CAREER: Improving Mobile Video Delivery for Emerging Contents and Networks

在移动设备上无线流媒体视频是一个越来越重要的应用。该项目的目标是为新内容类型和新兴网络带来移动视频传输的创新。具体而言，该项目研究了三个方面：(1)360度沉浸式视频传输，(2)多个网络路径（多路径）上的视频流，以及(3)毫米波（mmWave）链路上的视频流。这些预计将成为下一代视频流媒体服务的关键组成部分。首先，360度视频为用户提供独特的全景观看体验；然而，与普通视频相比，360度视频内容传输更具挑战性。第二，多网络接口已成为现成移动设备的标准，但其潜力远未得到充分利用。第三，毫米波是一项关键技术，将集成到5G无线网络中；但将视频流应用于毫米波在很大程度上仍是一个未知领域。所提出的解决方案将通过增强用户体验和减少下一代沉浸式视频服务的资源消耗来造福社会。这项研究还将与一项教育计划相结合，该计划旨在为计算机科学专业的学生提供网络和系统新技术趋势的知识，并激发公众对科学、技术、工程和数学的兴趣。该项目包括三个相互关联的研究重点。(1)对于360度视讯流，基于视场引导流的概念，利用大数据分析实现准确的头部运动预测，这是视场引导流的关键前提。它还使用了一种带有“增量编码”设计的速率自适应方案，允许获取的块的质量逐步升级。这大大提高了面对随机头部运动时的适应性。(2)多路径流媒体，本项目使用多个网络接口同时进行视频流媒体。网络框架支持视频速率自适应，允许用户灵活配置每条路径的成本。该框架还通过策略分组调度支持多路径上延迟敏感的实时流。(3)毫米波链路具有大容量和间歇性可用性的独特特点。该项目首先为毫米波链路设计一个传输层。然后，它提出了几种针对毫米波的视频流策略，例如战略性地将毫米波与传统的全向无线电相结合。对于上述研究重点，该项目将开发算法、模型和系统，并以实际实施和评估为后盾。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Streaming videos wirelessly on mobile devices is an increasingly important application. The objective of this project is to bring innovations to mobile video delivery for new content types and over emerging networks. Specifically, the project investigates three aspects: (1) 360-degree immersive video delivery, (2) video streaming over multiple network paths (multipath), and (3) video streaming over millimeter-wave (mmWave) links. These are expected to be the key building blocks of next-generation video streaming services. First, 360-degree videos provide users with unique panoramic viewing experience; however, 360-degree video content delivery is much more challenging compared to regular videos. Second, multiple network interfaces have become a norm on off-the-shelf mobile devices but their potential is far from being fully exploited. Third, mmWave is a key technology that will be integrated into 5G wireless networks; but adapting video streaming to mmWave largely remains an uncharted territory. The proposed solutions will benefit the society by enhancing the user experience and reducing the resource consumption for next-generation immersive video services. The research will also be integrated with an education plan that seeks to prepare computer science students with the knowledge of new technological trends in networking and systems, and stimulate the general public interest in Science, Technology, Engineering, and Mathematics.This project includes three inter-connected research thrusts. (1) For 360 video streaming, based on the concept of field-of-view (FoV) guided streaming, the project uses big data analytics to facilitate accurate head movement prediction, a key prerequisite for FoV-guided streaming. It also uses a rate adaptation scheme with a "delta encoding" design allowing the quality of a fetched chunk to be incrementally upgraded. This substantially improves adaptability when facing randomness in head movements. (2) For multipath streaming, the project uses multiple network interfaces to be used simultaneously for streaming videos. The network framework supports video rate adaptation and allows users to flexibly configure each path's cost. The framework also supports delay-sensitive live streaming over multipath through strategic packet scheduling. (3) mmWave links bear unique characteristics of massive capacity and intermittent availability. The project first designs a transport layer for mmWave links. It then proposes several video streaming strategies tailored to mmWave, such as strategically combining mmWave and legacy omni-directional radios. For the above research thrusts, the project will develop algorithms, models, and systems, backed up by real implementation and evaluation.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.