Distributed artificial intelligence (AI) is becoming an efficient approach to fulfill the high and
diverse requirements for future vehicular networks. However, distributed intelligence tasks …

With the emergence of new vehicular applications, computation offloading based on mobile
edge computing (MEC) has become a promising paradigm in resource‐constrained …

The proliferation of computation-intensive and delay-sensitive applications in the Internet of
Vehicles (IoV) poses great challenges to resource-constrained vehicles. To tackle this issue …

With the surge in tasks for in-vehicle terminals, the resulting network congestion and time
delay cannot meet the service needs of users. Offloading algorithms are introduced to …

With the explosion of delay-sensitive and computation-intensive vehicular applications,
traditional cloud computing has encountered enormous challenges. Vehicular edge …

Task offloading decision is one of the core technologies of vehicular edge computing.
Efficient offloading decision can not only meet the requirements of complex vehicle tasks in …

Vehicular edge computing (VEC) effectively reduces the computing load of vehicles by
offloading computing tasks from vehicle terminals to edge servers. However, offloading of …

With the development of 5G and the Internet, the explosion of new mobile applications has
led to an increasing number of computation-intensive and latency-sensitive tasks, which …

Recent years have witnessed the explosive growth of ubiquitous vehicles with extremely
intelligent systems, which results in large amounts of data generated. Most of these vehicle …

Abstract Connected and Automated Vehicle (CAV) is a transformative technology that has
great potential to improve urban traffic and driving safety. Electric Vehicle (EV) is becoming …