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A Simple Model for Predicting the Number and Duration of Rebuffering Events for YouTube Flows

机译:预测YouTube流重新缓冲事件的数量和持续时间的简单模型

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摘要

In this paper, we propose a simple model for predicting the number of rebuffering events and their duration in progressive downloads from YouTube. These metrics are necessary to predict the quality perceived by YouTube users. The proposed rebuffering model is based on two thresholds of the amount of data stored by the player buffer: the first threshold is extracted from the results of previous studies, and the second is derived from the experimental results presented in this paper. The proposed model can be easily implemented in simulation tools and we present an example of its use in a Long-Term Evolution simulator in which the mentioned quality metrics have been estimated for different users.
机译:在本文中,我们提出了一个简单的模型,用于预测从YouTube逐步下载中的重新缓冲事件的数量及其持续时间。这些指标对于预测YouTube用户的感知质量非常必要。所提出的重新缓冲模型基于玩家缓冲区存储的数据量的两个阈值:第一个阈值是从先前研究的结果中提取的,第二个阈值是从本文提出的实验结果中得出的。所提出的模型可以在仿真工具中轻松实现,并且我们提供了在长期演进仿真器中使用该模型的示例,其中已针对不同用户估算了提及的质量指标。

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