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[HTML][HTML] EneA-FL: Energy-aware orchestration for serverless federated learning
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 …
learning over multiple clients in real-world scenarios. Despite the great strides reached in …
Privacy in Federated Learning
Federated Learning (FL) represents a significant advancement in distributed machine
learning, enabling multiple participants to collaboratively train models without sharing raw …
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
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 …
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
Recommendations for ride-hailing zones are crucial for matching drivers with passengers
efficiently, improving mobility, and managing traffic effectively. However, current …
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 …
connections, which increases the likelihood of message loss during delivery and makes …