In recent years, the number of IoT devices has been growing fast which leads to a challenging task for managing, storing, analyzing, and making decisions about raw data from different IoT devices, especially for delay-sensitive applications. In a vehicular network (VANET) environment, the dynamic nature of vehicles makes the current open research issues even more challenging due to the frequent topology changes that can lead to disconnections between vehicles. To this end, a number of research works have been proposed in the context of cloud and fog computing over the 5G infrastructure. On the other hand, there are a variety of research proposals that aim to extend the connection time between vehicles. Vehicular Social Networks (VSNs) have been defined to decrease the burden of connection time between the vehicles. This survey paper first provides the necessary background information and definitions about fog, cloud and related paradigms such as 5G and SDN. Then, it introduces the reader to Vehicular Social Networks, the different metrics and the main differences between VSNs and Online Social Networks. Finally, this survey investigates the related works in the context of VANETs that have demonstrated different architectures to address the different issues in fog computing. Moreover, it provides a categorization of the different approaches and discusses the required metrics in the context of fog and cloud and compares them to Vehicular social networks. A comparison of the relevant related works is discussed along with new research challenges and trends in the domain of VSNs and fog computing.
翻译:近几年来,IOT装置的数量迅速增长,导致管理、储存、分析和决定不同IOT装置的原始数据,特别是延迟敏感应用程序的原始数据的任务具有挑战性。在车辆网络(VANET)环境中,机动车辆的动态性质使得当前的公开研究问题更加具有挑战性,因为频繁的地形变化可能导致车辆之间的脱节。为此,在5G基础设施的云雾计算方面提出了一些研究项目。另一方面,有各种研究提议,旨在延长车辆之间的连接时间。SNSN社会网络(VSNS)被确定为减少车辆之间连接时间的负担。这份调查文件首先提供有关雾、云和相关模式的必要背景资料和定义,如5G和SDN。随后,它向读者介绍VSNS和在线社会网络之间的云雾计算,不同尺度和在线社会网络之间的主要差异。最后,这次调查调查调查了VANSNET和网络的关联工作,将VANet网络和VA的网络与不同域域域域域图的对比,将VA和VA网络的相关结构与不同的模型进行比较。