Tube streaming: Modelling collaborative media streaming in urban railway networks
Tube streaming: Modelling collaborative media streaming in urban railway networks
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DOI：
10.1109/ifipnetworking.2016.7497247
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发表时间：
2016-05
期刊：
影响因子：
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通讯作者：
Argyrios G. Tasiopoulos;I. Psaras;Vasilis Sourlas;G. Pavlou
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文献类型：
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作者：
Argyrios G. Tasiopoulos;I. Psaras;Vasilis Sourlas;G. Pavlou
我们提出了一个质量评估框架，在城市铁路网络的众包流媒体。我们假设通勤者要么“收听”某个电视/广播频道，要么提交他们希望观看或收听的内容的请求，最终形成视频/播客/曲调的播放列表。鉴于连接受到列车移动和这种移动导致的断开的挑战，用户协作地下载（通过蜂窝和WiFi连接）和共享内容，以保持不中断的播放。我们为伦敦地铁网络的情况下，协作媒体流建模。所提出的质量评估框架包括一个效用函数，该效用函数表征用户（主观）感知的体验质量（QoE），并考虑到影响平滑播放的所有必要参数。通过调整相关参数，该框架可用于评估任何铁路网络中的流媒体质量。据我们所知，这是第一项从建模角度而不是系统角度量化（地下）铁路网络中协作媒体流的感知质量的研究。基于来自伦敦地铁网络的真实的通勤者轨迹，我们评估音频和视频是否可以以可接受的QoE流传输到通勤者。我们的研究结果表明，即使有非常高速的互联网连接，用户仍然会遇到中断，但精心设计的协作机制可以导致高水平的感知QoE，即使在这种破坏性的情况下。
We propose a quality assessment framework for crowdsourced media streaming in urban railway networks. We assume that commuters either “tune in” to some TV/radio channel, or submit requests for content they desire to watch or listen to, which eventually forms a playlist of videos/podcasts/tunes. Given that connectivity is challenged by the movement of trains and the disconnection that this movement causes, users collabo-ratively download (through cellular and WiFi connections) and share content, in order to maintain undisrupted playback. We model collaborative media streaming for the case of the London Underground train network. The proposed quality assessment framework comprises a utility function which characterises the Quality of Experience (QoE) that users (subjectively) perceive and takes into account all the necessary parameters that affect smooth playback. The framework can be used to assess the media streaming quality in any railway network, after adjusting the related parameters. To the best of our knowledge, this is the first study to quantify the perceptual quality of collaborative media streaming in (underground) railway networks from a modelling perspective, as opposed to a systems perspective. Based on real commuter traces from the London Underground network, we evaluate whether audio and video can be streamed to commuters with acceptable QoE. Our results show that even with very high-speed Internet connection, users still experience disruptions, but a carefully designed collaborative mechanism can result in high levels of perceived QoE even in such disruptive scenarios.