Oowards Multi-Resolution Database Management Systems

Oowards 多分辨率数据库管理系统

• 批准号: 9312003
• 负责人: Abraham Silberschatz
• 金额: $ 39.75万
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1993
• 资助国家: 美国
• 起止时间: 1993-11-15 至 1997-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9312003&HistoricalAwards=false
• 关键词: Oowards; Multi; Resolution; Database; Management

9312003 Silberschatz The use of data at different levels of information content is essential to the performance of very large databases because lower information content (or lower resolution) data is smaller and thus can significantly decrease I/O and communication costs. The ability to trade query response resolution for faster performance has been suggested as an approach to meeting real-time performance constraints. These two performance advantages of a multiresolution system can be exploited fully only by a database management system (DBMS) that supports the convenient retrieval of data at different levels of resolution. A data model that defines and supports the notions of multiresolution and incremental improvement of query responses, or "progressive refinement," is constructed. The basis of this model is a new construct, called the "sandbag," for representing imprecise information about a set. Practical, efficient algorithms that implement the sandbag, and thus enable a multiresolution DBMS, are developed. An extended query language that specifies the tradeoff of resolution for performance, and a mechanism for implementing such queries, are also developed. This research will provide solutions which effectively balance performance and cost for the information-processing challenges of next generation database applications such as multimedia, scientific, geographic, and other very large databases. ***

小行星9312003 使用不同信息含量级别的数据对于大型数据库的性能至关重要，因为信息含量较低（或分辨率较低）的数据较小，因此可以显著降低I/O和通信成本。 为了更快的性能而牺牲查询响应分辨率的能力被认为是满足实时性能约束的一种方法。 多分辨率系统的这两个性能优势只能通过支持不同分辨率级别的数据的方便检索的数据库管理系统（DBMS）来充分利用。 一个数据模型，定义和支持的概念，多分辨率和增量改进的查询响应，或“渐进式细化”，构建。 这个模型的基础是一个新的构造，称为“沙袋”，用于表示关于集合的不精确信息。 实用，高效的算法，实现沙袋，从而使多分辨率DBMS，开发。 一个扩展的查询语言，指定的性能的分辨率的权衡，并实现这种查询的机制，也被开发。 这项研究将为下一代数据库应用程序（如多媒体，科学，地理和其他超大型数据库）的信息处理挑战提供有效平衡性能和成本的解决方案。 ***