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QWatch: Detecting and Locating QoE Anomaly for VoD in the Cloud

机译:QWatch:在云中检测和定位VoD的QoE异常

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Commercial large-scale VoD systems such as Netflix and Hulu rely on CDNs to deliver videos to users around the world. Various anomalies occur often and degrade users' Quality of Experience (QoE). Detecting and locating such anomalies are highly complex due to a large number of different entities involved in the end-to-end video delivery. These entities include VoD provider, CDN/Cloud providers, transit ISPs, access ISPs, and end user devices. QoE perceived by the users is a critical metric for VoD providers. We propose QWatch, a scalable monitoring system, which detects and locates anomalies based on the end user QoE in real-time. We evaluate QWatch in a controlled VoD system and production Microsoft Azure Cloud and CDN. QWatch effectively detects and locates QoE anomalies in our extensive experiments. We discuss insights obtained from running VoD system with 200 worldwide users in production Cloud.
机译:Netflix和Hulu等商业大型VoD系统依靠CDN向世界各地的用户提供视频。各种异常现象经常发生,并降低用户的体验质量(QoE)。由于端到端视频传递中涉及大量不同的实体,因此检测和定位此类异常情况非常复杂。这些实体包括VoD提供程序,CDN /云提供程序,中转ISP,访问ISP和最终用户设备。用户感知的QoE是VoD提供者的关键指标。我们建议使用QWatch,这是一种可扩展的监视系统,它可以根据最终用户QoE实时检测和定位异常。我们在受控的VoD系统和生产的Microsoft Azure云和CDN中评估QWatch。在我们广泛的实验中,QWatch有效地检测并定位了QoE异常。我们讨论了与生产Cloud中200个全球用户一起运行VoD系统获得的见解。

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