CNS Core: Small: Expedient Computing: A Framework for Energy-Efficient and Timely Computing at the Edge

CNS 核心：小型：便捷计算：边缘节能和及时计算的框架

• 批准号: 2219180
• 负责人: Suresh Subramaniam
• 金额: $ 58.47万
• 依托单位: George Washington University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-10-01 至 2025-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2219180&HistoricalAwards=false
• 关键词: CNS; Core; Small; Expedient; Computing

Emerging and future cyber-physical system applications demand timely processing at the network edge of large volumes of fresh data from sensor nodes, which may have limited processing ability and energy budgets. The sheer variety of envisioned applications and their requirements call for new performance metrics and strategies for balancing freshness of information, timeliness and accuracy of results, and the energy consumed in producing those results. This project proposes and develops a new holistic framework called Expedient Computing, in which results are produced as quickly as needed, with as much precision/accuracy as needed, using information that is as fresh as needed. The specific research objectives of the project include: (i) characterizing fundamental tradeoffs in expedient computing, (ii) exploration of emerging hardware designs in edge servers for expedient computing, (iii) developing an integrated optimization framework for expedient computing, and (iv) demonstrating expedient computing principles. This cross-disciplinary project will draw upon expertise in hardware architecture, network optimization and performance analysis, algorithms, and fundamental limits.Due to the inexorable desire to make the world smarter, millions upon millions of sensors are being deployed worldwide. The successful realization of envisioned applications such as connected autonomous vehicles and remote robotic surgery will critically depend on the timely extraction of actionable intelligence from sensor data. This project lays the groundwork for doing so while balancing the limitations in energy and processing capabilities and exploring the tradeoffs between them. The outcomes of this research project can offer significant performance improvements by maximizing precision, timeliness, energy efficiency and their tradeoffs in broad application domains such as edge computing, mobile sensing, and Internet of Things, and catalyze the industry toward seeking energy-efficient and timely computing technologies at the edge. Project results will be disseminated via research publications, organizing workshops and tutorials in top conferences, and through training students in this crucial cross-cutting field.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.

新兴和未来的网络物理系统应用需要及时处理来自传感器节点的大量新数据的网络边缘，这些数据可能具有有限的处理能力和能源预算。各种各样的设想应用程序及其要求呼吁采用新的绩效指标和策略，以平衡信息的新鲜度，及时性和结果的准确性以及产生这些结果的能量。该项目提出并开发了一个称为权宜计算的新的整体框架，其中最快地产生了结果，并使用根据需要的新鲜信息来精确/准确。该项目的具体研究目标包括：（i）表征方便计算中的基本权衡，（ii）探索用于方便计算的边缘服务器中新兴硬件设计的探索，（iii）开发用于方便计算的集成优化框架，以及（iv）证明了权宜计算原则。这个跨学科的项目将借鉴硬件体系结构，网络优化和性能分析，算法和基本限制的专业知识。要使世界更加智能的渴望，全世界正在部署数百万传感器的愿望。成功地实现了诸如连接的自动驾驶汽车和远程机器人手术之类的设想应用程序将严重取决于及时从传感器数据中提取可起作用的智能。该项目为这样做奠定了基础，同时平衡了能源和处理能力的限制以及探索它们之间的权衡。该研究项目的结果可以通过最大程度地提高精确度，及时性，能源效率及其在广泛的应用领域（例如边缘计算，移动传感和物联网）中的权衡来提供重大的绩效提高，并促进该行业寻求Edge的能源效率和及时的计算技术。项目结果将通过研究出版物，在顶级会议中组织研讨会和教程来传播，并通过培训这个关键的跨切割领域的培训学生。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影响的审查标准通过评估来获得支持的。

项目成果

Performance Modeling of Scheduling Algorithms in a Multi-Source Status Update System

多源状态更新系统中调度算法的性能建模

• DOI: 10.1109/isit50566.2022.9834272
• 发表时间: 2022
• 期刊: International Symposium on Information Theory
• 作者: Zou, Peng;Zhang, Jin;Subramaniam, Suresh
• 通讯作者: Subramaniam, Suresh

Optimizing the Age of Information with Segmentation and Predictive Scheduling

• DOI: 10.1109/wcnc55385.2023.10118997
• 发表时间: 2023-03
• 期刊: 2023 IEEE Wireless Communications and Networking Conference (WCNC)
• 作者: Jin Zhang;P. Zou;Suresh Subramaniam

Joint UAV Trajectory Planning, DAG Task Scheduling, and Service Function Deployment Based on DRL in UAV-Empowered Edge Computing

• DOI: 10.1109/jiot.2023.3257291
• 发表时间: 2023-07
• 期刊: IEEE Internet of Things Journal
• 影响因子: 10.6
• 作者: Xianglin Wei;Lingfeng Cai;Nan Wei;P. Zou;Jin Zhang;S. Subramaniam