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Video QoE killer and performance statistics in WebRTC-based video communication

机译:基于WebRTC的视频通信中的视频QoE杀手和性能统计

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In this paper, we investigate session-related performance statistics of a Web-based Real-Time Communication (WebRTC) application called appear.in. We explore the characteristics of these statistics and explore how they may relate to users' Quality of Experience (QoE). More concretely, we have run a series of tests involving two parties and according to different test scenarios, and collected real-time session statistics by means of Google Chrome's WebRTC-internals tool. Despite the fact that the Chrome statistics have a number of limitations, our observations indicate that they are useful for QoE research when these limitations are known and carefully handled when performing post-processing analysis. The results from our initial tests show that a combination of performance indicators measured at the sender's and receiver's end may help to identify severe video freezes (being an important QoE killer) in the context of WebRTC-based video communication. In this paper the performance indicators used are significant drops in data rate, non-zero packet loss ratios, non-zero PLI values, and non-zero bucket delay.
机译:在本文中,我们调查了一个名为see.in的基于Web的实时通信(WebRTC)应用程序与会话相关的性能统计信息。我们探索了这些统计数据的特征,并探讨了它们可能与用户的体验质量(QoE)之间的关系。更具体地说,我们已经根据不同的测试场景进行了涉及两方的一系列测试,并通过Google Chrome的WebRTC-internals工具收集了实时会话统计信息。尽管Chrome统计信息存在许多局限性,但我们的观察表明,只要知道这些局限性并在进行后处理分析时仔细处理,它们对于QoE研究很有用。我们初步测试的结果表明,在基于WebRTC的视频通信中,在发送者和接收者端测量的性能指标的组合可能有助于识别严重的视频冻结(是重要的QoE杀手)。在本文中,所使用的性能指标是数据速率的显着下降,非零丢包率,非零PLI值和非零桶延迟。

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