SII: Lebesgue Estimation for Minimizing Power Consumption in Ad Hoc Sensor Networks

SII：最小化自组传感器网络功耗的勒贝格估计

• 批准号: 0427976
• 负责人: Roy McCann
• 金额: $ 9.44万
• 依托单位: University of Arkansas
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-09-01 至 2008-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0427976&HistoricalAwards=false
• 关键词: SII; Lebesgue; Estimation; Minimizing; Power

SSI: Lebesgue Estimation for Minimizing Power Consumption in Ad Hoc Sensor Networks (Proposal No. 0427976)Abstract- This sensor proposal focuses on the development a new type of state-estimator (optimal observer) that minimizes the power requirements of wireless sensor networks employed in real-time feedback control systems. There is considerable ongoing work in optimizing sensor network protocols for minimizing power requirements. It is noted that most of the power consumed in a wireless sensor device is associated with executing a communication transmission event. This research seeks to determine a method whereby both the occurrence of communication events is minimized and the data content of each message is minimized while ensuring that the resulting state estimate does not exceed a specified error requirement. The intellectual merit of this research is in transforming a continuous-time and continuous-state model for the plant into a non-periodic discrete-time and non-uniform discrete-state system. The research will develop methods for analyzing and designing state estimators as stochastic timed automata within the framework of generalized semi-Markov processes. The broader impact of this research is setting the foundation for a wireless sensor network laboratory at the University of Arkansas. This laboratory is directed towards intelligent transportation systems in anticipation of the introduction of ad hoc sensor networks throughout highway infrastructure and motor vehicles. In outreach to K-12 students, the laboratory elevates the awareness of engineering careers to young people by showing explicitly how technology can be employed to increase safety, reduce congestion, and improve air quality. Additionally, the results will aid in the development of advanced collision avoidance and traffic regulation systems.

SSI：LEBESGUE估算，以最大程度地减少临时传感器网络中的功耗（提案号0427976）摘要 - 该传感器建议着重于开发一种新型的状态估计器（Optimal Observer）（最佳观察者），将无线传感器网络的功率要求最小化，以实时反馈控制系统中使用。在优化传感器网络协议以最大程度地减少功率要求方面，正在进行的许多工作。值得注意的是，无线传感器设备中消耗的大多数功率都与执行通信传输事件相关联。这项研究试图确定一种方法，通过将通信事件的出现最小化，并确保所得状态估计值不超过指定的错误要求，并将每个消息的数据内容最小化。这项研究的智力优点在于将植物的连续时间和连续状态模型转变为非周期离散时间和不均匀的离散状态系统。这项研究将开发用于在广义半马尔可夫过程框架内分析和设计状态估计器作为随机定时自动机的方法。这项研究的广泛影响是为阿肯色大学的无线传感器网络实验室奠定了基础。该实验室针对智能运输系统，期望在整个高速公路基础设施和机动车中引入临时传感器网络。在与K-12学生的宣传中，实验室通过明确显示如何采用技术来提高安全性，减少拥塞并提高空气质量，从而提高了对年轻人的工程职业的认识。此外，结果将有助于发展高级碰撞和交通调节系统。