Towards Fog-based Next Generation Internet of Vehicles Architecture

S. A. Siddiqui, A. Mahmood
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引用次数: 3

Abstract

Internet of Vehicles (IoV) is an integral component of the Intelligent Transportation System (ITS) with the vision to acquire and process data for improving traffic safety. In IoV, vehicles communicate by exchanging messages with other vehicles and roadside infrastructure subsequently generating a large volume of data often referred to as big data, and which demands a massive storage and high computational capability with minimal possible delay. The aim of this paper is to take a step forward in outlining the current state-of-the-art in IoV and analyzing the improved data processing and storage features by utilizing big data analytics and fog computing paradigm. We further presented a preliminary simulation result to demonstrate that the introduction of fog improves the overall system performance by ensuring low-latency critical for especially vehicular safety applications. Moreover, this paper briefly discusses a fog computing based IoV crime assistant and highlight some of its challenges which needs to be addressed in order to enhance the performance of such systems.
迈向基于雾的下一代车联网架构
车联网(IoV)是智能交通系统(ITS)的一个组成部分,其愿景是获取和处理数据以改善交通安全。在车联网中,车辆通过与其他车辆和路边基础设施交换信息进行通信,随后产生大量数据,通常称为大数据,这需要大量存储和高计算能力,并尽可能减少延迟。本文的目的是进一步概述当前车联网的最新技术,并通过利用大数据分析和雾计算范式分析改进的数据处理和存储特征。我们进一步提出了一个初步的模拟结果,以证明雾的引入通过确保低延迟来提高整体系统性能,特别是在车辆安全应用中。此外,本文简要讨论了基于雾计算的车联网犯罪助手,并强调了为了提高此类系统的性能需要解决的一些挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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