collaborators

5 papers

cs.NI2024

A Survey on Large Language Models for Communication, Network, and Service Management: Application Insights, Challenges, and Future Directions

Gordon Owusu Boateng, Hani Sami, Ahmed Alagha +10

The rapid evolution of communication networks in recent decades has intensified the need for advanced Network and Service Management (NSM) strategies to address the growing demands…

cs.LG2024

On-Demand Model and Client Deployment in Federated Learning with Deep Reinforcement Learning

Mario Chahoud, Hani Sami, Azzam Mourad +3

In Federated Learning (FL), the limited accessibility of data from diverse locations and user types poses a significant challenge due to restricted user participation. Expanding cl…

cs.NI2024

Federated Learning and Evolutionary Game Model for Fog Federation Formation

Zyad Yasser, Ahmad Hammoud, Azzam Mourad +3

In this paper, we tackle the network delays in the Internet of Things (IoT) for an enhanced QoS through a stable and optimized federated fog computing infrastructure. Network delay…

cs.CR2024

Trust Driven On-Demand Scheme for Client Deployment in Federated Learning

Mario Chahoud, Azzam Mourad, Hadi Otrok +2

Containerization technology plays a crucial role in Federated Learning (FL) setups, expanding the pool of potential clients and ensuring the availability of specific subsets for ea…

cs.GT2024

Enhancing Mutual Trustworthiness in Federated Learning for Data-Rich Smart Cities

Osama Wehbi, Sarhad Arisdakessian, Mohsen Guizani +5

Federated learning is a promising collaborative and privacy-preserving machine learning approach in data-rich smart cities. Nevertheless, the inherent heterogeneity of these urban…