CAREER: Data Management for Ad-Hoc Geosensor Networks

该项目探索地理传感器网络的数据管理方法，即部署在地理环境中的非常小的电池驱动传感器节点的大型集合，用于测量物理量（如温度或臭氧水平）的时空变化。这种地球传感器网络的一项重要任务是以一种节能的方式实时收集、分析和估计所观察的连续现象的信息，例如化工厂附近的有毒云。该项目的主要推力是传感器网络中空间数据分析技术与网络内数据查询执行的集成。该项目研究了新的算法，如增量，网络内克里格，重新定义了传统的，高度计算密集型的空间数据估计方法，用于在微小，能量和带宽受限的传感器节点之间进行分布式，协作和增量处理。这项工作包括根据观察到的现象对传感器设备的位置和传感特性进行建模，支持时空估计查询，以及关注复杂空间估计查询的网络内数据聚合算法。将高级数据查询接口与先进的空间分析方法相结合，将允许领域科学家在环境观测中有效地使用传感器网络。该项目对缅因大学空间数据库研究的本科生和研究生具有广泛的影响，同时也是当前传感材料、传感设备和传感领域的IGERT项目的关键组成部分。有关该项目的更多信息、出版物、仿真软件和实证研究可在该项目的网站上获得（http://www.spatial.maine.edu/~nittel/career/）。

This project explores data management methods for geosensor networks, i.e. large collections of very small, battery-driven sensor nodes deployed in the geographic environment that measure the temporal and spatial variations of physical quantities such as temperature or ozone levels. An important task of such geosensor networks is to collect, analyze and estimate information about continuous phenomena under observation such as a toxic cloud close to a chemical plant in real-time and in an energy-efficient way. The main thrust of this project is the integration of spatial data analysis techniques with in-network data query execution in sensor networks. The project investigates novel algorithms such as incremental, in-network kriging that redefines a traditional, highly computationally intensive spatial data estimation method for a distributed, collaborative and incremental processing between tiny, energy and bandwidth constrained sensor nodes. This work includes the modeling of location and sensing characteristics of sensor devices with regard to observed phenomena, the support of temporal-spatial estimation queries, and a focus on in-network data aggregation algorithms for complex spatial estimation queries. Combining high-level data query interfaces with advanced spatial analysis methods will allow domain scientists to use sensor networks effectively in environmental observation. The project has a broad impact on the community involving undergraduate and graduate students in spatial database research at the University of Maine as well as being a key component of a current IGERT program in the areas of sensor materials, sensor devices and sensor. More information about this project, publications, simulation software, and empirical studies are available on the project's web site (http://www.spatial.maine.edu/~nittel/career/).