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Architectural Design Alternatives based on Cloud/Edge/Fog Computing for Connected Vehicles
IEEE Communications Surveys & Tutorials ( IF 34.4 ) Pub Date : 2020-01-01 , DOI: 10.1109/comst.2020.3020854
Haoxin Wang , Tingting Liu , BaekGyu Kim , Chung-Wei Lin , Shinichi Shiraishi , Jiang Xie , Zhu Han

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.

中文翻译:

基于云/边缘/雾计算的互联车辆架构设计替代方案

随着汽车在人们的日常生活中扮演着越来越重要的角色,对更安全、更舒适的驾驶体验的要求也随之而来。联网汽车(CV)可以提供实现这些要求的使能技术,并引起了学术界和工业界的广泛关注。这些要求要求设计良好的计算架构来支持 CV 应用程序的服务质量 (QoS)。计算卸载技术,如云计算、边缘计算和雾计算,可以帮助 CV 处理计算密集型和大规模计算任务。此外,不同的云/边缘/雾计算架构适合支持不同类型的 CV 应用,其 QoS 要求差异很大,这说明了计算架构设计的重要性。然而,大多数现有的关于 CV 的云/边缘/雾计算的调查都忽略了计算架构设计,他们 (i) 只关注一种特定的计算架构,并且 (ii) 缺乏对不同架构的好处、研究挑战和系统要求的讨论备择方案。在本文中,我们对基于 CV 的云/边缘/雾计算的不同架构设计备选方案进行了全面调查。本文的贡献是:(i) 对现有的基于云/边缘/雾计算的 CV 架构设计替代方案进行了全面的文献调查,(ii) 提出了基于云/边缘/雾计算的计算架构的新分类对于 CV:计算辅助和支持计算的架构,
更新日期:2020-01-01
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