CAREER: Information-Aware Wireless Sensor Networks

职业：信息感知无线传感器网络

• 批准号: 0747363
• 负责人: Jean-Francois Chamberland
• 金额: $ 21.27万
• 依托单位: Texas A&M Engineering Experiment Station
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-01-01 至 2013-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0747363&HistoricalAwards=false
• 关键词: CAREER; Information; Aware; Wireless; Sensor

The emergence of miniature sensors with low-power wireless transceivers holds the promise of a new phase in the wireless revolution. Sensor networks have the ability to collect and transmit environmental data through the ubiquitous deployment of inexpensive wireless devices. This project addresses some of the most important current issues in wireless sensor networks. It seeks to develop an integrated framework for the combined analysis of sampling, distributed signal processing, and data dissemination in the context of delay-sensitive applications. Understanding the interplay between data gathering, resource allocation, and overall performance in wireless sensor networks necessitates a new mindset and a global system perspective. To this end, this project introduces a methodology for the analysis and the design of delay-sensitive sensor networks based, in part, on large deviations, queueing theory, and network calculus.Systems composed of hundreds or thousands of wireless sensors make the dense sampling of stochastic environments possible. The amount of data generated by such large numbers of devices is equally vast, and it creates new challenges for the processing and transmission of observed data. Novel methods of analysis are required to provide insight into the efficient design and conception of sensor networks. As part of this research project, techniques from large-deviation theory and asymptotic analysis will be extended and applied to distributed sensing. These techniques will be used to: derive guidelines for node placement in correlated fields, propose novel paradigms for communication over multihop sensor networks with statistical delay guarantees, develop access control strategies that utilize the information content of individual packets, and characterize the interplay between in-network signal processing and traffic profiles for event-driven applications.

具有低功耗无线收发器的微型传感器的出现为无线革命的新阶段带来了希望。 传感器网络具有通过无处不在的廉价无线设备的部署来收集和传输环境数据的能力。 这个项目解决了无线传感器网络中一些最重要的当前问题。 它旨在开发一个综合的框架，在延迟敏感的应用程序的背景下，采样，分布式信号处理和数据传播的综合分析。 了解无线传感器网络中数据收集、资源分配和整体性能之间的相互作用需要一种新的思维方式和全局系统视角。 为此，该项目介绍了一种方法，用于分析和设计的延迟敏感的传感器网络的基础上，部分大偏差，嵌入式理论，和网络calculation.Systems组成的数百或数千个无线传感器的随机环境的密集采样成为可能。 如此大量的设备产生的数据量同样巨大，这为观测数据的处理和传输带来了新的挑战。 新的分析方法，需要提供洞察传感器网络的有效设计和概念。 作为这个研究项目的一部分，大偏差理论和渐近分析的技术将被扩展并应用于分布式传感。 这些技术将被用来：推导出相关领域的节点布局的指导方针，提出新的范例，多跳传感器网络的通信与统计延迟保证，开发访问控制策略，利用个人数据包的信息内容，并表征网络信号处理和流量配置文件之间的相互作用事件驱动的应用程序。