CAREER: A Data-Driven Uncertainty-Guided Architecture for Energy Management in Sensor Systems

职业生涯：用于传感器系统中的能量管理的数据驱动的不确定性引导架构

• 批准号: 1254192
• 负责人: Alberto Cerpa
• 金额: $ 53.95万
• 依托单位: University of California - Merced
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-02-01 至 2018-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1254192&HistoricalAwards=false
• 关键词: CAREER; Data; Driven; Uncertainty; Guided

The dramatic growth of wireless sensor networks (WSNs) in the last few years has seen the emergence of a variety of applications and pilot deployments that span scientific, engineering, medical and otherdisciplines. This project addresses an important research problem in sensor networks: energy management. By using hierarchical WSNs with different resources at different proxy and sensor tiers, as well as novel machine learning methods, we plan to develop DURACEM, a data-driven uncertainty-guided architecture that addresses energy efficiency across many sensor network services in a unified manner. Our architecture is built around (a) prediction models of phenomena, energy usage, and communication and the uncertainty in these models, (b) a slew of services that can exploit the uncertainty measures to save energy and(c) an overall energy optimization framework that combines the different models and services at both the proxy and sensor tiers.DURACEM has the potential for broad social impact. Our proposed research will provide fundamental services and tools to build next generation hierarchical sensor networks. DURACEM will provide a suite of efficientprediction models, as well as a variety of energy-optimized services built over these models. Our source code for our tools, libraries and prototypes will be made available to other researchers via an open-source software license. The project also focuses on building an inter-disciplinary teaching lab that can spur adoption of sensor networks by educating students across engineering and sciences. The project includes the development of a comprehensive curriculum that provides graduate and undergraduate students with core systems and analytical skills in sensor networks. The DURACEM project will enhance the research experiences of minority groups at University of California, Merced (UCM), which is one of only few research universities in the nation with a Hispanic student population greater than 40% and it is considered a Hispanic Serving Institution. The project includes an outreach undergraduate component specifically targeted to the minoritystudents.

无线传感器网络（WSNs）在过去的几年里迅速发展，出现了各种各样的应用和试点部署，跨越了科学、工程、医学和其他学科。该项目解决了传感器网络中的一个重要研究问题：能量管理。通过在不同的代理和传感器层使用具有不同资源的分层无线传感器网络，以及新颖的机器学习方法，我们计划开发DURACEM，这是一种数据驱动的不确定性指导架构，以统一的方式解决许多传感器网络服务的能源效率问题。我们的架构是围绕（a）现象、能源使用和通信的预测模型以及这些模型中的不确定性构建的，（B）一系列可以利用不确定性措施来节省能源的服务，以及（c）一个整体的能源优化框架，该框架结合了代理和传感器层的不同模型和服务。DURACEM具有广泛的社会影响潜力。我们提出的研究将提供基本的服务和工具，以建立下一代分层传感器网络。DURACEM将提供一套高效的预测模型，以及基于这些模型的各种能源优化服务。我们的工具、库和原型的源代码将通过开源软件许可证提供给其他研究人员。该项目还专注于建立一个跨学科的教学实验室，通过教育工程和科学领域的学生来促进传感器网络的采用。该项目包括开发一个综合课程，为研究生和本科生提供传感器网络的核心系统和分析技能。该DURACEM项目将提高少数群体的研究经验，在加州，默塞德（UCM），这是在全国仅有的几所研究型大学之一，西班牙裔学生人数超过40%，它被认为是一个西班牙裔服务机构。该项目包括一个专门针对少数民族学生的外联本科部分。