Scalable Network and Transport Supports for QoE Fairness in Streaming Media Services

可扩展的网络和传输支持流媒体服务中的 QoE 公平性

• 批准号: 2096280
• 金额: --
• 依托单位: University of St Andrews
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2096280
• 关键词: Scalable; Network; Transport; Supports; QoE

Video streaming applications have become ubiquitous and are predicted to account for 82% of global IP traffic by the year 2021[1]. Providers such as Netflix and Amazon increasingly seek to replace rather than complement the tradition television experience, aided by the availability of clients for multiple devices allowing multiple users to stream video content simultaneously.There are competing industry standards aimed at ensuring quality of experience (QoE) for users, one example is Dynamic Adaptive Streaming over HTTP (DASH). Used by Netflix and YouTube among others, DASH is a codec-agnostic technique for delivering content from HTTP servers. Media is broken into equal length, non-overlapping segments, encoded at various bitrates and made available from the server. Client applications request media at the highest bitrate possible based on current network conditions. The requested bitrate can be varied from one segment to another depending on fluctuations in available bandwidth.DASH and similar standards aim to ensure the best possible QoE for application users. However, given the shift in user habits, video streams now frequently compete with each other for bandwidth behind a common network bottleneck, most often a home router. Recent work in this area has shown the current adaptation mechanisms do not improve QoE, but instead lead to instability for users and unfairness between competing applications.In order to provide a long term solution to this problem it is necessary to explore a new network- wide architecture that implements an approach similar to Transport-Independent Path Layer State Management[4] This builds upon the work in to enable client applications to expose the information necessary to optimise QoE at a network level.

视频流应用已变得无处不在，预计到 2021 年将占全球 IP 流量的 82%[1]。 Netflix 和 Amazon 等提供商越来越多地寻求取代而不是补充传统电视体验，这得益于多个设备的客户端可用性，允许多个用户同时流式传输视频内容。存在旨在确保用户体验质量 (QoE) 的竞争行业标准，一个例子是基于 HTTP 的动态自适应流式传输 (DASH)。 DASH 是一种与编解码器无关的技术，用于从 HTTP 服务器传输内容，Netflix 和 YouTube 等公司都在使用它。媒体被分成等长、不重叠的片段，以不同的比特率进行编码并从服务器提供。客户端应用程序根据当前网络条件以尽可能高的比特率请求媒体。根据可用带宽的波动，请求的比特率可能会因可用带宽的波动而有所不同。DASH 和类似标准旨在确保应用程序用户获得最佳的 QoE。然而，鉴于用户习惯的转变，视频流现在经常在常见网络瓶颈（通常是家庭路由器）后面相互竞争带宽。该领域的最新工作表明，当前的适应机制不会改善 QoE，反而会导致用户不稳定和竞争应用程序之间的不公平。为了提供此问题的长期解决方案，有必要探索一种新的网络范围架构，该架构实现类似于传输独立路径层状态管理[4]的方法。这建立在使客户端应用程序能够公开在网络级别优化 QoE 所需的信息的基础上。