基于sdn的应用感知网络——以YouTube视频流为例

M. Jarschel, Florian Wamser, Thomas Hohn, T. Zinner, P. Tran-Gia
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引用次数: 154

摘要

应用感知网络是一种很有前途的方法,可以在网络资源有限的情况下(如今天的接入网)为用户提供良好的应用质量。有了SDN,一种特别有趣的方法可以在网络中实现基于流的流量管理。在这项工作中,我们来看看一个特定的应用程序,即YouTube流媒体,如何从这样一个基于sdn的应用感知网络中受益。我们实现并研究了一种基于深度包检测(DPI)的方法和一种基于OpenFlow测试平台中应用程序直接信息输入的方法,以展示如何利用这些不同类型的应用程序信息来提高体验质量(QoE)。此外,我们还确定了每种方法造成的开销。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SDN-Based Application-Aware Networking on the Example of YouTube Video Streaming
Application-Aware Networking is a promising approach to provide good application quality to users in scenarios with limited network resources, like today's access networks. With SDN, a particularly interesting method to enable flowbased traffic management in networks has become available. In this work we take a look at how a specific application, i.e., YouTube Streaming, can benefit from such an SDN-based Application-Aware Network. We implement and investigate an approach based on Deep Packet Inspection (DPI) and one based on direct information input from the application in an OpenFlow testbed in order to show, how these different types of application information can be exploited to enhance the Quality of Experience (QoE). Furthermore, we determine the overhead caused by each of the presented approaches.
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