Year: 2020
Type: article
Abstract: As vehicles playing an increasingly important role in people's daily life, requirements on safer and more comfortable driving experience have arisen. Connected vehicles (CVs) can provide enabling technologies to realize these requirements and have attracted widespread attentions from both academia and industry. These requirements ask for a well-designed computing architecture to support the Quality-of-Service (QoS) of CV applications. Computation offloading techniques, such as cloud, edge, and fog computing, can help CVs process computation-intensive and large-scale computing tasks. Additionally, different cloud/edge/fog computing architectures are suitable for supporting different types of CV applications with highly different QoS requirements, which demonstrates the importance of the computing architecture design. However, most of the existing surveys on cloud/edge/fog computing for CVs overlook the computing architecture design, where they (i) only focus on one specific computing architecture and (ii) lack discussions on benefits, research challenges, and system requirements of different architectural alternatives. In this article, we provide a comprehensive survey on different architectural design alternatives based on cloud/edge/fog computing for CVs. The contributions of this article are: (i) providing a comprehensive literature survey on existing proposed architectural design alternatives based on cloud/edge/fog computing for CVs, (ii) proposing a new classification of computing architectures based on cloud/edge/fog computing for CVs: computation-aided and computation-enabled architectures, (iii) presenting a holistic comparison among different cloud/edge/fog computing architectures for CVs based on functional requirements of CV systems, including advantages, disadvantages, and research challenges, (iv) presenting a holistic overview on the design of CV systems from both academia and industry perspectives, including activities in industry, functional requirements, service requirements, and design considerations, and (v) proposing several open research issues of designing cloud/edge/fog computing architectures for CVs.
Authors: Haoxin Wang, Tingting Liu, BaekGyu Kim, Chung-Wei Lin, Shinichi Shiraishi, Jiang Xie, Zhu Han
Language: English
Topic: IoT and Edge/Fog Computing
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Awards: SpecEES: Intelligent Energy Efficient Spectrum Access for Wireless IoT, CNS Core: Small: MAC Layer Failure Control and Avoidance in Cognitive Radio Networks, 无线内容分发网络中基于边缘存储技术的激励机制与优化方法的研究, NeTS: Small: Collaborative Research: Hierarchical Framework with Distributed Resource Allocation for Mobile Fog Computing, G2053853133, CNS Core: Small: Towards Seamless Mobility in Mobile Edge Computing Networks, Collaborative Research: Exploiting Upper Layer Spectrum Sensing and Directionality to Access the Hidden Available Spectrum, Collaborative Research: Energy-Efficient Heterogeneous Network Virtualization with Spectrum-Power Trading, NeTS: Small: Collaborative Research: Hierarchical Framework with Distributed Resource Allocation for Mobile Fog Computing, WiFIUS: Collaborative Research: Ambient Re-Scatter Inspired Machine Type Communication for Heterogeneous IoT Systems
OpenAlex ID: W3082239611