Pipeline-based multi-query optimization for similarity queries in grid environment

被引：0
|
作者：
Hu H. [1 ,2 ]
Zhuang Y. [2 ]
Hu H.-Y. [1 ,2 ]
Chiu D. [3 ]
机构：
[1] College of Computer Science, Hangzhou Dianzi University
[2] College of Computer and Information Engineering, Zhejiang Gongshang University
[3] Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong
来源：
Ruan Jian Xue Bao/Journal of Software | 2010年 / 21卷 / 01期
关键词：
Data partition; Grid; High-dimensional indexing; Multi-query optimization;
D O I：
10.3724/SP.J.1001.2010.03665
中图分类号：
学科分类号：
摘要：
This paper proposes a multi-query optimization algorithm for pipeline-based distributed similarity query processing (pGMSQ) in grid environment. First, when a number of query requests are simultaneously submitted by users, a cost-based dynamic query clustering (DQC) is invoked to quickly and effectively identify the correlation among the query spheres (requests). Then, index-support vector set reduction is performed at data node level in parallel. Finally, refinement of the candidate vectors is conducted to get the answer set at the execution node level. By adopting pipeline-based technique, this algorithm is experimentally proved to be efficient and effective in minimizing the response time by decreasing network transfer cost and increasing the throughput. © by Institute of Software, the Chinese Academy of Sciences. All rights reserved.
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页码：55 / 67
页数：12
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