High stable and accurate vehicle selection scheme based on federated edge learning in vehicular networks
Federated edge learning (FEEL) technology for vehicular networks is considered as a
promising technology to reduce the computation workload while keeping the privacy of …
promising technology to reduce the computation workload while keeping the privacy of …
Edge computing-based joint client selection and networking scheme for federated learning in vehicular IoT
W Bao, C Wu, S Guleng, J Zhang… - China …, 2021 - ieeexplore.ieee.org
In order to support advanced vehicular Internet-of-Things (IoT) applications, information
exchanges among different vehicles are required to find efficient solutions for catering to …
exchanges among different vehicles are required to find efficient solutions for catering to …
Vehicle selection and resource optimization for federated learning in vehicular edge computing
As a distributed deep learning paradigm, federated learning (FL) provides a powerful tool for
the accurate and efficient processing of on-board data in vehicular edge computing (VEC) …
the accurate and efficient processing of on-board data in vehicular edge computing (VEC) …
Semi-synchronous federated learning protocol with dynamic aggregation in internet of vehicles
In an Internet of Vehicle (IoV) system, federated learning (FL) is a new approach to process
real-time vehicle data in a distributed way, which can improve the driving experience and …
real-time vehicle data in a distributed way, which can improve the driving experience and …
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 …
Vehicle selection and resource allocation for federated learning-assisted vehicular network
To exploit the massive amounts of onboard data in vehicular networks while protecting data
privacy and security, federated learning (FL) is regarded as a promising technology to …
privacy and security, federated learning (FL) is regarded as a promising technology to …
Communication and computation efficient federated learning for Internet of vehicles with a constrained latency
Considering the privacy and security issues in Internet of Vehicles (IoV), wireless federated
learning (FL) can be adopted to facilitate various emerging vehicular applications. However …
learning (FL) can be adopted to facilitate various emerging vehicular applications. However …
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 …
Content-based vehicle selection and resource allocation for federated learning in IoV
S Wang, F Liu, H Xia - 2021 IEEE Wireless Communications …, 2021 - ieeexplore.ieee.org
In order to use datasets collected from multiple vehicles to train a machine learning model
while ensuring vehicle user privacy, federal learning framework was introduced into the …
while ensuring vehicle user privacy, federal learning framework was introduced into the …
Resource constrained vehicular edge federated learning with highly mobile connected vehicles
This paper proposes a vehicular edge federated learning (VEFL) solution, where an edge
server leverages highly mobile connected vehicles'(CVs') onboard central processing units …
server leverages highly mobile connected vehicles'(CVs') onboard central processing units …
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