CNS Core: Small: A Unified Approach to Internet Performance Measurement

CNS 核心：小型：互联网性能测量的统一方法

• 批准号: 2133452
• 负责人: Ka Pui Mok
• 金额: $ 49.5万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-12-15 至 2024-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2133452&HistoricalAwards=false
• 关键词: CNS; Core; Small; Unified; Approach

Telecommuting, distance learning, and virtual gatherings have significantly increased during the COVID-19 pandemic. Poor Quality of Experience (QoE) of underlying networked software, such as video conferencing tools, degrades the usability of remote presence applications and thus impairs the effectiveness of distance communication and learning. However, current network performance measurement capabilities cannot systematically capture subjective aspects of QoE, hindering scientific study of this issue.The goal of this project is to develop and evaluate a fundamentally new approach to Internet performance measurement by conducting subjective assessments to measure the QoE of video streaming and conferencing applications in the wild and correlate these QoE measurements with Internet performance. Specifically, this research will 1) develop a unified assessment platform to crowdsource novel experiments for measuring the QoE of video streaming and video conferencing; 2) leverage gamification techniques to incentivize subject participation and improve overall efficiency of the experimental effort; and 3) combine analyses of QoE assessment data with external network topology and performance measurements to diagnose QoE degradations induced by congestion events on interconnections and last-mile access links.This research will advance the field's capabilities to diagnose performance degradation of essential tools for remote learning and telecommuting in the United States. In the process, this project will mentor a diverse set of undergraduate/high school students, who will learn about real-world Internet measurement through participating in platform development.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.

在COVID-19大流行期间，远程通信，远程学习和虚拟聚会显着增加。诸如视频会议工具之类的基础网络软件的经验质量（QOE）降低了远程存在应用程序的可用性，从而损害了距离沟通和学习的有效性。 但是，当前的网络性能测量能力无法系统地捕获QoE的主观方面，阻碍了对此问题的科学研究。该项目的目的是通过进行主观评估来开发和评估一种从根本上进行互联网性能测量的新方法，以测量主观评估，以测量视频流的Qoe，并在野外进行视频流媒体应用程序，并与Internet cormions corral in Internet cormions corral corters corral corters cornecters contecters contecters contecters contection contrence。具体而言，这项研究将1）开发一个统一的评估平台，以众包新颖的实验，以测量视频流和视频会议的Qoe； 2）利用游戏化技术激励受试者的参与并提高实验努力的总体效率； 3）将QoE评估数据的分析与外部网络拓扑结合在一起，以诊断由交通拥堵事件引起的有关互连和最后一英里访问链路引起的QOE降解。这项研究将提高该领域的能力，以诊断该领域的绩效降级，以降级远程学习和远程学习和远程远程通讯的工具。 在此过程中，该项目将指导各种各样的本科/高中学生，他们将通过参与平台开发来了解现实世界中的互联网测量。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛的审查标准通过评估来进行评估的。