Understanding the impact of network dynamics on mobile video user engagement

M. Shafiq, Jeffrey Erman, Lusheng Ji, A. Liu, Jeffrey Pang, Jia Wang
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引用次数: 139

Abstract

Mobile network operators have a significant interest in the performance of streaming video on their networks because network dynamics directly influence the Quality of Experience (QoE). However, unlike video service providers, network operators are not privy to the client- or server-side logs typically used to measure key video performance metrics, such as user engagement. To address this limitation, this paper presents the first large-scale study characterizing the impact of cellular network performance on mobile video user engagement from the perspective of a network operator. Our study on a month-long anonymized data set from a major cellular network makes two main contributions. First, we quantify the effect that 31 different network factors have on user behavior in mobile video. Our results provide network operators direct guidance on how to improve user engagement --- for example, improving mean signal-to-interference ratio by 1 dB reduces the likelihood of video abandonment by 2%. Second, we model the complex relationships between these factors and video abandonment, enabling operators to monitor mobile video user engagement in real-time. Our model can predict whether a user completely downloads a video with more than 87% accuracy by observing only the initial 10 seconds of video streaming sessions. Moreover, our model achieves significantly better accuracy than prior models that require client- or server-side logs, yet we only use standard radio network statistics and/or TCP/IP headers available to network operators.
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了解网络动态对移动视频用户参与的影响
移动网络运营商对其网络上流媒体视频的性能非常感兴趣,因为网络动态直接影响体验质量(QoE)。然而,与视频服务提供商不同,网络运营商并不了解客户端或服务器端日志,这些日志通常用于衡量关键视频性能指标,如用户参与度。为了解决这一限制,本文首次从网络运营商的角度对蜂窝网络性能对移动视频用户参与的影响进行了大规模研究。我们对一个主要蜂窝网络长达一个月的匿名数据集的研究有两个主要贡献。首先,我们量化了31种不同的网络因素对移动视频用户行为的影响。我们的研究结果为网络运营商提供了如何提高用户参与度的直接指导——例如,将平均信干扰比提高1 dB,可将视频放弃的可能性降低2%。其次,我们模拟了这些因素与视频放弃之间的复杂关系,使运营商能够实时监控移动视频用户的参与度。我们的模型可以通过观察视频流会话的最初10秒来预测用户是否完全下载视频,准确率超过87%。此外,我们的模型比之前需要客户端或服务器端日志的模型实现了更好的准确性,但我们只使用标准的无线网络统计数据和/或网络运营商可用的TCP/IP头。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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