REU Site: Intelligent Edge Computing Systems

REU 站点:智能边缘计算系统

基本信息

  • 批准号:
    2348711
  • 负责人:
  • 金额:
    $ 33.36万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2024
  • 资助国家:
    美国
  • 起止时间:
    2024-02-01 至 2027-01-31
  • 项目状态:
    未结题

项目摘要

This project establishes a Research Experiences for Undergraduates (REU) site at Mississippi State University. Computing in homes, workspaces, farms, factories, e-commerce, vehicles, healthcare, etc., is pervasive, and human expectations of making decisions quickly, robustly, and effectively have yet to know any bounds. To cater to such a profound need, edge computing is tapped as a practical solution as the user experience improves due to the increased focus on the domain (vehicles, factories, healthcare, etc.). The increased focus mandates domain-specific solutions that make intelligent decisions that are timely and accurate. The Intelligent Edge Computing Systems (iEDGE) REU site aims to expose undergraduate students to various domain-specific edge computing systems. Eight undergraduate students will work each year for ten weeks on iEDGE projects. The environment provided at the REU site will focus on peer mentoring, rapid integration of students in existing projects, and a robust support system that will include knowledge transference from faculty members, postdoctoral researchers, and doctoral, master, and undergraduate research students already working on projects related to edge computing at Mississippi State University. While the iEDGE REU site projects may have different emphases per domain, all projects will research and develop solutions for integrated edge platforms comprising computational, communications, and sensory elements coordinating to control and monitor various processes. The REU site students will primarily be recruited from Minority Serving Institutions (MSIs) and provided with a two-week baseline primer to enable them to conduct research successfully. The topics covered in the primer will include (but are not limited to) embedded systems, radio access networks, 5G communications, software-defined radios, Zigbee, federated machine learning, sensor processing, wave propagation, antennae design, operating systems, libraries, compilers, and distributed systems. The REU participants will also be exposed to topics on project management, collaborative research, team management, research ethics, equity, diversity, and inclusion, as well as several professional development programs. Through the unique mentoring program immersed in peer mentoring at all levels, the participants will gain a robust research experience that will prepare them well to work at the intersection of computing and communication to develop domain-specific integrated platform solutions.This project is jointly funded by the NSF CISE REU Program and the Established Program to Stimulate Competitive Research (EPSCoR).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.
该项目在密西西比州立大学建立了一个本科生研究经验(REU)网站。家庭、工作空间、农场、工厂、电子商务、车辆、医疗保健等领域的计算无处不在,人们对快速、有力和有效地做出决策的期望尚未确定任何界限。为了迎合这种深刻的需求,边缘计算被用作一种实用的解决方案,因为用户体验因对该领域(车辆、工厂、医疗保健等)的日益关注而得到改善。越来越多的关注要求特定领域的解决方案能够做出及时和准确的智能决策。智能边缘计算系统(IEDGE)REU网站旨在让本科生接触到各种特定于领域的边缘计算系统。8名本科生每年将在iEDGE项目上工作10周。REU网站提供的环境将侧重于同行指导,学生快速融入现有项目,以及强大的支持系统,其中将包括已在密西西比州立大学从事边缘计算相关项目的教职员工、博士后研究人员以及博士后、硕士和本科生的知识传授。虽然iEDGE REU现场项目可能在每个领域有不同的侧重点,但所有项目都将研究和开发集成边缘平台的解决方案,包括协调控制和监控各种过程的计算、通信和传感元素。REU网站的学生将主要从少数族裔服务机构(MSI)招募,并提供为期两周的基线入门读物,使他们能够成功地进行研究。入门读物涵盖的主题将包括(但不限于)嵌入式系统、无线电接入网络、5G通信、软件定义无线电、Zigbee、联合机器学习、传感器处理、波传播、天线设计、操作系统、库、编译器和分布式系统。REU的参与者还将接触到项目管理、合作研究、团队管理、研究道德、公平、多样性和包容性等主题,以及几个专业发展计划。通过沉浸在各级同行指导中的独特指导计划,参与者将获得强大的研究体验,这将为他们在计算和通信的交叉点上很好地工作,开发特定领域的集成平台解决方案做好准备。该项目由NSF Cise REU计划和既定的激励竞争研究计划(EPSCoR)联合资助。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。

项目成果

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Samee Khan其他文献

Samee Khan的其他文献

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{{ truncateString('Samee Khan', 18)}}的其他基金

FET: Medium: A Quantum Computing Based Approach to Undirected Generative Machine Learning Models
FET:中:基于量子计算的无向生成机器学习模型方法
  • 批准号:
    2211841
  • 财政年份:
    2022
  • 资助金额:
    $ 33.36万
  • 项目类别:
    Continuing Grant
Workshop on Quantum Computing, Information, Science, and Engineering
量子计算、信息、科学与工程研讨会
  • 批准号:
    2202377
  • 财政年份:
    2022
  • 资助金额:
    $ 33.36万
  • 项目类别:
    Standard Grant
Travel: NSF Student Travel Grant for 2022 IEEE Cloud Summit
旅行:2022 年 IEEE 云峰会 NSF 学生旅行补助金
  • 批准号:
    2243579
  • 财政年份:
    2022
  • 资助金额:
    $ 33.36万
  • 项目类别:
    Standard Grant
Collaborative Research: PPoSS: Planning: Software Stack for Scalable Heterogeneous NISQ Cluster
协作研究:PPoSS:规划:可扩展异构 NISQ 集群的软件堆栈
  • 批准号:
    2216898
  • 财政年份:
    2022
  • 资助金额:
    $ 33.36万
  • 项目类别:
    Standard Grant
Collaborative Research: CNS Core: Small: HARMONIA: New Methods for Colocating Multiple QoS-Sensitive Jobs
协作研究:CNS 核心:小型:HARMONIA:共置多个 QoS 敏感作业的新方法
  • 批准号:
    2124908
  • 财政年份:
    2021
  • 资助金额:
    $ 33.36万
  • 项目类别:
    Standard Grant
EAGER: From Theory to Practice of Elastic Interval Runtime Schedulers
EAGER:弹性间隔运行时调度器从理论到实践
  • 批准号:
    2135439
  • 财政年份:
    2021
  • 资助金额:
    $ 33.36万
  • 项目类别:
    Standard Grant

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