Towards network-wide QoE fairness using openflow-assisted adaptive video streaming

Panagiotis Georgopoulos, Yehia El-khatib, M. Broadbent, Mu Mu, N. Race
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引用次数: 253

Abstract

Video streaming is an increasingly popular way to consume media content. Adaptive video streaming is an emerging delivery technology which aims to increase user QoE and maximise connection utilisation. Many implementations naively estimate bandwidth from a one-sided client perspective, without taking into account other devices in the network. This behaviour results in unfairness and could potentially lower QoE for all clients. We propose an OpenFlow-assisted QoE Fairness Framework that aims to fairly maximise the QoE of multiple competing clients in a shared network environment. By leveraging a Software Defined Networking technology, such as OpenFlow, we provide a control plane that orchestrates this functionality. The evaluation of our approach in a home networking scenario introduces user-level fairness and network stability, and illustrates the optimisation of QoE across multiple devices in a network.
利用openflow辅助的自适应视频流实现全网QoE公平
视频流是一种日益流行的消费媒体内容的方式。自适应视频流是一种新兴的传输技术,旨在提高用户QoE和最大化连接利用率。许多实现从片面的客户端角度天真地估计带宽,而不考虑网络中的其他设备。这种行为会导致不公平,并可能降低所有客户端的QoE。我们提出了一个openflow辅助的QoE公平框架,旨在公平地最大化共享网络环境中多个竞争客户端的QoE。通过利用软件定义网络技术(如OpenFlow),我们提供了一个协调此功能的控制平面。在家庭网络场景中对我们的方法进行了评估,介绍了用户级公平性和网络稳定性,并说明了网络中多个设备之间的QoE优化。
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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