摘要
K最近邻(KNN)查询是相似性查询的一种,已有大部分KNN查询算法都是针对集中式计算环境的,因此很容易形成性能瓶颈。P2P这种新的分布式计算技术能够有效克服集中式计算环境中的性能瓶颈问题。提出了一种分组式P2P网络结构下基于iDisdance索引的KNN查询方法,其主要思想是通过分布式簇索引裁剪搜索空间,降低网络通信开销,从而在P2P环境下执行KNN查询。最后通过仿真测试了该方法的有效性以及分组数量与数据分布对查询开销的影响。
KNN （K-Nearest Neighbor） query is a kind of similarity query.A majority of KNN query algorithms are intended for concentrated computing environment,which will easily lead to performance bottle-neck.P2P,the new distributed computing technology,can effectively overcome the performance bottle-neck highlighted in the concentrated computing environment.A KNN query approach based on iDisdance index in grouping P2P networks was put forward.In the precondition of distributed clustering index prune in searching of space,this approach effectively reduced the network communication overhead,thus the KNN query could be implemented in P2P.The simulation results prove its validity and influences on query spending from the group number and data distribution.
出处
《计算机应用》
CSCD
北大核心
2010年第5期1156-1158,共3页
journal of Computer Applications
