.1742-1751, 2000.

B. Sikdar, S. Kalyanaraman, and K. S. Vastola, Analytic models for the latency and steady-state throughput of TCP Tahoe, Reno, and SACK, IEEE/ACM Transactions On Networking, vol.11, issue.6, pp.959-971, 2003.

R. Prasad, C. Dovrolis, M. Murray, and K. Claffy, Bandwidth estimation: metrics, measurement techniques, and tools, IEEE Network, vol.17, issue.6, pp.27-35, 2003.

N. Bui, F. Michelinakis, and J. Widmer, A Model for Throughput Prediction for Mobile Users, 2014.

F. Ren and C. Lin, Modeling and Improving TCP Performance over Cellular Link with Variable Bandwidth, IEEE Transactions on Mobile Computing, vol.10, issue.8, pp.1057-1070, 2011.
DOI : 10.1109/tmc.2010.234

Q. He, C. Dovrolis, and M. Ammar, On the predictability of large transfer TCP throughput, ACM SIGCOMM Computer Communication Review, vol.35, pp.145-156, 2005.

M. Mirza, J. Sommers, P. Barford, and X. Zhu, A Machine Learning Approach to TCP Throughput Prediction, ACM Sigmetrics conference, 2007.
DOI : 10.1109/tnet.2009.2037812

Q. Xu, S. Mehrotra, Z. Mao, and J. Li, PROTEUS: Network Performance Forecast for Real-time, Interactive Mobile Applications, 2013.

J. Jiang, V. Sekar, and H. Zhang, Improving fairness, efficiency, and stability in http-based adaptive video streaming with festive, Proceedings of the 8th international conference on Emerging networking experiments and technologies, pp.97-108, 2012.

Z. Li, X. Zhu, J. Gahm, R. Pan, H. Hu et al., Probe and adapt: Rate adaptation for http video streaming at scale, IEEE Journal on Selected Areas in Communications, vol.32, issue.4, pp.719-733, 2014.
DOI : 10.1109/jsac.2014.140405

URL : http://arxiv.org/pdf/1305.0510

Y. Sun, X. Yin, J. Jiang, V. Sekar, F. Lin et al., Cs2p: Improving video bitrate selection and adaptation with data-driven throughput prediction, Proceedings of the 2016 conference on ACM SIGCOMM 2016 Conference, pp.272-285, 2016.

J. Yao, S. S. Kanhere, and M. Hassan, An empirical study of bandwidth predictability in mobile computing, ACM WINTECH workshop, 2008.

X. Xie, X. Zhang, S. Kumar, and L. E. Li, piStream: Physical layer informed adaptive video streaming over LTE, 2015.

S. Lederer, C. Müller, C. Timmerer, C. Concolato, J. L. Feuvre et al., Proc. of ACM Multimedia Systems Conference (MMSys), pp.131-135, 2013.

, Vision 360 Degres (V3D), 2016.

T. Everts, The average web page is 3MB. How much should we care, 2017.

, Technical Specification Group Radio Access Network

, User Equipment (UE) radio access capabilities

J. Postel, Transmission control protocol

X. Hu, X. Li, E. C. Ngai, V. C. Leung, and P. Kruchten, Multidimensional context-aware social network architecture for mobile crowdsensing, IEEE Communications Mag, vol.52, issue.6, pp.78-87, 2014.
DOI : 10.1109/mcom.2014.6829948

S. Hahn, D. Gotz, S. Lohmuller, L. Schmelz, A. Eisenblätter et al., Classification of Cells Based on Mobile Network Context Information for the Management of SON Systems, 2015.

S. Buuren and K. , Groothuis-Oudshoorn, mice: Multivariate imputation by chained equations in R, Journal of statistical software, vol.45, issue.3

A. Samba and . Linkspotter, , 2017.

. R-core-team, R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, 2016.

D. N. Reshef, Y. A. Reshef, H. K. Finucane, S. R. Grossman, G. Mcvean et al., Detecting novel associations in large data sets, science, vol.334, issue.6062, pp.1518-1524, 2011.
DOI : 10.1126/science.1205438

URL : http://apophenia.wikidot.com/local--files/start/reshef_2011_novel_associations.pdf

L. Breiman, Random forests, Machine learning, vol.45, issue.1, pp.5-32, 2001.

P. Mccullagh, Generalized linear models, European Journal of Operational Research, vol.16, issue.3, pp.285-292, 1984.

P. Geladi and B. R. Kowalski, Partial least-squares regression: a tutorial, Analytica chimica acta, vol.185, pp.1-17, 1986.

W. N. Venables and B. D. Ripley, Modern applied statistics with S-PLUS, 2013.

A. Liaw and M. Wiener, Classification and Regression by randomForest, R News, vol.2, issue.3, pp.18-22, 2002.

B. Mevik, R. Wehrens, and K. H. Liland, pls: Partial Least Squares and Principal Component regression, 2013.

B. Efron and R. J. Tibshirani, An introduction to the bootstrap, 1994.

S. B. Said, M. R. Sama, K. Guillouard, L. Suciu, G. Simon et al., New Control Plane in 3GPP LTE/EPC Architecture for OnDemand Connectivity Service, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00876149

J. Liu, G. Simon, C. Rosenberg, and G. Texier, Optimal Delivery of RateAdaptive Streams in Underprovisioned Networks, IEEE Journal on Selected Areas in Communications

V. K. Adhikari, Y. Guo, F. Hao, M. Varvello, V. Hilt et al.,

U. Zhang and . Netflix, Understanding and improving multi-CDN movie delivery, IEEE INFOCOM, 2012.

, ETSI, Digital cellular telecommunications system

, Telecommunication management; Subscriber and equipment trace; Trace data definition and management

E. Thomas, M. Van-deventer, T. Stockhammer, A. C. Begen, and J. Famaey, Enhancing MPEG DASH performance via server and network assistance

G. Cofano, L. De-cicco, T. Zinner, A. Nguyen-ngoc, P. Tran-gia et al., Design and Experimental Evaluation of Network-assisted Strategies for HTTP Adaptive Streaming, 2016.

J. Jiang, X. Liu, V. Sekar, I. Stoica, and H. Zhang, EONA: Experience-Oriented Network Architecture, 2014.