J. Santos, T. Wauters, B. Volckaert, and F. De-turck, Towards network-aware resource provisioning in Kubernetes for fog computing applications, Proc. IEEE NetSoft, 2019.

F. Rossi, V. Cardellini, F. L. Presti, and M. Nardelli, Geodistributed efficient deployment of containers with Kubernetes, Computer Communications, vol.159, 2020.

C. Wöbker, A. Seitz, H. Mueller, and B. Bruegge, Fogernetes: Deployment and management of fog computing applications, Proc. IEEE/IFIP NOMS, 2018.

S. Noghabi, L. Cox, S. Agarwal, and G. Ananthanarayanan, The emerging landscape of edge computing, GetMobile: Mobile Computing and Communications, vol.23, issue.4, 2020.

Y. Zhu, J. Liu, M. Guo, Y. Bao, W. Ma et al., BestConfig: Tapping the performance potential of systems via automatic configuration tuning, Proc. ACM SoCC, 2017.

B. Burns, B. Grant, D. Oppenheimer, E. Brewer, and J. Wilkes, ACM Queue, vol.14, issue.1, 2016.

S. Kubernetes and . Multicluster, Kubernetes cluster federation, p.2020

J. O. Kephart and D. M. Chess, The vision of autonomic computing, Computer, vol.36, issue.1, 2003.

A. G. Ganek and T. A. Corbi, The dawning of the autonomic computing era, IBM systems Journal, vol.42, issue.1, 2003.

H. Chen, G. Jiang, H. Zhang, and K. Yoshihira, Boosting the performance of computing systems through adaptive configuration tuning, Proc. ACM SAC, 2009.

W. Zheng, R. Bianchini, and T. D. Nguyen, MassConf: Automatic configuration tuning by leveraging user community information, Proc. ACM/SPEC ICPE, 2011.

S. Bouchenak, N. Palma, D. Hagimont, and C. Taton, Autonomic management of clustered applications, Proc. IEEE Cluster, 2006.
URL : https://hal.archives-ouvertes.fr/hal-00684406

M. Li, L. Zeng, S. Meng, J. Tan, L. Zhang et al., MRONLINE: MapReduce online performance tuning, Proc. ACM HPDC, 2014.

G. Wang, J. Xu, and B. He, A novel method for tuning configuration parameters of Spark based on machine learning, Proc. IEEE HPCC/SmartCity/DSS, 2016.

D. Van-aken, A. Pavlo, G. J. Gordon, and B. Zhang, Automatic database management system tuning through large-scale machine learning, Proc. ACM SIGMOD, 2017.

L. Bao, X. Liu, Z. Xu, and B. Fang, AutoConfig: Automatic configuration tuning for distributed message systems, Proc. ASE, 2018.

D. Menascé, D. Barbará, and R. Dodge, Preserving QoS of e-commerce sites through self-tuning: A performance model approach, Proc. ACM EC, 2001.

N. Gandhi, D. M. Tilbury, Y. Diao, J. Hellerstein, and S. Parekh, MIMO control of an Apache web server: Modeling and controller design, Proc. IEEE ACC, 2002.

Y. Diao, N. Gandhi, J. L. Hellerstein, S. Parekh, and D. M. Tilbury, Using MIMO feedback control to enforce policies for interrelated metrics with application to the Apache web server, Proc. IEEE/IFIP NOMS, 2002.

K. Ye and Y. Ji, Performance tuning and modeling for big data applications in Docker containers, Proc. NAS, 2017.

T. Chiba, R. Nakazawa, H. Horii, S. Suneja, and S. Seelam, ConfAdvisor: A performance-centric configuration tuning framework for containers on Kubernetes, Proc. IEEE IC2E, 2019.

W. Chen, S. Toueg, and M. K. Aguilera, On the quality of service of failure detectors, IEEE Transactions on computers, vol.51, issue.5, 2002.

F. Lima and R. Macêdo, Adapting failure detectors to communication network load fluctuations using SNMP and artificial neural nets, Proc. LADC, 2005.

R. C. Nunes and I. Jansch-porto, QoS of timeout-based selftuned failure detectors: The effects of the communication delay predictor and the safety margin, Proc. DSN, 2004.

L. Falai and A. Bondavalli, Experimental evaluation of the QoS of failure detectors on wide area network, Proc. DSN, 2005.

A. S. De-sá and R. J. Macêdo, QoS self-configuring failure detectors for distributed systems, Proc. IFIP DAIS, 2010.

D. Balouek, A. Carpen-amarie, G. Charrier, F. Desprez, E. Jeannot et al., Adding virtualization capabilities to the Grid'5000 testbed, Cloud Computing and Services Science, vol.367, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00946971

F. P. Tso, D. R. White, S. Jouet, J. Singer, and D. P. Pezaros, The Glasgow Raspberry Pi cloud: A scale model for cloud computing infrastructures, Proc. ICDCS Workshops, 2013.

A. Van-kempen, T. Crivat, B. Trubert, D. Roy, and G. Pierre, MEC-ConPaaS: An experimental single-board based mobile edge cloud, Proc. IEEE Mobile Cloud Conference, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01446483

P. K. Janert, Feedback control for computer systems: introducing control theory to enterprise programmers, 2013.

J. G. Ziegler and N. B. Nichols, Optimum settings for automatic controllers, Trans. of the ASME, vol.64, 1942.