Computation offloading is one of the key technologies in Mobile Edge Computing (MEC),
which makes up for the deficiencies of mobile devices in terms of storage resource …

With the advent of new technologies in both hardware and software, we are in the need of a
new type of application that requires huge computation power and minimal delay …

In vehicle ad-hoc networks, the progression of wireless communication technology to 6G,
overcomes storage, processing, privacy, and power limits to create an efficient and …

Vehicular Edge Computing (VEC) has gained increasing interest due to its potential to
provide low latency and reduce the load in backhaul networks. In order to meet drastically …

Vehicular Edge Computing (VEC) is enjoying a surge in research interest due to the
remarkable potential to reduce response delay and alleviate bandwidth pressure. Facing the …

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 …

The development of the Internet of vehicles (IoV) has spawned a series of driving assistance
services (eg, collision warning), which improves the safety and intelligence of transportation …

Many enterprise companies migrate their services and applications to the cloud to benefit
from cloud computing advantages. Meanwhile, the rapidly increasing number of connected …

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) …

Multi-access Edge Computing (MEC) is a key solution that enables operators to open their
networks to new services and IT ecosystems to leverage edge-cloud benefits in their …