Joint resource management for mobility supported federated learning in Internet of Vehicles
G Wang, F Xu, H Zhang, C Zhao - Future Generation Computer Systems, 2022 - Elsevier
In recent years, the powerful combination of Multi-access Edge Computing (MEC) and
Artificial Intelligence (AI), called edge intelligence, promotes the development of Intelligent …
Artificial Intelligence (AI), called edge intelligence, promotes the development of Intelligent …
Clustered vehicular federated learning: Process and optimization
Federated Learning (FL) is expected to play a prominent role for privacy-preserving machine
learning (ML) in autonomous vehicles. FL involves the collaborative training of a single ML …
learning (ML) in autonomous vehicles. FL involves the collaborative training of a single ML …
Privacy-preserved federated learning for autonomous driving
Y Li, X Tao, X Zhang, J Liu, J Xu - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
In recent years, the privacy issue in Vehicular Edge Computing (VEC) has gained a lot of
concern. The privacy problem is even more severe in autonomous driving business than the …
concern. The privacy problem is even more severe in autonomous driving business than the …
Blockchain-based federated learning in mobile edge networks with application in internet of vehicles
The rapid increase of the data scale in Internet of Vehicles (IoV) system paradigm, hews out
new possibilities in boosting the service quality for the emerging applications through data …
new possibilities in boosting the service quality for the emerging applications through data …
Multi-region asynchronous swarm learning for data sharing in large-scale internet of vehicles
H Yin, X Huang, Y Wu, C Liang… - IEEE Communications …, 2023 - ieeexplore.ieee.org
To provide various intelligent services in Internet of Vehicles (IoVs), such as autonomous
driving, data sharing technologies enable vehicles to overcome information barriers and …
driving, data sharing technologies enable vehicles to overcome information barriers and …
Federated learning for vehicular internet of things: Recent advances and open issues
Federated learning (FL) is a distributed machine learning approach that can achieve the
purpose of collaborative learning from a large amount of data that belong to different parties …
purpose of collaborative learning from a large amount of data that belong to different parties …
FedCPF: An efficient-communication federated learning approach for vehicular edge computing in 6G communication networks
The sixth-generation network (6G) is expected to achieve a fully connected world, which
makes full use of a large amount of sensitive data. Federated Learning (FL) is an emerging …
makes full use of a large amount of sensitive data. Federated Learning (FL) is an emerging …
Distributed Deep Reinforcement Learning Based Gradient Quantization for Federated Learning Enabled Vehicle Edge Computing
Federated Learning (FL) can protect the privacy of the vehicles in vehicle edge computing
(VEC) to a certain extent through sharing the gradients of vehicles' local models instead of …
(VEC) to a certain extent through sharing the gradients of vehicles' local models instead of …
Federated learning in intelligent transportation systems: Recent applications and open problems
Intelligent transportation systems (ITSs) have been fueled by the rapid development of
communication technologies, sensor technologies, and the Internet of Things (IoT) …
communication technologies, sensor technologies, and the Internet of Things (IoT) …
Coalition based utility and efficiency optimization for multi-task federated learning in Internet of Vehicles
Z Li, H Wu, Y Lu - Future Generation Computer Systems, 2023 - Elsevier
With the emergence of the sixth generation (6G) communication technologies, massive
infrastructures will be densely deployed and the number of data will be generated …
infrastructures will be densely deployed and the number of data will be generated …