A. Aamodt and E. Plaza, Case-based reasoning: Foundational issues, methodological variations, and system approaches, AI communications, vol.7, issue.1, pp.39-59, 1994.

D. Anicic, P. Fodor, S. Rudolph, R. Stühmer, N. Stojanovic et al., A Rule-Based Language for Complex Event Processing and Reasoning, International Conference on Web Reasoning and Rule Systems, pp.42-57, 2010.
DOI : 10.1007/978-3-642-15918-3_5

P. Arcaini, E. Riccobene, and P. Scandurra, Modeling and Analyzing MAPE-K Feedback Loops for Self-Adaptation, 2015 IEEE/ACM 10th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, 2015.
DOI : 10.1109/SEAMS.2015.10

G. S. Blair, N. Bencomo, and R. B. France, Models@ run.time, Computer, vol.42, issue.10, pp.22-27, 2009.
DOI : 10.1109/MC.2009.326
URL : https://hal.archives-ouvertes.fr/hal-00733338

A. Cimatti and A. Micheli, Strong temporal planning with uncontrollable durations, Proceedings of the Twenty- Ninth AAAI Conference on Artificial Intelligence, pp.3254-3260, 2015.
DOI : 10.1016/j.artint.2017.11.006

T. Hartmann, Enabling Model-Driven Live Analytics For Cyber-Physical Systems: The Case of Smart Grids, 2016.

T. Hartmann, F. Fouquet, M. Jimenez, R. Rouvoy, and Y. L. Traon, Analyzing Complex Data in Motion at Scale with Temporal Graphs, Proceedings of the 29th International Conference on Software Engineering and Knowledge Engineering, pp.596-601, 2017.
DOI : 10.18293/SEKE2017-048
URL : https://hal.archives-ouvertes.fr/hal-01511636

T. Hartmann, F. Fouquet, G. Nain, B. Morin, J. Klein et al., A Native Versioning Concept to Support Historized Models at Runtime, Model-Driven Engineering Languages and Systems -17th International Conference, pp.252-268, 2014.
DOI : 10.1007/978-3-319-11653-2_16
URL : https://hal.archives-ouvertes.fr/hal-01097020

K. Henricksen, J. Indulska, and A. Rakotonirainy, Modeling Context Information in Pervasive Computing Systems, Pervasive Computing, First International Conference Proceedings. 167?180, 2002.
DOI : 10.1007/3-540-45866-2_14
URL : http://espace.library.uq.edu.au/view/UQ:10713/Modeling_context_information___.pdf

M. Mao and M. Humphrey, A Performance Study on the VM Startup Time in the Cloud, 2012 IEEE Fifth International Conference on Cloud Computing, pp.423-430, 2012.
DOI : 10.1109/CLOUD.2012.103

M. Maurer, I. Breskovic, V. C. Emeakaroha, and I. Brandic, Revealing the MAPE loop for the autonomic management of Cloud infrastructures, 2011 IEEE Symposium on Computers and Communications (ISCC), 2011.
DOI : 10.1109/ISCC.2011.5984008

B. Morin, O. Barais, J. Jézéquel, F. Fleurey, and A. Solberg, Models@ Run.time to Support Dynamic Adaptation, Computer, vol.42, issue.10, pp.44-51, 2009.
DOI : 10.1109/MC.2009.327

G. Mulligan and D. Gra?anin, A comparison of SOAP and REST implementations of a service based interaction independence middleware framework, Proceedings of the 2009 Winter Simulation Conference (WSC), pp.1423-1432, 2009.
DOI : 10.1109/WSC.2009.5429290

S. Shen, V. Van-beek, and A. Iosup, Statistical Characterization of Business-Critical Workloads Hosted in Cloud Datacenters, 2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, pp.465-474, 2015.
DOI : 10.1109/CCGrid.2015.60

M. Norha, G. Villegas, . Tamura, A. Hausi, L. Müller et al., DYNAMICO: A reference model for governing control objectives and context relevance in self-adaptive software systems, Software Engineering for Self-Adaptive Systems II, pp.265-293, 2013.

H. Yuan, J. Bi, W. Tan, and B. H. Li, Temporal Task Scheduling With Constrained Service Delay for Profit Maximization in Hybrid Clouds, IEEE Transactions on Automation Science and Engineering, vol.14, issue.1, pp.337-348, 2017.
DOI : 10.1109/TASE.2016.2526781