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：用于最小化自组织传感器网络中功耗的勒贝格估计（提案编号 0427976）摘要 - 该传感器提案侧重于开发一种新型状态估计器（最佳观测器），可最大程度地减少无线传感器网络中使用的功耗要求实时反馈控制系统。在优化传感器网络协议以最大限度地降低功耗方面正在进行大量工作。注意，无线传感器设备中消耗的大部分功率与执行通信传输事件相关联。本研究旨在确定一种方法，使通信事件的发生最小化，并且每个消息的数据内容最小化，同时确保结果状态估计不超过指定的误差要求。这项研究的智力价值在于将工厂的连续时间和连续状态模型转换为非周期离散时间和非均匀离散状态系统。该研究将开发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时间自动机的方法。这项研究的更广泛影响为阿肯色大学无线传感器网络实验室奠定了基础。该实验室针对智能交通系统，预计在整个高速公路基础设施和机动车辆中引入特设传感器网络。在面向 K-12 学生的宣传活动中，该实验室明确展示了如何利用技术来提高安全性、减少拥堵和改善空气质量，从而提高年轻人对工程职业的认识。此外，研究结果将有助于开发先进的防撞和交通管制系统。