6G will be the next horizon from connected people and things to intelligence-of-everything.
Machine learning (ML) combines artificial intelligence with vehicular edge computing (VEC) …

In 6G Internet of Vehicles (IoV) system, Federated Learning (FL) is usually used to structure
the joint training model between vehicles and RSU. However, due to the mobility of the …

The accelerating progress of the Internet of Vehicles (IoV) has put forward a higher demand
for distributed model training and data sharing in vehicular networks. Traditional centralized …

Federated Learning (FL) has achieved great success in many intelligent applications of the
Internet of Vehicles (IoV), however, a large number of vehicles and increasingly size of …

With the upcoming next generation wireless network, vehicles are expected to be
empowered by artificial intelligence (AI). By connecting vehicles and cloud server via …

The Internet of Vehicles (IoV) aims to perceive, compute, and process environmental data in
a collaborative manner. Previous works focus on data sharing between vehicles, but a large …

Decentralized federated learning (DFL) is a promising technology to implement distributed
machine learning in Internet of Vehicles (IoV), which enables vehicles to share and …

The vision of the upcoming 6G technologies that have fast data rate, low latency, and ultra-
dense network, draws great attentions to the Internet of Vehicles (IoV) and Vehicle-to …

Sixth generation (6G) vehicle-to-anything (V2X) networks support intelligent edge computing
that leverages data sensing, computation, and offloading among vehicular nodes (VN) with …

Vehicular networks enable vehicles support some real-time applications through training
data. Due to the limited computing capability of vehicles, vehicles usually transmit data to a …