CAREER: New Technologies for Approximate Query Processing
CAREER: New Technologies for Approximate Query Processing
批准号:
0448264
负责人:
Alin Dobra
金额:
$0.0万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2005
资助国家:
美国
项目状态:
已结题
起止时间:
2005-06-01 至 2011-05-31
中文摘要
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英文摘要
One of the two goals of the project is to advance the state-of-the art in approximate query processing (AQP), a critical component of analytical processing -- a 3.5 billion dollar segment of the software industry. The need for approximate query processing arises from the growing discrepancy between the volume of information that has to be processed and the computational resources or communication capabilities available. Using two computational models, data-streaming and distributed computation, the project addresses fundamental problems in AQP such as development of new approximation techniques for data-stream computation, extensions of data-stream algorithms to distributed algorithms that can efficiently query sensor and peer-to-peer networks, and theoretical aspects of AQP that allow the design of AQP techniques to be accelerated and better understood. Part of the project's research goal is the design and implementation of a approximate query processing engine that uses the developed AQP techniques and the rigorous benchmarking of the software produced. The second goal of the project is educational and consists in, on one hand, motivating students to study and pursue carers in databases through bonus points for extra activities and integration of the database curricula and other CS disciplines, and, on the other hand, integration of approximate query processing into both undergraduate and graduate curricula. The project will have broad impact by developing techniques for efficient processing of large volumes of data -- crucial for scientific data processing and home-land security -- and by increasing the quality of database education with a direct impact on nation's technological leadership.http://www.cise.ufl.edu/~adobra/AQP
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
III: EAGER: A Framework for Large Data Analysis
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批准号:1144985
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项目类别:Standard Grant
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资助金额:$10.0万
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财政年份:2011
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负责人:Alin Dobra
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依托单位:
海外基金