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 …

Supported by some of the major revolutionary technologies, such as Internet of Vehicles
(IoVs), Edge Computing, and Machine Learning (ML), the traditional Vehicular Networks …

In recent years, the powerful combination of Multi-access Edge Computing (MEC) and
Artificial Intelligence (AI), called edge intelligence, promotes the development of Intelligent …

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 …

Federated learning is a newly emerged distributed machine learning paradigm, where the
clients are allowed to individually train local deep neural network (DNN) models with local …

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 …

With the incoming introduction of 5G networks and the advancement in technologies such as
network function virtualization and software defined networking, new and emerging …

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 …

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 …

Connected and Automated Vehicles (CAVs) represent a rapidly growing technology in the
automotive domain sector, offering promising solutions to address challenges such as traffic …