20 citations · 29 across the 15 of their papers we have counts for
6 papers · 1 filter
Federated Deep Reinforcement Learning for Open RAN Slicing in 6G Networks
Amine Abouaomar, Afaf Taik, Abderrahime Filali +1
Radio access network (RAN) slicing is a key element in enabling current 5G networks and next-generation networks to meet the requirements of different services in various verticals…
Resource Provisioning in Edge Computing for Latency Sensitive Applications
Amine Abouaomar, Soumaya Cherkaoui, Zoubeir Mlika +1
Low-Latency IoT applications such as autonomous vehicles, augmented/virtual reality devices and security applications require high computation resources to make decisions on the fl…
A Deep Reinforcement Learning Approach for Service Migration in MEC-enabled Vehicular Networks
Amine Abouaomar, Zoubeir Mlika, Abderrahime Filali +2
Multi-access edge computing (MEC) is a key enabler to reduce the latency of vehicular network. Due to the vehicles mobility, their requested services (e.g., infotainment services)…
Mean-Field Game and Reinforcement Learning MEC Resource Provisioning for SFC
Amine Abouaomar, Soumaya Cherkaoui, Zoubeir Mlika +1
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…
A Resources Representation For Resource Allocation In Fog Computing Networks
Amine Abouaomar, Soumaya Cherkaoui, Abdellatif Kobbane +1
Fog computing is emerging as a new paradigm to deal with latency-sensitive applications, by making data processing and analysis close to their source. Due to the heterogeneity of d…
Matching-Game for User-Fog Assignment
Amine Abouaomar, Abdellatif Kobbane, Soumaya Cherkaoui
Fog computing has emerged as a new paradigm in mobile network communications, aiming to equip the edge of the network with the computing and storing capabilities to deal with the h…