MII: Infrastructure for Research and Training on High -Performance Heterogeneous Distributed Database Management
MII: Infrastructure for Research and Training on High -Performance Heterogeneous Distributed Database Management
批准号:
9711582
负责人:
Naphtali Rishe
金额:
$125.0万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
1997
资助国家:
美国
项目状态:
已结题
起止时间:
1997-08-15 至 2003-07-31
中文摘要
97-11582里什,纳夫塔利·巴顿,大卫·佛罗里达国际大学(FIU)cise MII:高性能异类分布式数据库管理研究和培训的基础设施。该奖项将用于吸引和留住少数族裔学生,鼓励高性能的数据库研究。计划是一个特别的指导计划,仿照德克萨斯大学埃尔帕索分校的“亲和力小组”。这些小组由本科生和研究生、博士后和教职员工组成,提供了一个框架,通过在参与合作研究的环境中获得实际环境来加深对某一领域的知识。有组织的活动有助于知识转让,并有助于确定进展情况。本科生暑期实习的预算是让他们参与研究项目。FIU高性能数据库研究中心内的亲缘关系小组对开发异类分布式数据库管理系统(HDBMS)进行研究,通过应用和利用语义数据库管理系统来定义异类数据的全球模式,从而提供不同数据源的快速集成和高效的互操作性。SQL的语义解释用于实现关系数据库和面向对象数据库的高效互操作性。采用动态调度的代理技术,实现了分布式、异构型数据库的接口。在存在异质网络的情况下,查询优化技术正在被评估和研究。
英文摘要
97-11582 Rishe, Naphtali Barton, David Florida International University (FIU) CISE MII: Infrastructure for Research and Training on High-Performance Heterogeneous Distributed Database Management. This award is to be used to attract and retain minority students, encouraging high-performance database research. Planned is a special mentoring program modeled after the "Affinity Groups" of the University of Texas at El Paso. The groups, consisting of undergraduate and graduate students, post-docs, and faculty members, provide the framework that enables deepening knowledge of a field by procuring a physical setting in a cooperative research-engaging environment. Structured activities facilitate knowledge transfer and serve to ascertain progress. Summer internships for undergraduates are budgeted to involve them in research projects. The affinity groups, within the FIU High Performance Database Research Center at FIU performs research towards the development of a heterogeneous distributed database management system (HDBMS) providing fast integration of disparate data sources and efficient interoperability through the application and utilization of a semantic database management system to define a global schema of the heterogeneous data. A semantic interpretation of SQL is used for efficient interoperability of relational and object-oriented databases. Dynamically-dispatched agent technology is used to interface the distributed heterogeneous databases. Query optimization techniques in the presence of heterogeneous networks are being evaluated and investigated.
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