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

IIS-0546136阿莫尔V Deshpande Escherich@cs.umd.edu马里兰州大学帕克分校职业生涯：MauveDB：基于模型的用户对传感器数据的看法真实世界的数据-特别是由分布式测量基础设施（如传感器网络）生成的数据-往往是不完整的、不精确的和错误的，这使得它不可能呈现给用户或直接馈送到应用程序中。 这个项目的目标是开发一个数据管理系统MauveDB，它通过支持一个新的抽象，称为“基于模型的视图”，提供了一个处理这个问题的原则性方法。MauveDB是利用Apache Derby数据库管理系统（DBMS）代码库构建的。 类似于传统的数据库视图，基于模型的视图提供了与底层数据生成机制的细节的独立性，并通过使用统计和概率“模型”来隐藏数据的不规则性，以向用户呈现数据的一致视图。MauveDB支持用于定义基于模型的视图的声明性语言，并使用支持连续和概率查询的SQL扩展版本支持基于模型的视图的声明性查询。作为一个成熟的数据库管理系统，MauveDB还可以轻松存储、归档和查询历史数据。通过减轻用户处理嘈杂的现实世界数据的负担，MauveDB能够实现基于监控和传感设备网络的高影响力的新型现实世界应用，例如交通监控，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，将用于正在开发的新课程模块在马里兰州大学;代码和课程材料开发也将免费提供在项目网站http://www.cs.umd.edu/~amol/MauveDB。

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.