1 Introduction

Fog Computing is a paradigm that extends Cloud Computing, which emphasizes proximity to end-users and client objectives, dense geographical distribution and local resource pooling, latency reduction for quality of service, and edge analytics, resulting in superior user experience and redundancy in case of failure.

As more and more resources, such as computational power, storage, networking, and even electrical power, are integrated in vehicles, connected vehicles and roadside unites constitute a perfect Fog Computing platform. With the vast number of vehicles and their extraordinary mobility and wide distribution, a vehicular fog is the ideal platform to deliver a rich menu of services in infotainment, safety, traffic support, and analytics. The realization of vehicular fogs involves research in several disciplines including sensor technology, vehicular technology, wireless communication technology, and various technologies in computer science such as software engineering, artificial intelligence, big data analytics, and others. The research in vehicular fogs is interdisciplinary surrounding IoTs applications. Besides, the concept of vehicular fogs is new, with growing interest from the research community.

The aim of this special issue is to provide an introduction to the burgeoning theme of fog computing on connected vehicles and to collect articles about ideas, concepts, models, technologies, approaches, methodologies, and practices of vehicular fogs. Following an open call for papers, 15 technical papers are reviewed by at least three reviewers for their technical merit, scope, and relevance to the scope of this special issue, and 7 of them are selected and cover various areas within this theme, ranging from vehicular fog computing architecture to security problem in the system.

The first article, by Yuanguo Bi on “Neighboring vehicle-assisted fast handoff for vehicular fog communications” proposes a cross-layer and neighboring vehicle-aided fast handoff scheme to provide a satisfactory user experience of accessing Internet on mobile vehicles. The second article entitled “Fog computing enabling geographic routing for urban area vehicular network” by Ting Lu, Shan Chang, and Wei Li presents a position-based routing scheme for the inter-vehicle communication in city environments, leveraging vehicular fog computing to make the best utilization of the vehicular communication and computational resources. In “Connection is power: Near optimal advertisement infrastructure placement for vehicular fogs”, Wanru Xu, Panlong Yang, and Lijing Jiang undertake a theoretical analysis on mobile advertisement infrastructure deployment problem and the interaction between this deployment and vehicular fogs. The fourth article by Kai Fan, Junxiong Wang, Xin Wang, Hui Li, and Yintang Yang on “Secure, efficient and revocable data sharing scheme for vehicular fogs” presents how to utilize vehicular fog platform to achieve data sharing in vehicular networks. In “Towards fast and lightweight spam account detection in mobile social networks through fog computing”, Jiahao Zhang, Qiang Li, Xiaoqi Wang, Bo Feng, and Dong Guo present how to use vehicular fog to detect spam account in mobile social networks in a fast and lightweight way. The sixth article on “Efficient multi-tasks scheduling algorithm in mobile cloud computing with time constraints” by Tongxiang Wang, Xianglin Wei, Chaogang Tang, and Jianhua Fan investigates the mobile-cloud-computing-assisted execution of multi-tasks scheduling problem in hybrid computing architecture. The last (but not least) paper on “A multi-vessels cooperation scheduling for networked maritime fog-ran architecture leveraging SDN” by Tingting Yang, ZhengQi Cui, Rui Wang, Jian Zhao, Zhou Su, and Ruilong Deng integrates SDN and fog computing into maritime wideband communications system so as to achieve the minimized delay of weighted uploading packets.

Collectively, these 7 papers illustrate the diverse range of issues, providing a detailed compilation of the diverse range of issue currently being investigated in the field of vehicular fog computing.