28 citations · 164 across the 37 of their papers we have counts for
6 papers · 1 filter
Towards Reliable Participation in UAV-Enabled Federated Edge Learning on Non-IID Data
Youssra Cheriguene, Wael Jaafar, Halim Yanikomeroglu +1
Federated Learning (FL) is a decentralized machine learning (ML) technique that allows a number of participants to train an ML model collaboratively without having to share their p…
RL-Based Cargo-UAV Trajectory Planning and Cell Association for Minimum Handoffs, Disconnectivity, and Energy Consumption
Nesrine Cherif, Wael Jaafar, Halim Yanikomeroglu +1
Unmanned aerial vehicle (UAV) is a promising technology for last-mile cargo delivery. However, the limited on-board battery capacity, cellular unreliability, and frequent handoffs…
Data-Efficient Energy-Aware Participant Selection for UAV-Enabled Federated Learning
Youssra Cheriguene, Wael Jaafar, Chaker Abdelaziz Kerrache +3
Unmanned aerial vehicle (UAV)-enabled edge federated learning (FL) has sparked a rise in research interest as a result of the massive and heterogeneous data collected by UAVs, as w…
Market Driven Multi-domain Network Service Orchestration in 5G Networks
Mouhamad Dieye, Wael Jaafar, Halima Elbiaze +1
The advent of a new breed of enhanced multimedia services has put network operators into a position where they must support innovative services while ensuring both end-to-end Quali…
Multi-UAV Speed Control with Collision Avoidance and Handover-aware Cell Association: DRL with Action Branching
Zijiang Yan, Wael Jaafar, Bassant Selim +1
This paper presents a deep reinforcement learning solution for optimizing multi-UAV cell-association decisions and their moving velocity on a 3D aerial highway. The objective is to…
FLSTRA: Federated Learning in Stratosphere
Amin Farajzadeh, Animesh Yadav, Omid Abbasi +2
We propose a federated learning (FL) in stratosphere (FLSTRA) system, where a high altitude platform station (HAPS) facilitates a large number of terrestrial clients to collaborati…