QoEyes演示:完全在数据平面上实现虚拟现实流QoE估计

F. Vogt, F. R. Cesen, Ariel Góes De Castro, M. C. Luizelli, Christian Esteve Rothenberg, Gergely Pongrácz
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引用次数: 0

摘要

最近VR技术的进步创造了新的用户体验(例如,在线活动,游戏)。然而,确保用户体验仍然是一个挑战。主要是因为体验质量(QoE)测量仅限于用户或控制平面,导致不同场景(例如5G网络及更高版本)的高延迟。为了解决这一挑战,我们提出了QoEyes,一种基于可编程设备中测量的Inter-Packet-Gap (IPG)的网络内QoE估计技术。我们的研究结果表明,可以通过测量数据平面上的IPG来提供对用户QoE的强有力的估计。此外,在本演示中,我们使用在监控服务器上运行的Grafana仪表板实时显示此QoE估计和其他相关指标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Demo of QoEyes: Towards Virtual Reality Streaming QoE Estimation Entirely in the Data Plane
Recent advances in VR technology have created new user experiences (e.g., online events, gaming). However, ensuring the user experience is still a challenge. Mostly because Quality of Experience (QoE) measurement is limited to the user or control plane, causing high latencies for different scenarios (e.g., 5G networks and beyond). To address this challenge, we present QoEyes, an in-network QoE estimation technique based on Inter-Packet-Gap (IPG) measured in programmable devices. Our results show that a strong estimate of the user’s QoE can be provided by measuring the IPG on the data plane. Additionally, in this demonstration, we show this QoE estimate and other related metrics in real time, using a Grafana dashboard running in our monitoring server.
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