D. Ungar, Generation Scavenging, ACM SIGPLAN Notices, vol.19, issue.5, pp.157-167, 1984.
DOI : 10.1145/390011.808261

H. Lieberman and C. Hewitt, A real-time garbage collector based on the lifetimes of objects, Communications of the ACM, vol.26, issue.6, pp.419-429, 1983.
DOI : 10.1145/358141.358147

. Google, Available: https://github

M. Colmant, M. Kurpicz, P. Felber, L. Huertas, R. Rouvoy et al., Process-level power estimation in VM-based systems, Proceedings of the Tenth European Conference on Computer Systems, EuroSys '15, pp.141-1414, 2015.
DOI : 10.1145/2741948.2741971

URL : https://hal.archives-ouvertes.fr/hal-01132495

L. A. Barroso and U. Hölzle, The case for energyproportional computing, IEEE Computer, vol.40, 2007.

. Docker and . Swarm, Available: https://www.docker. com/products/docker-swarm

A. Verma, L. Pedrosa, M. Korupolu, E. Tune, and J. Wilkes, Large-scale cluster management at Google with Borg, Proceedings of the Tenth European Conference on Computer Systems, EuroSys '15, pp.1-1817, 2015.
DOI : 10.1145/2741948.2741964

. Ubuntu, Available: http://kernel.ubuntu. com/ ? cking/stress-ng [9] influxdata Available: https

. Swipely, Docker API Available: https://github. com/swipely

. Docker, Docker Remote API Available: https: //docs.docker.com/engine

. Resque, Available: https://github.com/ resque/resque [13] libvirt Available: https

. Docker, Scheduler Strategies Available: https: //docs.docker.com/swarm/scheduler/strategy [15] OpenNebula More Google cluster data Google research blog, 2011.

C. Reiss, J. Wilkes, and J. L. Hellerstein, Google clusterusage traces: format + schema, Google Inc, 2011.

C. Reiss, A. Tumanov, G. R. Ganger, R. H. Katz, and M. A. Kozuch, Heterogeneity and dynamicity of clouds at scale, Proceedings of the Third ACM Symposium on Cloud Computing, SoCC '12, 2012.
DOI : 10.1145/2391229.2391236

R. Buyya, D. Abramson, and J. Giddy, Nimrod/G: an architecture for a resource management and scheduling system in a global computational grid, Proceedings Fourth International Conference/Exhibition on High Performance Computing in the Asia-Pacific Region, pp.283-289, 2000.
DOI : 10.1109/HPC.2000.846563

T. Tannenbaum, D. Wright, K. Miller, and M. Livny, Condor: a distributed job scheduler, Beowulf cluster computing with Linux, pp.307-350, 2001.

D. Jackson, Q. Snell, and M. Clement, Core Algorithms of the Maui Scheduler, pp.87-102, 2001.
DOI : 10.1007/3-540-45540-X_6

N. Capit, G. Da-costa, Y. Georgiou, G. Huard, C. Martin et al., A batch scheduler with high level components, CCGrid 2005. IEEE International Symposium on Cluster Computing and the Grid, 2005., pp.776-783, 2005.
DOI : 10.1109/CCGRID.2005.1558641

URL : https://hal.archives-ouvertes.fr/hal-00005106

V. K. Vavilapalli, A. C. Murthy, C. Douglas, S. Agarwal, M. Konar et al., Apache Hadoop YARN, Proceedings of the 4th annual Symposium on Cloud Computing, SOCC '13, pp.1-5, 2013.
DOI : 10.1145/2523616.2523633

O. Litvinski and A. Gherbi, Openstack scheduler evaluation using design of experiment approach, 16th IEEE International Symposium on Object/component/service-oriented Real-time distributed Computing (ISORC 2013), pp.1-7, 2013.
DOI : 10.1109/ISORC.2013.6913212

B. Burns, B. Grant, D. Oppenheimer, E. Brewer, and J. W. Borg, Borg, Omega, and Kubernetes, Communications of the ACM, vol.59, issue.5, pp.50-57, 2016.
DOI : 10.1145/2890784

T. Knauth and C. Fetzer, Energy-aware scheduling for infrastructure clouds, 4th IEEE International Conference on Cloud Computing Technology and Science Proceedings, pp.58-65, 2012.
DOI : 10.1109/CloudCom.2012.6427569