Edge computing is the key to building 5G Networks and Future 2030 Networks. Edge
computing extends the cloud computing paradigm by placing resources close to the network …

With the rise of intelligent transportation systems and the increasing diversity of vehicular
applications, such as safety-related features, parking navigation, and multimedia …

With the emergence of new vehicle‐mounted services, such as autonomous driving and
augmented reality, the computing capability at the edge of the Internet of vehicles (IoV) has …

Aiming at the problem that fixed mobile edge computing (MEC) server is difficult to meet the
needs of mobile users and temporary computing services, this study proposes a network …

Low-latency IoT applications, such as autonomous vehicles, augmented/virtual reality
devices, and security applications, require high computation resources to make decisions on …

The contradiction between limited network resources and a large number of user demands
in vehicle environment will cause a lot of system delay and energy consumption. To solve …

Edge Computing and Network Function Virtualization (NFV) concepts can improve network
processing and multi-resources allocation when intelligent optimization algorithms are …

Digital twin (DT) has emerged as a promising technology for improving resource allocation
decisions in Internet of Vehicles (IoV) networks. In this paper, we consider an IoV network …

With the development of various vehicle applications, such as vehicle social networking,
pattern recognition, and augmented reality, diverse and complex tasks have to be executed …

Edge computing extends the Cloud computing paradigm by providing computation
resources at the edge of the network where data is being generated to effectively meet the …