论文标题
软件化，虚拟化和机器学习，用于智能有效的V2X通信
Softwarization, Virtualization, & Machine Learning For Intelligent & Effective V2X Communications
论文作者
论文摘要
近年来，由于电信运营商和服务提供商希望升级其基础架构和交付模式以满足不断增长的需求，因此第五代（5G）移动网络系统的概念已经出现。软质量，虚拟化和机器学习等概念将是此类网络的创新和灵活推动者的关键组成部分。特别是，诸如软件定义的网络，软件定义的周边，云和边缘计算以及网络功能虚拟化等范例将在应对几个5G网络的挑战方面发挥重要作用，尤其是在灵活性，可编程性，可伸缩性和安全性方面。在这项工作中，讨论了这些范式在V2X通信中的作用和潜力。为此，本文通过提供V2X通信的概述和背景开始。然后，本文在更多细节中讨论了V2X通讯所面临的各种挑战以及以前的一些文献工作以解决这些问题。此外，本文描述了软件化，虚拟化和机器学习如何适应以应对此类网络的挑战。
The concept of the fifth generation (5G) mobile network system has emerged in recent years as telecommunication operators and service providers look to upgrade their infrastructure and delivery modes to meet the growing demand. Concepts such as softwarization, virtualization, and machine learning will be key components as innovative and flexible enablers of such networks. In particular, paradigms such as software-defined networks, software-defined perimeter, cloud & edge computing, and network function virtualization will play a major role in addressing several 5G networks' challenges, especially in terms of flexibility, programmability, scalability, and security. In this work, the role and potential of these paradigms in the context of V2X communication is discussed. To do so, the paper starts off by providing an overview and background of V2X communications. Then, the paper discusses in more details the various challenges facing V2X communications and some of the previous literature work done to tackle them. Furthermore, the paper describes how softwarization, virtualization, and machine learning can be adapted to tackle the challenges of such networks.
