Zhihan Liu

TL;DR: An abstract network model of the IoV is proposed, the technologies required to create the IoVs are discussed, different applications based on certain currently existing technologies are presented, and essential future research is described in the area of IoV.

TL;DR: This article proposes a two-level edge computing architecture for automated driving services in order to make full use of the intelligence at the wireless edge (i.e., base stations and autonomous vehicles) for coordinated content delivery and investigates the research challenges of wireless edge caching and vehicular content sharing.

TL;DR: This paper introduces an edge computing based hierarchical architecture for efficient distribution of large-volume vehicular data and proposes a multi-place multi-factor prefetching scheme to meet the rapid topology change and unbalanced traffic.

TL;DR: This paper proposes a novel proactively load balancing approach that enables efficient cooperation among MESs, referred to as end-to-end load balancer (E2LB), which can guarantee the real-time scheduling, since the calling of a well-trained neural network only requires a small number of simple operations.

TL;DR: A congestion detection and notification scheme using VANETs for urban expressways that adopts a simplified Doppler frequency shift method and develops a spatial–temporal effectiveness model based on the potential energy theory to control the dissemination area and survival time of the congestion information.