Learning-based Energy Management for Cyber-Physical Systems

基于学习的网络物理系统能源管理

• 批准号: RGPIN-2017-06001
• 负责人: Lin, Man
• 金额: $ 1.46万
• 依托单位: St. Francis Xavier University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=634442
• 关键词: Learning; based; Energy; Management; Cyber

With the advance of engineering and networking technology, many embedded devices are now connected into a network or with the Internet, and are emerging into cyber-physical systems. A cyber-physical system can be found in various applications for control and monitoring, such as automotive, aerospace, health care, transportation, building and process control, and entertainment. Unlike desktop systems, many cyber-physical systems operate with batteries that have limited energy supplies. Thus, energy efficiency is one of the inherent requirements of cyber-physical systems, as low-energy consumption yields better battery life, which is especially important for applications involving implanted medical devices. With more and more cyber-physical systems around us nowadays, low-energy consumption problem of cyber-physical systems becomes more critical.

随着工程和网络技术的进步，许多嵌入式设备现在连接到网络或与互联网，并正在成为网络物理系统。信息物理系统可以在各种控制和监控应用中找到，例如汽车，航空航天，医疗保健，运输，建筑和过程控制以及娱乐。与桌面系统不同，许多网络物理系统使用能量供应有限的电池运行。因此，能源效率是网络物理系统的内在要求之一，因为低能耗可以产生更长的电池寿命，这对于涉及植入式医疗器械的应用尤其重要。随着越来越多的信息物理系统出现在我们身边，信息物理系统的低能耗问题变得越来越重要。