As a result of the advancement in the fourth industrial revolution and communication
technology, the use of digital twins (DT) and federated learning (FL) in the industrial Internet …

This paper proposes a vehicular edge federated learning (VEFL) solution, where an edge
server leverages highly mobile connected vehicles'(CVs') onboard central processing units …

Federated Learning (FL), as a privacy-preserving distributed machine learning paradigm,
has become a promising privacy computing framework for increasingly complex network …

With the advent of the Internet of things (IoT) era, federated learning plays an important role
in breaking through traditional data barriers and effectively realizing data privacy and …

Unmanned aerial vehicles (UAVs)-assisted multiaccess edge computing (MEC) has
emerged as a promising solution in B5G/6G networks. The high flexibility and seamless …

The number of Internet of Things (IoT) applications, especially latency‐sensitive ones, have
been significantly increased. So, cloud computing, as one of the main enablers of the IoT …

The concept of federated learning (FL) is becoming increasingly popular as a method for
training collaborative models without loss the sensitive information. The term has become …

With the increasing number of connected vehicles on the road, vehicular communications
have become an important research area. Federated learning (FL), a distributed machine …

As a promising distributed technology, federated learning (FL) has been widely used in
vehicular networks involving large amounts of IoT-enabled sensor data, which derives …

Significant efforts have been made for vehicle-to-vehicle communications that now enable
the Internet of Vehicles (IoV). However, current IoV solutions are unable to capture traffic …