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Bridging the Gap between QoE and User Engagement in HTTP Video Streaming

机译:弥合HTTP视频流中QoE和用户参与之间的差距

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On video streaming platforms, users expect a high Quality of Experience (QoE). In contrast, service and content providers aim at high User Engagement, most notably because their revenue is usually dependent on it. In order to satisfy users, it is critical to know how QoE is related to the User Engagement. However, no model for this relation exists yet. Current approaches to managing QoE are usually based on traffic analysis. However, this will become more difficult in the future since the encryption of Internet traffic progresses. In this paper, we present an approach to bringing QoE and User Engagement together with video streaming as the use case. We do this by fitting existing measurement data of User Engagement to obtain a model. Furthermore, we extend the existing queuing model for QoE and investigate the correlation between QoE and User Engagement in a simulation. Hereby, we model different scenarios where we quantify network bandwidth and video requirements. Our results show that there is a strong correlation between QoE and User Engagement. Additionally, we observe that simple buffer policies, which do not rely on buffer information, can still perform well. These revelations open the way for new approaches to QoE Management in the future Internet.
机译:在视频流平台上,用户期望获得高质量的体验(QoE)。相比之下,服务和内容提供商的目标是提高用户参与度,最显着的原因是其收入通常取决于用户参与度。为了使用户满意,了解QoE与用户参与的关系至关重要。但是,还没有这种关系的模型。当前管理QoE的方法通常基于流量分析。但是,随着Internet流量加密的进行,这在将来将变得更加困难。在本文中,我们提出了一种将QoE和用户参与度以及视频流作为用例结合在一起的方法。我们通过拟合用户参与度的现有测量数据来获得模型。此外,我们扩展了现有的QoE排队模型,并在仿真中研究了QoE与用户参与度之间的相关性。因此,我们在量化网络带宽和视频需求的不同场景中建模。我们的结果表明,QoE与用户参与度之间存在很强的相关性。此外,我们观察到不依赖于缓冲区信息的简单缓冲区策略仍然可以很好地执行。这些发现为将来的Internet中的QoE管理新方法开辟了道路。

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