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A new three-layer QoE modeling method for HTTP video streaming over wireless networks

机译:无线网络上HTTP视频流的一种新的三层QoE建模方法

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Quality of experience (QoE) indicates users' perception of an Internet service or business in objective conditions, which is significantly meaningful to service providers or network operators to improve their quality of services and to utilize valuable network resources efficiently. Online video service has become the most fast-growing Internet service in recent years. Building models for QoE evaluation of video services has become a hot research topic. In this paper, we propose three metrics to evaluate buffering situations of HTTP video streaming, which have been verified to be the main factors that influence the QoE of network videos, and together with three fundamental quality of service (QoS) parameters, to build a three-layer QoE model for HTTP video streaming. Then, we use linear regression and BPNN (back propagation neural network) to reflect the mapping relations of the QoS parameters, buffering-related metrics and QoE, and demonstrate that BPNN performs better than linear regression in this situation.
机译:体验质量(QoE)表示用户在客观条件下对Internet服务或业务的感知,这对于服务提供商或网络运营商提高其服务质量并有效利用宝贵的网络资源具有重大意义。在线视频服务已成为近年来发展最快的Internet服务。建立视频服务QoE评估模型已经成为研究的热点。在本文中,我们提出了三个指标来评估HTTP视频流的缓冲情况,这些指标已被证明是影响网络视频QoE的主要因素,并与三个基本服务质量(QoS)参数一起构建了一个HTTP视频流的三层QoE模型。然后,我们使用线性回归和BPNN(反向传播神经网络)来反映QoS参数,与缓冲相关的指标和QoE的映射关系,并证明在这种情况下BPNN的性能要优于线性回归。

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