%0 Journal Article
%T Pipeline-Based Multi-Query Optimization for Similarity Queries in Grid Environment
网格环境下基于流水线的多重相似查询优化
%A HU Hua
%A ZHUANG Yi
%A HU Hai-Yang
%A Dickson CHIU
%A
胡华
%A 庄毅
%A 胡海洋
%A 赵格华
%J 软件学报
%D 2010
%I
%X 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.
%K grid
%K multi-query optimization
%K high-dimensional indexing
%K data partition
网格
%K 多重查询优化
%K 高维索引
%K 数据分片
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=7735F413D429542E610B3D6AC0D5EC59&aid=F205B4F2CE8578602989B75BB3147943&yid=140ECF96957D60B2&vid=659D3B06EBF534A7&iid=CA4FD0336C81A37A&sid=E514EE58E0E50ECF&eid=5D71B28100102720&journal_id=1000-9825&journal_name=软件学报&referenced_num=0&reference_num=23