[HTML][HTML] EneA-FL: Energy-aware orchestration for serverless federated learning

A Agiollo, P Bellavista, M Mendula, A Omicini - Future Generation …, 2024 - Elsevier
Federated Learning (FL) represents the de-facto standard paradigm for enabling distributed
learning over multiple clients in real-world scenarios. Despite the great strides reached in …

Privacy in Federated Learning

J Sen, H Waghela, S Rakshit - arxiv preprint arxiv:2408.08904, 2024 - arxiv.org
Federated Learning (FL) represents a significant advancement in distributed machine
learning, enabling multiple participants to collaboratively train models without sharing raw …

Mitigating content poisoning attacks in named data networking: a survey of recent solutions, limitations, challenges and future research directions

SS Ullah, S Hussain, I Ali, H Khattak… - Artificial Intelligence …, 2024 - Springer
Abstract Named Data Networking (NDN) is one of the capable applicants for the future
Internet architecture, where communications focus on content rather than providing content …

Collaborative Federated Learning in Mobile Vehicle Clouds for Online Ride-Hailing Passenger Zones Recommendation

Z Liao, X Zhou, W Liang, KC Li, Y Liu… - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
Recommendations for ride-hailing zones are crucial for matching drivers with passengers
efficiently, improving mobility, and managing traffic effectively. However, current …

Forward Legal Anonymous Group Pairing-Onion Routing for Mobile Opportunistic Networks

X Zhu, L Lin, Y Huang, X Wang… - IEEE Transactions on …, 2025 - ieeexplore.ieee.org
Mobile Opportunistic Networks (MONs) often experience frequent interruptions in end-to-end
connections, which increases the likelihood of message loss during delivery and makes …