课题基金 / 基金详情

CAREER: Improving Mobile Video Delivery for Emerging Contents and Networks

CAREER: Improving Mobile Video Delivery for Emerging Contents and Networks
职业:改进新兴内容和网络的移动视频传输
批准号:
1750890
负责人:
Feng Qian
金额:
$55.66万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-05-01 至 2019-04-30

项目摘要

项目成果

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中文摘要
翻译
在移动的设备上无线地流式传输视频是越来越重要的应用。该项目的目标是为新内容类型和新兴网络的移动的视频交付带来创新。具体而言,该项目研究了三个方面:(1)360度沉浸式视频交付,(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。预计这些将成为下一代视频流服务的关键组成部分。 首先,360度视频为用户提供了独特的全景观看体验;然而,与常规视频相比,360度视频内容交付更具挑战性。第二,多个网络接口已经成为现成的移动的设备上的标准,但它们的潜力远未被充分利用。第三,毫米波是将被集成到5G无线网络中的关键技术;但将视频流媒体适配到毫米波在很大程度上仍然是一个未知的领域。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。该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方面的新技术趋势的知识,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方向。(1)对于360度视频流,基于视野(FoV)引导流的概念,该项目使用大数据分析来促进准确的头部运动预测,这是FoV引导流的关键先决条件。它还使用了一个速率自适应方案,具有“增量编码”设计,允许增量升级获取的块的质量。当面对头部运动的随机性时,这大大提高了适应性。(2)对于多路径流,该项目使用多个网络接口同时用于流视频。该网络框架支持视频速率自适应,并允许用户灵活配置每条路径的成本。该框架还支持通过战略数据包调度的多路径延迟敏感的实时流。(3)毫米波链路具有大容量和间歇可用性的独特特性。该项目首先为毫米波链路设计了一个传输层。然后,它提出了几种针对mmWave的视频流策略,例如战略性地将mmWave和传统全向无线电相结合。 对于上述研究方向,该项目将开发算法、模型和系统,并以真实的实施和评估为后盾。该奖项反映了NSF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。
英文摘要
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.
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会议论文
Conference: ACM SIGCOMM 2023 Travel Grant
Collaborative Research: CNS Core: Medium: Innovating Volumetric Video Streaming with Motion Forecasting, Intelligent Upsampling, and QoE Modeling
  • 批准号:
    2409008
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $40.0万
  • 财政年份:
    2023
  • 负责人:
    Feng Qian
  • 依托单位:
Collaborative Research: SaTC: CORE: Medium: Audacity of Exploration: Toward Automated Discovery of Security Flaws in Networked Systems through Intelligent Documentation Analysis
  • 批准号:
    2409269
  • 项目类别:
    Standard Grant
  • 资助金额:
    $30.0万
  • 财政年份:
    2023
  • 负责人:
    Feng Qian
  • 依托单位:
CPS: Medium: Collaborative Research: Transforming Connected and Automated Transportation with Smart Networking, Cooperative Sensing, and Edge Computing
  • 批准号:
    2409271
  • 项目类别:
    Standard Grant
  • 资助金额:
    $25.98万
  • 财政年份:
    2023
  • 负责人:
    Feng Qian
  • 依托单位:
国内基金
海外基金
Improving modelling of compact binary evolution.
  • 批准号:
    10903001
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    20.0万元
  • 批准年份:
    2009
  • 负责人:
    史蒂芬
  • 依托单位: