251 citations · 833 across the 65 of their papers we have counts for
27 papers · 1 filter
Privacy-Aware Agent Collaboration for Dynamic VR Slice Management in 6G SD-RAN
Khaled M. Naguib, Soumaya Cherkaoui, Mahmoud M. Elmesalawy +2
Ultra-low latency and high throughput are required for Virtual Reality (VR) services in 6G networks, which presents critical challenges for Software-Defined Radio Access Networks (…
DRL-Driven Edge-Aware Utility Optimization for Multi-Slice 6G Networks
Khaled M. Naguib, Soumaya Cherkaoui, Mahmoud M. Elmessalawy +2
Virtual Reality (VR) services delivered over 6G networks demand ultra-low latency and high bandwidth to ensure seamless user experiences. This paper presents an intelligent resourc…
Adversarial Attacks in AI-Driven RAN Slicing: SLA Violations and Recovery
Deemah H. Tashman, Soumaya Cherkaoui
Next-generation (NextG) cellular networks are designed to support emerging applications with diverse data rate and latency requirements, such as immersive multimedia services and l…
ML-Enabled Open RAN: A Comprehensive Survey of Architectures, Challenges, and Opportunities
Mira Chandra Kirana, Patatchona Keyela, Fatemeh Rostamian +2
As wireless communication systems become more advanced, Open Radio Access Networks (O-RAN) stand out as a notable framework that promotes interoperability and cost-effectiveness. A…
Trustworthy AI-Driven Dynamic Hybrid RIS: Joint Optimization and Reward Poisoning-Resilient Control in Cognitive MISO Networks
Deemah H. Tashman, Soumaya Cherkaoui
Cognitive radio networks (CRNs) are a key mechanism for alleviating spectrum scarcity by enabling secondary users (SUs) to opportunistically access licensed frequency bands without…
Open RAN Slicing with Quantum Optimization
Patatchona Keyela, Soumaya Cherkaoui
RAN slicing technology is a key aspect of the Open RAN paradigm, allowing simultaneous and independent provision of various services such as ultra-reliable low-latency communicatio…
User Trajectory Prediction in Mobile Wireless Networks Using Quantum Reservoir Computing
Zoubeir Mlika, Soumaya Cherkaoui, Jean Frédéric Laprade +1
This paper applies a quantum machine learning technique to predict mobile users' trajectories in mobile wireless networks using an approach called quantum reservoir computing (QRC)…
Deep Deterministic Policy Gradient to Minimize the Age of Information in Cellular V2X Communications
Zoubeir Mlika, Soumaya Cherkaoui
This paper studies the problem of minimizing the age of information (AoI) in cellular vehicle-to-everything communications. To provide minimal AoI and high reliability for vehicles…
Unsupervised Data Splitting Scheme for Federated Edge Learning in IoT Networks
Boubakr Nour, Soumaya Cherkaoui
Federated Edge Learning (FEEL) is a promising distributed learning technique that aims to train a shared global model while reducing communication costs and promoting users' privac…
Communication and Computation O-RAN Resource Slicing for URLLC Services Using Deep Reinforcement Learning
Abderrahime Filali, Boubakr Nour, Soumaya Cherkaoui +1
The evolution of the future beyond-5G/6G networks towards a service-aware network is based on network slicing technology. With network slicing, communication service providers seek…
Dynamic SDN-based Radio Access Network Slicing with Deep Reinforcement Learning for URLLC and eMBB Services
Abderrahime Filali, Zoubeir Mlika, Soumaya Cherkaoui +1
Radio access network (RAN) slicing is a key technology that enables 5G network to support heterogeneous requirements of generic services, namely ultra-reliable low-latency communic…
Competitive Algorithms and Reinforcement Learning for NOMA in IoT Networks
Zoubeir Mlika, Soumaya Cherkaoui
This paper studies the problem of massive Internet of things (IoT) access in beyond fifth generation (B5G) networks using non-orthogonal multiple access (NOMA) technique. The probl…
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…
An Overview of Blockchain and 5G Networks
Hajar Moudoud, Soumaya Cherkaoui, Lyes Khoukhi
The 5G wireless networks are potentially revolutionizing future technologies. The 5G technologies are expected to foresee demands of diverse vertical applications with diverse requ…
An IoT Blockchain Architecture Using Oracles and Smart Contracts: the Use-Case of a Food Supply Chain
Hajar Moudoud, Soumaya Cherkaoui, Lyes Khoukhi
The blockchain is a distributed technology which allows establishing trust among unreliable users who interact and perform transactions with each other. While blockchain technology…
Network Slicing with MEC and Deep Reinforcement Learning for the Internet of Vehicles
Zoubeir Mlika, Soumaya Cherkaoui
The interconnection of vehicles in the future fifth generation (5G) wireless ecosystem forms the so-called Internet of vehicles (IoV). IoV offers new kinds of applications requirin…
Network slicing for vehicular communications: a multi-agent deep reinforcement learning approach
Zoubeir Mlika, Soumaya Cherkaoui
This paper studies the multi-agent resource allocation problem in vehicular networks using non-orthogonal multiple access (NOMA) and network slicing. To ensure heterogeneous servic…
Matching-based Service Offloading for Compute-less Driven IoT Networks
Boubakr Nour, Soumaya Cherkaoui
With the advent of the Internet of Things (IoT) and 5G networks, edge computing is offering new opportunities for business model and use cases innovations. Service providers can no…
Service Function Chaining in MEC: A Mean-Field Game and Reinforcement Learning Approach
Amine Abouaomar, Soumaya Cherkaoui, Zoubeir Mlika +1
Multi-access edge computing (MEC) and network virtualization technologies are important enablers for fifth-generation (5G) networks to deliver diverse applications and services. Se…
A Network-based Compute Reuse Architecture for IoT Applications
Boubakr Nour, Soumaya Cherkaoui
The tremendous advancements in the Internet of Things (IoT) increasingly involve computationally intensive services. These services often require more computation resources than ca…