, Network Functions Virtualisation (NFV): Architectural framework, ETSI GS NFV, vol.2, issue.2, p.1, 2013.

B. Yi, X. Wang, K. Li, S. K. Das, and M. Huang, A comprehensive survey of Network Function Virtualization, Computer Networks, vol.133, pp.212-262, 2018.

A. Gupta, B. Jaumard, M. Tornatore, and B. Mukherjee, A Scalable Approach for Service Chain Mapping With Multiple SC Instances in a Wide-Area Network, IEEE Journal on Selected Areas in Communications, vol.36, issue.3, pp.529-541, 2018.

I. Afolabi, T. Taleb, K. Samdanis, A. Ksentini, and H. Flinck, Network Slicing and Softwarization: A Survey on Principles, Enabling Technologies, and Solutions, IEEE Communications Surveys Tutorials, vol.20, issue.3, pp.2429-2453, 2018.

M. Mechtri, C. Ghribi, and D. Zeghlache, A Scalable Algorithm for the Placement of Service Function Chains, IEEE Transactions on Network and Service Management, vol.13, issue.3, pp.533-546, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01355234

S. Khebbache, M. Hadji, and D. Zeghlache, A multi-objective non-dominated sorting genetic algorithm for VNF chains placement, Proc. IEEE CCNC, pp.1-4, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01613473

S. Haeri and L. Trajkovi?, Virtual network embedding via Monte Carlo tree search, IEEE Transactions on Cybernetics, vol.48, issue.2, pp.510-521, 2018.

R. Riggio, A. Bradai, D. Harutyunyan, T. Rasheed, and T. Ahmed, Scheduling wireless virtual networks functions, IEEE Transactions on Network and Service Management, vol.13, issue.2, pp.240-252, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01292250

E. G. Coffman, M. R. Garey, and D. S. Johnson, Approximation Algorithms for NP-hard Problems, Approximation Algorithms for Bin Packing: A Survey, pp.46-93, 1997.

A. Tomassilli, F. Giroire, N. Huin, and S. Pérennes, Provably efficient algorithms for placement of service function chains with ordering constraints, IEEE INFOCOM 2018 -IEEE Conference on Computer Communications, pp.774-782, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01921112

M. C. Luizelli, L. R. Bays, L. S. Buriol, M. P. Barcellos, and L. P. Gaspary, Piecing together the NFV provisioning puzzle: Efficient placement and chaining of virtual network functions, Proc. IFIP/IEEE IM, pp.98-106, 2015.

I. Jang, D. Suh, S. Pack, and G. Dán, Joint optimization of service function placement and flow distribution for service function chaining, IEEE Journal on Selected Areas in Communications, vol.35, issue.11, pp.2532-2541, 2017.

H. Ko, D. Suh, H. Baek, S. Pack, and J. Kwak, Optimal placement of service function in service function chaining, Proc. ICUFN), pp.102-105, 2016.

Q. Zhang, Y. Xiao, F. Liu, J. C. Lui, J. Guo et al., Joint optimization of chain placement and request scheduling for network function virtualization, 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS), pp.731-741, 2017.

A. Shpiner, Z. Haramaty, S. Eliad, V. Zdornov, B. Gafni et al., Dragonfly+: Low cost topology for scaling datacenters, 2017 IEEE 3rd International Workshop on High-Performance Interconnection Networks in the Exascale and Big-Data Era (HiPINEB), pp.1-8, 2017.

A. Tomassilli, F. Giroire, N. Huin, and S. Pérennes, Provably efficient algorithms for placement of service function chains with ordering constraints, Proc. IEEE INFOCOM, pp.774-782, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01921112

S. R. Chowdhury, R. Ahmed, N. Shahriar, A. Khan, R. Boutaba et al., ReViNE: Reallocation of Virtual Network Embedding to eliminate substrate bottlenecks, 2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM), pp.116-124, 2017.

S. Khebbache, M. Hadji, and D. Zeghlache, Scalable and cost-efficient algorithms for VNF chaining and placement problem, Proc. ICIN, pp.92-99, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01630011

N. Tastevin, M. Obadia, and M. Bouet, A graph approach to placement of service functions chains, Proc. IFIP/IEEE IM, pp.134-141, 2017.

M. M. Tajiki, S. Salsano, L. Chiaraviglio, M. Shojafar, and B. Akbari, Joint Energy Efficient and QoS-Aware Path Allocation and VNF Placement for Service Function Chaining, IEEE Transactions on Network and Service Management, vol.16, issue.1, pp.374-388, 2019.

J. Pei, P. Hong, K. Xue, and D. Li, Efficiently embedding service function chains with dynamic virtual network function placement in geo-distributed cloud system, IEEE Transactions on Parallel and Distributed Systems, pp.1-1, 2018.

S. Kim, S. Park, Y. Kim, S. Kim, and K. Lee, VNF-EQ: dynamic placement of virtual network functions for energy efficiency and QoS guarantee in NFV, Cluster Computing, vol.20, issue.3, pp.2107-2117, 2017.

J. Cao, Y. Zhang, W. An, X. Chen, J. Sun et al., VNF-FG design and VNF placement for 5G mobile networks, Science China Information Sciences, vol.60, issue.4, p.40302, 2017.

M. Otokura, K. Leibnitz, Y. Koizumi, D. Kominami, T. Shimokawa et al., Application of evolutionary mechanism to dynamic virtual network function placement, Proc. IEEE ICNP, pp.1-6, 2016.

M. C. Luizelli, W. L. Da-costa-cordeiro, L. S. Buriol, and L. P. Gaspary, A fix-and-optimize approach for efficient and large scale virtual network function placement and chaining, Computer Communications, vol.102, pp.67-77, 2017.

T. Bäck, Evolutionary Algorithms in Theory and Practice: Evolution Strategies, Evolutionary Programming, Genetic Algorithms, 1996.

S. Singh, A. Okun, and A. Jackson, Learning to play Go from scratch, Nature, vol.550, p.2017

I. Bello, H. Pham, Q. V. Le, M. Norouzi, and S. Bengio, Neural combinatorial optimization with reinforcement learning, CoRR, 2016.

T. A. Pham, Y. Hadjadj-aoul, and A. Outtagarts, Deep Reinforcement Learning Based QoS-Aware Routing in Knowledge-Defined Networking, Proc. EAI QShine, pp.14-26, 2019.
URL : https://hal.archives-ouvertes.fr/hal-01933970

R. Mijumbi, J. Gorricho, J. Serrat, M. Claeys, F. D. Turck et al., Design and evaluation of learning algorithms for dynamic resource management in virtual networks, IEEE NOMS, pp.1-9, 2014.

G. Dulac-arnold, R. Evans, P. Sunehag, and B. Coppin, Reinforcement learning in large discrete action spaces, CoRR, 2015.

F. Carpio, S. Dhahri, and A. Jukan, VNF placement with replication for Load balancing in NFV networks, IEEE ICC, pp.1-6, 2017.

F. Carpio, W. Bziuk, and A. Jukan, Replication of Virtual Network Functions: Optimizing link utilization and resource costs, MIPRO, pp.521-526, 2017.

M. Ghaznavi, A. Khan, N. Shahriar, K. Alsubhi, R. Ahmed et al., Elastic virtual network function placement, CloudNet, pp.255-260, 2015.

P. T. Quang, A. Bradai, K. D. Singh, G. Picard, and R. Riggio, Single and Multi-Domain Adaptive Allocation Algorithms for VNF Forwarding Graph Embedding, IEEE Transactions on Network and Service Management, vol.16, issue.1, pp.98-112, 2019.

K. Rusek, J. Suárez-varela, A. Mestres, P. Barlet-ros, and A. Cabellos-aparicio, Unveiling the potential of graph neural networks for network modeling and optimization in SDN, CoRR, 2019.

Z. Xu, J. Tang, J. Meng, W. Zhang, Y. Wang et al., Experience-driven Networking: A Deep Reinforcement Learning based Approach, IEEE INFOCOM, pp.1871-1879, 2018.

Y. Xie, Z. Liu, S. Wang, and Y. Wang, Service function chaining resource allocation: A survey, CoRR, 2016.

C. J. Watkins and P. Dayan, Q-learning, Machine Learning, vol.8, pp.279-292, 1992.

J. Tsitsiklis and B. Van-roy, An analysis of temporal-difference learning with function approximation (technical report lids-p-2322)," Laboratory for Information and Decision Systems, 1996.

V. Mnih, K. Kavukcuoglu, D. Silver, A. A. Rusu, J. Veness et al., Human-level control through deep reinforcement learning, Nature, vol.518, issue.7540, pp.529-533, 2015.

S. Adam, L. Busoniu, and R. Babuska, Experience replay for real-time reinforcement learning control, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), vol.42, issue.2, pp.201-212, 2012.

T. P. Lillicrap, J. J. Hunt, A. Pritzel, N. Heess, T. Erez et al., Continuous control with deep reinforcement learning, CoRR, 2015.

G. Stampa, M. Arias, D. Sanchez-charles, V. Muntés-mulero, and A. Cabellos, A deep-reinforcement learning approach for softwaredefined networking routing optimization, CoRR, 2017.

V. Mnih, A. P. Badia, M. Mirza, A. Graves, T. Lillicrap et al., Asynchronous methods for deep reinforcement learning, International conference on machine learning, pp.1928-1937, 2016.

G. Barth-maron, M. W. Hoffman, D. Budden, W. Dabney, D. Horgan et al., Distributed distributional deterministic policy gradients, CoRR, 2018.

, The internet topology zoo

A. Varga, Discrete event simulation system, Proc. of the European Simulation Multiconference, 2011.

P. Erd?s and A. Rényi, On random graphs I, Publ. Math. Debrecen, vol.6, pp.290-297, 1959.

, On the evolution of random graphs, Publ. Math. Inst. Hungar. Acad. Sci, vol.5, pp.17-61, 1960.

, Network functions virtualisation (nfv); management and orchestration, IETF, pp.2070-1721, 2014.

K. Team, Keras, 2015.

D. P. Kingma and J. Ba, Adam: A method for stochastic optimization, CoRR, 2014.

X. Glorot, A. Bordes, and Y. Bengio, Deep sparse rectifier neural networks, Proc. AIStats, pp.315-323, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00752497

L. Yala, P. A. Frangoudis, G. Lucarelli, and A. Ksentini, Cost and availability aware resource allocation and virtual function placement for cdnaas provision, IEEE Transactions on Network and Service Management, vol.15, issue.4, pp.1334-1348, 2018.

L. Ochoa-aday, C. Cervelló-pastor, A. Fernández-fernández, and P. Grosso, An online algorithm for dynamic nfv placement in cloud-based autonomous response networks, Symmetry, vol.10, issue.5, 2018.

A. Marotta, E. Zola, F. D'andreagiovanni, and A. Kassler, A fast robust optimization-based heuristic for the deployment of green virtual network functions, Journal of Network and Computer Applications, vol.95, pp.42-53, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01665879

H. Yao, X. Chen, M. Li, P. Zhang, and L. Wang, A novel reinforcement learning algorithm for virtual network embedding, Neurocomputing, vol.284, pp.1-9, 2018.

D. Tai, H. Dai, T. Zhang, and B. Liu, On data plane latency and pseudo-TCP congestion in Software-Defined Networking, Proc

A. Ancs, , pp.133-134, 2016.

S. Khebbache, M. Hadji, and D. Zeghlache, Virtualized network functions chaining and routing algorithms, Computer Networks, vol.114, pp.95-110, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01471730