@conference {Abouaomar2021,
	title = {Mean-Field Game and Reinforcement Learning MEC Resource Provisioning for SFC},
	booktitle = {2021 IEEE Global Communications Conference, GLOBECOM 2021 - Proceedings},
	year = {2021},
	note = {cited By 0},
	abstract = {In this paper, we address the resource provisioning problem for service function chaining (SFC) in terms of the placement and chaining of virtual network functions (VNFs) within a multi-access edge computing (MEC) infrastructure to reduce service delay. We consider the VNFs as the main entities of the system and propose a mean-field game (MFG) framework to model their behavior for their placement and chaining. Then, to achieve the optimal resource provisioning policy without considering the system control parameters, we reduce the proposed MFG to a Markov decision process (MDP). In this way, we leverage reinforcement learning with an actor-critic approach for MEC nodes to learn complex placement and chaining policies. Simulation results show that our proposed approach outperforms benchmark state-of-the-art approaches. {\textcopyright} 2021 IEEE.},
	keywords = {Computer games, Computing infrastructures, Computing resource, e-learning, Edge computing, Markov processes, Mean-field games, Multi-access edge computing, Multiaccess, Network function virtualization, Reinforcement learning, Reinforcement learnings, Resource provisioning, Service function chaining, Service functions, Transfer functions, Virtual addresses, Virtual reality},
	doi = {10.1109/GLOBECOM46510.2021.9685236},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124062107\&doi=10.1109\%2fGLOBECOM46510.2021.9685236\&partnerID=40\&md5=8319d7756843c2ccadb8f9de4bec7eff},
	author = {Abouaomar, A. and Cherkaoui, S. and Mlika, Z. and Kobbane, A.}
}
@article {Filali2020197017,
	title = {Multi-access edge computing: A survey},
	journal = {IEEE Access},
	volume = {8},
	year = {2020},
	note = {cited By 49},
	pages = {197017-197046},
	abstract = {Multi-access Edge Computing (MEC) is a key solution that enables operators to open their networks to new services and IT ecosystems to leverage edge-cloud benefits in their networks and systems. Located in close proximity from the end users and connected devices, MEC provides extremely low latency and high bandwidth while always enabling applications to leverage cloud capabilities as necessary. In this article, we illustrate the integration of MEC into a current mobile networks{\textquoteright} architecture as well as the transition mechanisms to migrate into a standard 5G network architecture.We also discuss SDN, NFV, SFC and network slicing as MEC enablers. Then, we provide a state-of-the-art study on the different approaches that optimize the MEC resources and its QoS parameters. In this regard, we classify these approaches based on the optimized resources and QoS parameters (i.e., processing, storage, memory, bandwidth, energy and latency). Finally, we propose an architectural framework for a MEC-NFV environment based on the standard SDN architecture. {\textcopyright} 2020 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.},
	keywords = {5G mobile communication systems, Architectural frameworks, Bandwidth, Close proximity, Edge computing, Network function virtualization, Network slicing, Networks and systems, Optimized resources, QoS parameters, State of the art, Transition mechanism},
	doi = {10.1109/ACCESS.2020.3034136},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85099901543\&doi=10.1109\%2fACCESS.2020.3034136\&partnerID=40\&md5=bc99db081ebbbf5eb6d188c020bb33a2},
	author = {Filali, A. and Abouaomar, A. and Cherkaoui, S. and Kobbane, A. and Guizani, M.}
}
@conference {Abouaomar2019,
	title = {Matching-Game for User-Fog Assignment},
	booktitle = {2018 IEEE Global Communications Conference, GLOBECOM 2018 - Proceedings},
	year = {2019},
	note = {cited By 0},
	doi = {10.1109/GLOCOM.2018.8647545},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85063543941\&doi=10.1109\%2fGLOCOM.2018.8647545\&partnerID=40\&md5=2e86072aa15d3175de06d25bff61c79f},
	author = {Abouaomar, A. and Kobbane, A. and Cherkaoui, S.}
}
