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Object Clustering Heuristics and Algorithms in Next Generation Database Management Systems

下一代数据库管理系统中的对象集群启发式和算法

基本信息

批准号：
9006348
负责人：
Roger King
金额：
$ 17.5万
依托单位：
University of Colorado at Boulder
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
1990
资助国家：
美国
起止时间：
1990-09-15 至 1993-02-28
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=9006348&HistoricalAwards=false
关键词：
Object Clustering Heuristics Algorithms Next

项目摘要

Traditional (e.g., relational) database systems cluster data on disks in order to minimize the cost of accessing information; such mechanisms are simplistic and are designed before the system is put into use - and are never changed. But new applications are making bigger demands on database systems. An example is aircraft engineering, where multiple designers simultaneously perform ever-changing manipulations on complex integrations of electronic and mechanical engineering components. This is in contrast to data processing, where highly-predictable data manipulations are typically performed. This has caused data clustering to emerge as a critical area demanding newer and more powerful algorithmic results. The goal of the self-adaptive clustering project is to consider the wide variety of factors that come into play when one considers clustering algorithms which are not constructed in advance and can adapt themselves to changing, unusual database access patterns. This will lead to the development of a theory of self-adaptive clustering, which will be of great significance to a wide variety of database users, in particular CAD/CAM, software, printed circuit board, and VLSI designers. This will provide a spectrum of software algorithms which will transform overly-expensive applications into cost-effective systems.

传统的（例如，关系）数据库系统群集数据磁盘，以尽量减少访问信息的成本; 这种机制过于简单，已经投入使用，而且从未改变。但新的应用程序是对数据库系统提出了更高的要求。一个例子是飞机工程，多个设计师同时执行不断变化的操纵复杂的电子集成和机械工程部件。这不同于数据处理，其中高度可预测的数据操作通常执行。这使得数据聚类成为一个需要更新和更强大的算法的关键领域结果自适应聚类项目的目标是考虑到各种各样的因素，当一个人认为聚类算法，这不是构造在能够适应不断变化的、不寻常的数据库访问模式。这将导致一个理论的发展，自适应聚类，这将是非常重要的意义，各种各样的数据库用户，特别是CAD/CAM，软件、印刷电路板和VLSI设计人员。这将提供一系列软件算法，将过于昂贵的应用程序转化为具有成本效益的系统。