CAREER: MauveDB: Model-Based User Views over Sensor Data

IIS-0546136AmoL V Deshpande Aol@cs.umd.eduMarland College ParkCAREER：MauveDB：传感器数据上基于模型的用户视图真实世界的数据--尤其是由传感器网络等分布式测量基础设施生成的数据--往往是不完整、不准确和错误的，因此无法将其呈现给用户或直接提供给应用程序。该项目的目标是开发MauveDB，这是一种数据管理系统，通过支持一种称为“基于模型的视图”的新抽象，提供了一种处理此问题的原则性方法。MauveDB是通过利用Apache Derby数据库管理系统(DBMS)代码库构建的。与传统的数据库视图类似，基于模型的视图独立于底层数据生成机制的细节，并通过使用统计和概率“模型”向用户呈现一致的数据视图来隐藏数据的不规则性。MauveDB支持用于定义基于模型的视图的声明性语言，并支持使用支持连续和概率查询的扩展版本的SQL在基于模型的视图上进行声明性查询。作为一个成熟的数据库管理系统，MauveDB还可以方便地存储、存档和查询历史数据。通过减轻用户处理嘈杂的真实世界数据的负担，MauveDB实现了基于监控和传感设备网络的高影响的新一类真实世界应用，如交通监控、基于位置的服务、环境监控、健康服务和军事应用。这项研究将用于开发代码、数据集和传感器网络部署，用于马里兰大学正在开发的新课程模块；开发的代码和课程材料也将在项目网站http://www.cs.umd.edu/~amol/MauveDB.上免费提供

IIS-0546136Amol V Deshpande amol@cs.umd.eduUniversity of Maryland College ParkCAREER: MauveDB: Model-based User Views over Sensor DataReal-world data --- especially when generated by distributed measurement infrastructures such as sensor networks --- tends to be incomplete, imprecise, and erroneous, making it impossible to present it to the users or to feed it directly into applications. The goal of this project is to develop MauveDB, a data management system that offers a principled approach to dealing with this problem by supporting a new abstraction called "model-based views." MauveDB is built by leveraging the Apache Derby Database Management System (DBMS) codebase. Analogous to traditional database views, model-based views provide independence from the details of the underlying data generating mechanism and hide the irregularities of the data by using statistical and probabilistic "models" to present a consistent view of the data to the users. MauveDB supports a declarative language for defining model-based views, and supports declarative querying over model-based views using an extended version of SQL that supports continuous and probabilistic queries. Being a full-fledged DBMS, MauveDB also enables easy storage and archival and querying of historical data. By relieving the users of the burden of dealing with the noisy real-world data, MauveDB enables a high-impact new class of real-world applications based on networks of monitoring and sensing devices, such as traffic monitoring, location-based services, environmental monitoring, health services, and military applications. This research will be used to develop code, datasets and sensor network deployments that will be used in the new course modules being developed at the University of Maryland; the code and the course material developed will also be made freely available at the project web site http://www.cs.umd.edu/~amol/MauveDB.