Software-Defined Vehicular Networks: A Cooperative Approach for Computational Offloading

S. Shah, M. Gregory, Shuo Li
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Abstract

Conventional vehicular systems are gradually evolving into intelligent transportation systems. Multi-access Edge Computing (MEC) has become an important component of the software-defined vehicular networks that benefit from the introduction of reliable and low latency 5G networks and Wi-Fi. MEC offers a variety of smart services closer to the access networks leveraged by vehicles. The intelligent and connected vehicles demand access to compute-intensive applications that require compute and storage resources in addition to what is available in vehicles today. The computational burden on the connected vehicles can be significantly reduced by offloading to the MEC nodes and to the cloud. However, existing computational offloading schemes are challenged by the fast-moving vehicles, frequent handovers and subtle differences to the scenarios designed to support mobile phone handovers. The paper presents a software-defined vehicular edge computing architecture that copes with the mobility challenges by utilising the Software Defined Networking paradigm to perform traffic flow management for information collection and intelligent management of connected vehicles and networks.
软件定义的车辆网络:一种计算卸载的协作方法
传统的车辆系统正逐步向智能交通系统发展。多接入边缘计算(MEC)已成为软件定义车辆网络的重要组成部分,该网络受益于可靠和低延迟的5G网络和Wi-Fi的引入。MEC提供各种智能服务,更接近车辆利用的接入网络。智能互联汽车需要访问计算密集型应用程序,这些应用程序需要计算和存储资源。通过卸载到MEC节点和云,可以显著减少联网车辆的计算负担。然而,现有的计算卸载方案受到快速移动的车辆、频繁的切换以及与支持手机切换的场景的细微差异的挑战。本文提出了一种软件定义的车辆边缘计算架构,该架构通过利用软件定义的网络范式来执行交通流量管理,以便对连接的车辆和网络进行信息收集和智能管理,从而应对移动性挑战。
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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