Adaptive and High-Quality Multimedia Streaming

自适应和高质量多媒体流

• 批准号: RGPIN-2016-03699
• 负责人: Wang, Mea
• 金额: $ 1.89万
• 依托单位: University of Calgary
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=634286
• 关键词: Adaptive; Quality; Multimedia; Streaming

Multimedia streaming in all forms (including YouTube and Netflix) constitutes 58.6% of peak Internet traffic in North America. In addition to the soaring demand, the heterogeneous and fluctuating network condition, due to different connection types (e.g., WiFi, wired LAN, and cellular), and diverse hardware specifications on end-user devices challenge multimedia streaming services to be more adaptive. Though there are solutions, such as Dynamic Adaptive Streaming over HTTP (DASH) and Apple's HTTP Live Streaming (HLS), to meet the increasing demand and to make multimedia streaming services more adaptive, none of them fully utilizes all available network resources to deliver the video in the best possible quality. For example, even if the available bandwidth from a service provider to an end-user device is 400 Kbps, sufficient to serve a video better than the standard definition quality (at 192 Kpbs bitrate), only standard definition video will be delivered since there is no intermediate quality level between standard definition and high definition (at 2 Mbps bitrate). It is challenging to provide a continuous video quality selection scheme since transcoding (for each quality level) is a time consuming and CPU intensive process. It is also challenging to select the appropriate quality level subject to the dynamic network condition.

各种形式的多媒体流媒体（包括YouTube和Netflix）占北美互联网峰值流量的58.6%。除了飙升的需求之外，由于不同的连接类型（例如，WiFi、有线LAN和蜂窝）以及终端用户设备上的各种硬件规范对多媒体流服务提出了更高的自适应性挑战。虽然有一些解决方案，如HTTP动态自适应流媒体（DASH）和Apple的HTTP实时流媒体（HLS），以满足不断增长的需求，并使多媒体流媒体服务更具适应性，但它们都没有充分利用所有可用的网络资源来提供最佳质量的视频。例如，即使从服务提供商到终端用户设备的可用带宽是400 Kbps，足以提供比标准清晰度质量更好的视频（在192 Kpbs比特率下），也将仅传送标准清晰度视频，因为在标准清晰度和高清晰度之间没有中间质量水平（在2 Mbps比特率下）。提供连续的视频质量选择方案是具有挑战性的，因为转码（对于每个质量等级）是耗时且CPU密集的过程。根据动态网络条件选择适当的质量水平也具有挑战性。