CPS: Small: Sensor Network Information Flow Dynamics

CPS：小型：传感器网络信息流动态

• 批准号: 0931957
• 负责人: Mehdi Khandani
• 金额: $ 29.85万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-10-01 至 2014-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0931957&HistoricalAwards=false
• 关键词: CPS; Small; Sensor; Network; Information

The objective of this research is to develop numerical techniques for solving partial differential equations (PDE) that govern information flow in dense wireless networks. Despite the analogy of information flow in these networks to physical phenomena such as thermodynamics and fluid mechanics, many physical and protocol imposed constraints make information flow PDEs unique and different from the observed PDEs in physical phenomena. The approach is to develop a systematic method where a unified framework is capable of optimizing a broad class of objective functions on the information flow in a network of a massive number of nodes. The objective function is defined depending on desired property of the geometric paths of information. This leads to PDEs whose form varies depending on the optimization objective. Finally, numerical techniques will be developed to solve the PDEs in a network setting and in a distributed manner. The intellectual merits of this project are: developing mathematical tools that address a broad range of design objectives in large scale wireless sensor networks under a unified framework; initiating a new field on numerical analysis of information flow in dense wireless networks; and developing design tools for networking problems such as transport capacity, routing, and load balancing.The broader impacts of this research are: helping the development of next generation wireless networks; encouraging involvement of undergraduate students and underrepresented groups, and incorporating the research results into graduate level courses. Additionally, the research is interdisciplinary, bringing together sensor networking, theoretical physics, partial differential equations, and numerical optimization.

本研究的目的是开发用于求解密集无线网络中控制信息流的偏微分方程（PDE）的数值技术。尽管这些网络中的信息流类似于热力学和流体力学等物理现象，但许多物理和协议强加的约束使得信息流偏微分方程与物理现象中观察到的偏微分方程是独特的和不同的。该方法是开发一种系统的方法，其中统一的框架能够在大量节点网络的信息流上优化广泛的目标函数。目标函数是根据信息的几何路径的期望性质来定义的。这导致偏微分方程的形式因优化目标而异。最后，将发展数值技术，以解决在网络设置和分布式方式的偏微分方程。该项目的智力优点是：开发数学工具，在统一框架下解决大规模无线传感器网络中的广泛设计目标；开创了密集无线网络中信息流数值分析的新领域；并开发设计工具来解决网络问题，如传输容量、路由和负载平衡。这项研究的更广泛的影响是：帮助下一代无线网络的发展；鼓励本科生和弱势群体的参与，并将研究成果纳入研究生水平的课程。此外，该研究是跨学科的，汇集了传感器网络，理论物理，偏微分方程和数值优化。