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基于KD树和R树的多维云数据索引
引用本文:何婧,吴跃,杨帆,尹春雷,周维.基于KD树和R树的多维云数据索引[J].计算机应用,2014,34(11):3218-3221.
作者姓名:何婧  吴跃  杨帆  尹春雷  周维
作者单位:1. 电子科技大学 计算机科学与工程学院,成都 611731; 2. 云南大学 软件学院,昆明 650091; 3. 云南农业大学 建筑工程学院,昆明 650201
基金项目:国家自然科学基金资助项目,云南省教育厅科学研究基金资助项目
摘    要:针对云存储系统大多基于键值对模型存储数据,多维查询需要对整个数据集进行完全扫描,查询效率较低的问题,提出了一种基于KD树和R树的多维索引结构(简称KD-R索引)。KD-R索引采用双层索引模式,在全局服务器建立基于KD树的多维全局索引,在局部数据节点构建R树多维本地索引。基于性能损耗模型,选取索引代价较小的R树节点发布到全局KD树,从而优化多维查询性能。实验结果表明:与全局分布式R树索引相比,KD-R索引能够有效提高多维范围查询性能,并且在出现服务器节点失效的情况下,KD-R索引同样具有高可用性。

关 键 词:云计算  云存储  云数据管理  多维索引  范围查询
收稿时间:2014-05-14
修稿时间:2014-07-03

Multi-dimensional cloud index based on KD-tree and R-tree
HE Jing,WU Yue,YANG Fan,YIN Chunlei,ZHOU Wei.Multi-dimensional cloud index based on KD-tree and R-tree[J].journal of Computer Applications,2014,34(11):3218-3221.
Authors:HE Jing  WU Yue  YANG Fan  YIN Chunlei  ZHOU Wei
Affiliation:1. School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu Sichuan 611731, China;
2. School of Software, Yunnan University, Kunming Yunnan 650091, China;
3. School of Architecture Engineering, Yunnan Agricultural University, Kunming Yunnan 650201, China
Abstract:Most existing cloud storage systems are based on the model, which leads to a full dataset scan for multi-dimensional queries and low query efficiency. A KD-tree and R-tree based multi-dimensional cloud data index named KD-R index was proposed. KD-R index adopted two-layer architecture: a KD-tree based global index was built in the global server and R-tree based local indexes were built in local server. A cost model was used to adaptively select appropriate R-tree nodes to publish into global KD-tree index. The experimental results show that, compared with R-tree based global index, KD-R index is efficient for multi-dimensional range queries, and it has high availability in the case of server failure.
Keywords:cloud computing  cloud storage  cloud data management  multi-dimensional index  range query
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