The upcoming team seminar will showcase presentations from four new ROC PhD students.
When: December 16, 2024 at 2 pm.
Where: room Amphi Gaston Planté, 2 rue Conté, CNAM, Paris, France.
Speaker: Billal Mokhtari
Title: Cyber-physical security design and integration for interoperability, traceability, and environmental impact reduction in battery cell manufacturing, enhanced by digital twins.
Abstract: My thesis, conducted within the framework of the European BaTTwin project, aims to use ontologies and AI techniques such as Graph Neural Networks (GNN) to detect cyber-physical system attacks in real-time within the battery cell manufacturing chain, based on collected data. The research focuses on identifying security threats and designing interoperability models to integrate cyber-physical security, while exploring approaches based on semantic graphs and even machine learning to improve anomaly detection.
Bio: First year PhD student at CNAM, supervised by Samia Bouzefrane and Nada Mimouni.
Speaker: Moussa GUEMDANI
Title: New resource allocation protocols and scheduling algorithms for disaggregated cellular access networks.
Abstract: This thesis focuses on new resource allocation protocols and scheduling algorithms adapted for disaggregated cellular access networks. These networks, which break down traditional monolithic base stations into separate, specialized components, offer increased flexibility and scalability.
The research aims to propose novel methods for dynamic resource allocation and efficient scheduling, optimizing network performance regarding latency, throughput, and reliability. Emphasis is placed on integrating these protocols within existing 5G network deployment and ensuring compatibility with OpenRan and cloud-native infrastructures. This work seeks to demonstrate the feasibility of the proposed solutions through accurate simulations and real-world experiments using open radio units (O-RUs) and open-source radio access networks (RAN). The thesis also explores how Machine Learning (ML) can enhance adaptive scheduling in response to network traffic conditions, to improve the Quality of Service (QoS) in disaggregated architecture
Bio: Moussa Guemdani holds a computer science master, track Computer Networks and IoT Systems, from CNAM, Paris, France. His research interests include network virtualization, IoT protocols, AI/ML integration, Software-Defined Networking, and beyond-5G architectures. His previous work involves deploying a disaggregated RAN in the 5G testbed for the CNAM computer science and communications research department (CEDRIC-ROC).
Speaker: Thierry Nkouka
Title: Distributed Artificial Intelligence for IoT Architectures
Abstract: The Internet of Things (IoT) has revolutionized interactions with the environment by enabling real-time decision-making through the interconnection of billions of devices. However, challenges such as managing heterogeneous devices, addressing energy constraints, and meeting real-time performance demands become significant as IoT networks scale and complexity grows. This research investigates the integration of Distributed Artificial Intelligence (AI) within IoT systems to address these issues. By decentralizing intelligence, Distributed AI reduces latency, decreases dependency on continuous connectivity, and improves scalability, offering an effective solution for managing large-scale, complex, and distributed IoT networks.
Speaker: Ali Srour
Title: NTN network communications using programmable UAVs
Abstract: The integration of Non-Terrestrial Networks (NTNs) in 5G and beyond is essential for addressing coverage gaps in traditional terrestrial networks. NTNs, including satellites and high-altitude platforms, provide connectivity in remote, underserved, and disaster-affected areas. However, NTN faces big challenges in terms of energy efficiency, latency, and reliability. Our research focuses on developing solutions using programmable logic devices (FPGAs) to enhance the performance of LEO-based open RAN applications.
Bio: Ali Srour is a PhD candidate at Cedric lab, CNAM. He holds a Bachelor’s degree in Telecommunication Engineering from IUL Lebanon and a Master’s degree in Computer Networks and IoT Systems from CNAM Paris. His research interests include 5G and beyond systems, Open RAN, Non-Terrestrial Networks, and Programmable Logic Devices. Throughout his academic journey, Ali has contributed to developing and implementing monitoring and machine learning-based applications within intelligent controllers for Open RAN architectures. Additionally, he has been involved in exploring solutions in the field of in-network computing.
