ITR/SI+IM (CISE):Distributed Data Compression and Dissemination for Wireless Sensor Networks

ITR/SI IM (CISE)：无线传感器网络的分布式数据压缩和传播

• 批准号: 0112801
• 负责人: David Neuhoff
• 金额: $ 39.94万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-09-01 至 2005-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0112801&HistoricalAwards=false
• 关键词: ITR; SI+IM; CISE; Distributed; Data

This project will develop new methods for the efficient dissemination of the data collected by wirelesssensor networks. With recent and projected advances in small, low cost microelectronic and micro-electromechanical sensors, it is easy to envision that a large array of sensors, distributed over anappropriate region, will be able to measure the spatial and temporal variations of important attributefield such as temperature, moisture, sound, light, gas concentrations, etc.. However, to realize thebenefits of such arrays, wireless communication networks must be devised that with low power encodeand disseminate the large amounts of data they generate. With this as the goal, the project willdevelop new methods of distributed data compression and data dissemination for dense sensor arrays,that is, for arrays whose sensors are so close that their measurements are highly correlated. One thesisof this project is that the correlations in such arrays can be exploited in order to make the networkoperate essentially as efficiently as a sparse sensor network, while having the additional advantages ofbeing resilient to sensor failures and permitting the attribute field to be measured adaptively or withhigher spatial resolution. Another thesis is that the data compression and dissemination issues forsuch networks are deeply intertwined. Accordingly, the project focuses on the joint design of such.For example, it seeks methodology for tailoring distributed data compression methods to partculardissemination strategies, and vice versa. In the process, it proposed to learn how the performance ofsensor networks depends on a variety of issues such as the number and placement of sensors.

该项目将开发新的方法，以有效传播由无线传感器网络收集的数据。随着小型，低成本微电子和微机电传感器的最新和预计的进展，很容易想象，分布在适当区域的大量传感器将能够测量重要属性领域的时空变化，如温度，湿度，声音，光，气体浓度等。然而，为了实现这种阵列的好处，无线通信网络必须设计成低功率编码和传播它们产生的大量数据。以此为目标，该项目将开发用于密集传感器阵列的分布式数据压缩和数据传播的新方法，即用于传感器如此接近以至于其测量结果高度相关的阵列。该项目的一个论点是，可以利用这些阵列中的相关性，以使网络基本上像稀疏传感器网络一样有效地运行，同时具有对传感器故障具有弹性的额外优势，并允许属性字段自适应地测量或具有更高的空间分辨率。另一个论点是，这种网络的数据压缩和传播问题是紧密交织在一起的。因此，本项目着重于此类的联合设计。例如，它寻求为特定的传播策略定制分布式数据压缩方法的方法，反之亦然。在此过程中，它提出要了解传感器网络的性能如何取决于传感器的数量和位置等各种问题。