Collaborative Research: IRES Track I: Wireless Federated Fog Computing for Remote Industry 4.0 Applications

合作研究：IRES Track I：用于远程工业 4.0 应用的无线联合雾计算

• 批准号: 2417064
• 负责人: Mohsen Amini Salehi
• 金额: $ 15.83万
• 依托单位: University of North Texas
• 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 2026-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2417064&HistoricalAwards=false
• 关键词: Collaborative; Research; IRES; Track; Wireless; Collaborative; Research; IRES; Track; Wireless

The overarching goal of this project is to create unique training and research opportunities for U.S. students through an international research collaboration with the IMDEA Networks Institute, a world-class research institution in Madrid, Spain. The project's research plan engages students in an interdisciplinary cutting-edge research at the intersections of wireless networking, edge/fog computing, and machine learning (ML). The proposed project will enable the U.S. team to build a wireless federated fog (WFF) platform that is robust and scalable in accommodating different types of Industry 4.0 applications in remote areas where there is shortage of access to cloud resources, i.e., it offers the illusion of accessing infinite cloud-like resources. To this end, a cross-layer communications-computing framework will be developed during the project years with novel solutions for: live container migration; deep learning (DL) partitioning and approximation; and serverless workflow development and deployment. The anticipated outcomes of the project will be the following artifacts: (1) Methods for seamless migration of containerized services across autonomous fog systems; (2) Methods for latency-aware partitioning of micro-service workflows across WFF; (3) A serverless framework for declarative and reliable workflow development (workflow as a code) on WFF; (4) Methods for robust and latency-aware distributed DL inference atop uncertain WFF; (5) Methods using approximate inference for on-premises execution of sensitive DL services. This project will provide a unique opportunity for U.S. students to gain international cross-disciplinary experience at a world-class research institute. Every year, graduate and undergraduate students will be selected via a well-defined procedure to visit the Global Computing research group at IMDEA for 8 summer weeks. The project will expose the students to both analytical and practical challenges of the communication-computing systems at a reputed research institution, and train them to become a globally-engaged and cultured workforce with world-class skills. The project outcomes will be evaluated annually by a professional evaluator, and enhanced during the subsequent years.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.

该项目的总体目标是通过与西班牙马德里的世界一流研究机构IMDEA Networks Institute的国际研究合作为美国学生创造独特的培训和研究机会。该项目的研究计划使学生在无线网络，边缘/雾计算和机器学习（ML）的交叉点上参与跨学科的尖端研究。拟议的项目将使美国团队能够构建一个无线联合雾（WFF）平台，该平台在容纳不同类型的行业4.0应用程序中，在偏远地区的不同类型的行业4.0应用程序中，由于无法访问云资源，即，它提供了访问Infinite云型资源的幻觉。为此，将在项目几年中使用新颖的解决方案：实时容器迁移；深度学习（DL）分区和近似；以及无服务器的工作流程开发和部署。该项目的预期结果将是以下工件：（1）在自主雾系统之间进行集装服务的无缝迁移的方法； （2）跨WFF的微服务工作流的延迟感知的方法； （3）WFF上的声明和可靠工作流程开发（工作流程）的无服务器框架； （4）在不确定的WFF上进行鲁棒和潜伏期分布式DL推断的方法； （5）使用敏感DL服务执行本地执行的方法。该项目将为美国学生提供一个独特的机会，可以在世界一流的研究所获得国际跨学科经验。每年，研究生和本科生都将通过定义明确的程序选择，以访问IMDEA的全球计算研究小组，共8个夏季。该项目将使学生在知名的研究机构中遇到交流计算系统的分析和实践挑战，并训练他们成为具有世界一流技能的全球参与和文化的劳动力。该项目的结果将每年由专业评估者进行评估，并在随后的几年中得到增强。该奖项反映了NSF的法定任务，并认为使用基金会的知识分子优点和更广泛的影响评估标准，认为值得通过评估来获得支持。