New technologies bring opportunities to deploy AI and machine learning to the edge of the
network, allowing edge devices to train simple models that can then be deployed in practice …

With the rapid growth of connected and autonomous vehicles (CAVs), vehicular
crowdsensing (VCS) has emerged as an effective way in a wide range of applications …

Facing the requirements of intelligent vehicles for massive data processing, vehicular edge
computing (VEC) utilizes computing resources deployed on the roadside infrastructure to …

The rapid growth of vehicular applications has resulted in high demand for Internet
technology, which demands an unprecedented network capacity and a high quality of …

The emerging vehicular connected applications, such as cooperative automated driving and
intersection collision warning, show great potentials to improve the driving safety, where …

Decentralized Autonomous Organizations (DAOs) have been gaining popularity in recent
years due to their promise of realizing the decentralized Web 3.0. However, most DAOs rely …

Data security and integrity are becoming increasingly important as the volume of data being
created and stored grows. A controlled third party that provides most of the existing big data …

This paper proposes a new efficient certificateless conditional privacy preserving
authentication (CL-CPPA) scheme named ELCPAS, which is pairing-free, energy-efficient …

Multi-access edge computing (MEC) technology is widely deployed at the edge of Vehicular
Ad hoc Networks (VANETs) to enhance their communication and computational capabilities …

In this paper, we study a tracking service vehicular edge computing (VEC) network that
provides computation offloading service for Intelligent vehicles, where computational tasks …