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Virtualized Network Function Orchestration System and Experimental Network Based QR Recognition for a 5G Mobile Access Network

机译:基于虚拟网络功能的编排系统和基于实验网络的5G移动接入网QR识别

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This paper proposes a virtualized network function orchestration system based on Network Function Virtualization (NFV), one of the main technologies in 5G mobile networks. This system should provide connectivity between network devices and be able to create flexible network function and distribution. This system focuses more on access networks. By experimenting with various scenarios of user service established and activated in a network, we examine whether rapid adoption of new service is possible and whether network resources can be managed efficiently. The proposed method is based on Bluetooth transfer technology and mesh networking to provide automatic connections between network machines and on a Docker flat form, which is a container virtualization technology for setting and managing key functions. Additionally, the system includes a clustering and recovery measure regarding network function based on the Docker platform. We will briefly introduce the QR code perceived service as a user service to examine the proposal and based on this given service, we evaluate the function of the proposal and present analysis. Through the proposed approach, container relocation has been implemented according to a network device?¢????s CPU usage and we confirm successful service through function evaluation on a real test bed. We estimate QR code recognition speed as the amount of network equipment is gradually increased, improving user service and confirm that the speed of recognition is increased as the assigned number of network devices is increased by the user service.
机译:本文提出了一种基于网络功能虚拟化(NFV)的虚拟化网络功能协调系统,这是5G移动网络中的主要技术之一。该系统应提供网络设备之间的连接性,并能够创建灵活的网络功能和分布。该系统更侧重于接入网。通过试验在网络中建立和激活的用户服务的各种方案,我们研究了是否有可能快速采用新服务以及是否可以有效地管理网络资源。所提出的方法基于蓝牙传输技术和网状网络,以提供网络机器之间的自动连接,并采用Docker扁平形式,这是一种用于设置和管理关键功能的容器虚拟化技术。此外,该系统还包括基于Docker平台的有关网络功能的群集和恢复措施。我们将简要介绍QR码感知服务作为用户服务来检查提案,并基于该给定服务评估提案的功能并进行分析。通过提出的方法,已根据网络设备的CPU使用率实现了容器重定位,并且我们通过在实际测试台上进行功能评估来确认服务成功。我们估计随着网络设备数量的逐渐增加,用户服务水平的提高,QR码识别速度会提高,并确认随着用户服务增加网络设备的分配数量,识别速度也会随之提高。

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