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CI-SUSTAIN: Collaborative Research: Sustaining Successful Smartphone Testbeds to Enable Diverse Mobile Experiments

CI-SUSTAIN: Collaborative Research: Sustaining Successful Smartphone Testbeds to Enable Diverse Mobile Experiments
CI-SUSTAIN:协作研究:维持成功的智能手机测试平台以实现多样化的移动实验
批准号:
1629763
负责人:
Zhuoqing Mao
金额:
$35.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-07-15 至 2021-06-30

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中文摘要
翻译
由于智能手机等移动和无线设备的计算和网络功能,它们正在改变我们生活的许多方面。随着基于物联网(IoT)的传感和驱动支持的发展,无线设备也在先进制造、交通运输和个性化健康等各个行业领域引入了范式转变。尽管有这样的承诺,但由于对现实软件和硬件平台以及用户行为的有限访问,对移动计算科学的大规模创新进行评估仍然相当困难。该奖项旨在支持和维持一个已经成功的名为MobiLab的全球规模现场实验室,以进一步实现长期的多样化移动实验。拟议的工作将有助于加强本科生密集实验的入门课程以及研究生水平的课程,使学生接触移动计算的各个方面。由此产生的基础设施将通过提供来自实际用例、软件构件和基于数据的结果的移动系统数据的丰富存储库,对研究社区和行业产生持久的影响。MobiLab将缓解移动计算和物联网领域陡峭的学习曲线,并在该领域吸引更多研究人员。MobiLab已被设想为著名的行星级网络试验床PlanetLab的移动计算类比,以支持基于智能手机的全球规模的移动计算科学实验。鉴于许多支持移动实验的MobiLab开源工具已经以众包应用程序的形式或作为特定操作环境中采用的定制工具得到了广泛部署,这项工作的重点是开发几个关键的软件基础设施改进,以实现实验基础设施的长期可持续性。特别是,该项目研究了如何使用新的可编程的上下文触发测量机制来补充主动和被动测量支持,该机制有助于平衡测量的开销和捕获的数据的准确性。基础设施的另一个增强是设计了基于将开发的允许在未经修改的设备和应用上测量用户体验质量的模型来准确衡量用户体验质量(QOE)的指标。基于QOE的测量支持与其他MobiLab工具集成,并通过应用程序市场大规模部署。最后,该项目还侧重于社区发展、公司赞助以及与其他组织和活动合作等方面的三项主要可持续性活动。
英文摘要
Mobile and wireless devices such as smartphones are transforming many aspects of our lives because of their computational and network capabilities. With the development of Internet of Things (IoT) based sensing and actuation support, wireless devices are also introducing a paradigm shift in various industry sectors such as advanced manufacturing, transportation, and personalized health. Despite this promise, it is still rather difficult to evaluate innovations in mobile computing science at scale due to limited access to realistic software and hardware platforms as well as user behavior. This award aims to support and sustain an already successful global-scale live laboratory known as MobiLab to further enable diverse mobile experiments in the long term. The proposed work will help augment both undergraduate lab-intensive introductory courses as well as graduate-level courses that expose students to various aspects in mobile computing. The resulting infrastructure will have a lasting impact on both the research community as well as industry by providing a rich repository of mobile system data from realistic use cases, software artifacts, and results based on the data. MobiLab will lighten the steep learning curve in mobile computing and IoT, as well as engage more researchers in this field.MobiLab has been conceived as a mobile computing analogue to the well-known planetary-scale networking testbed, PlanetLab, to support global-scale smartphone-based mobile computing science experimentation. Given many of the MobiLab open-source tools to support mobile experiments have already been widely deployed either in the form of crowd-sourced applications or as customized tools adopted in specific operational environment, this work focuses on developing several key software infrastructure improvements to enable long-term sustainability of the experimentation infrastructure. In particular, the project investigates how to complement the active and passive measurement support with a new programmable context-triggered measurement mechanism that helps balance the overhead of the measurement and the accuracy of the data captured. Another enhancement to the infrastructure is the design of metrics to accurately measure user quality of experience (QoE) based on models to be developed that allow QoE to be measured on unmodified devices and apps. QoE-based measurement support is integrated with the other MobiLab tools and deploy it at large scale via application marketplaces. Finally, this project also focuses on three main sustainability activities along the dimensions of community development, corporate sponsorship, as well as collaboration with other organizations and events.
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Collaborative Research: CISE: Large: Integrated Networking, Edge System and AI Support for Resilient and Safety-Critical Tele-Operations of Autonomous Vehicles
IMR: MT: xGTracker -- Mobile xG Performance Monitoring and Data Collection Platform to Enable Large-Scale Crowd-Sourced Measurement
CPS: Medium: Collaborative Research: Transforming Connected and Automated Transportation with Smart Networking, Cooperative Sensing, and Edge Computing
SBIR Phase I: Automated Safety/Security Compliance Verification and Enforcement for Autonomous Vehicle Software
  • 批准号:
    2015019
  • 项目类别:
    Standard Grant
  • 资助金额:
    $22.5万
  • 财政年份:
    2020
  • 负责人:
    Zhuoqing Mao
  • 依托单位:
海外基金