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

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IMDEA网络研究所（位于西班牙马德里的世界级研究机构）的国际研究合作，为美国学生创造独特的培训和研究机会。该项目的研究计划让学生参与无线网络，边缘/雾计算和机器学习（ML）交叉点的跨学科前沿研究。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，该平台具有强大的可扩展性，可在缺乏云资源访问的偏远地区适应不同类型的工业4.0应用，即，它提供了访问无限云资源的错觉。为此，将在项目期间开发跨层通信计算框架，并提供新的解决方案：实时容器迁移;深度学习（DL）分区和近似;以及无服务器工作流开发和部署。该项目的预期成果将是以下工件：（1）跨自治雾系统无缝迁移容器化服务的方法;（2）跨WFF对微服务工作流进行延迟感知分区的方法;（3）用于声明性和可靠工作流开发的无服务器框架（工作流作为代码）;（4）在不确定WFF上进行鲁棒的和延迟感知的分布式DL推理的方法;（5）使用近似推理进行敏感DL服务的本地执行的方法。该项目将为美国学生提供一个独特的机会，在世界一流的研究机构获得国际跨学科的经验。每年，研究生和本科生将通过一个明确的程序被选中访问IMDEA的全球计算研究小组8个夏季周。该项目将使学生在一个著名的研究机构中接触到通信计算系统的分析和实践挑战，并培养他们成为具有世界一流技能的全球参与和培养的劳动力。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估来支持。