STBucket: A Self-Tuning Bucket Index in DAS Paradigm
STBucket: A Self-Tuning Bucket Index in DAS Paradigm
复制标题
DOI：
10.1109/chinagrid.2009.38
复制
发表时间：
2009-08
期刊：
影响因子：
--
通讯作者：
Haocong Wang;Xiaoyong Du;Jieping Wang;Pingping Yang
中科院分区：
文献类型：
--
作者：
Haocong Wang;Xiaoyong Du;Jieping Wang;Pingping Yang
在数据库即服务 (DAS) 范式中，数据所有者将其数据外包给第三方服务提供商。由于服务提供商不可信，因此在外包之前应对数据进行加密。人们提出了多种方法来查询加密数据，其中基于桶的方法是有效的。然而，之前的研究只是着眼于给定工作负载的数据分布，这对于改变工作负载行为是无效的。在本文中，我们提出了一种自调整桶方案：STBucket。通过收集和分析查询反馈，STBucket 通过在线桶分裂和合并来实现对工作负载的适应。实验结果表明，STBucket 具有工作负载感知能力，并且在合理的开销下表现良好。）
In the Database-As-a-Service (DAS) paradigm, data owners outsource their data to the third-party service provider. Since the service provider is untrusted, the data should be encrypted before outsourced. Various approaches have been proposed to query on encrypted data, among which bucket based method is effective. However, previous researches just look at the data distribution with respect to a given workload, which is ineffective in changing workload behaviors. In this paper, we propose a Self-Tuning Bucket scheme: STBucket. By gathering and analyzing query feedback, STBucket achieves adaptation to workload through online bucket splitting and merging. Experimental results show that STBucket is workload aware and performs well with reasonable overhead.)