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An efficient and scalable multi-dimensional indexing scheme for modular data centers

机译:一种高效且可扩展的模块化数据中心多维索引方案

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An efficient distributed indexing scheme plays an important role in improving the performance of cloud storage systems. To achieve concurrent query service and high manageability, the indexing scheme should meet the requirements of high scalability and low latency. In this paper, we propose RB-Index, an efficient and scalable multi-dimensional indexing scheme for modular data centers with the BCube topology. RB-Index is a two-layer indexing scheme integrating the BCube based routing protocol and the R-tree based indexing structure. In RB-Index, we build several distinct indexing spaces with dimensions selected according to query history. Each server takes responsibility for a portion of the indexing space according to a mapping scheme. A data pretreatment method and a publishing scheme are presented to uniformly distribute the global index across all the servers in the network. Index maintenance strategies are designed to keep the system cost at a low level. Efficient and complete query strategies are also introduced to support highly concurrent queries. We conduct experiments on Amazon EC2 platform to evaluate the performance of RB-Index and compare its performance with RT-CAN and FT-Index. Experiment results manifest the efficiency and scalability of our indexing scheme.
机译:高效的分布式索引方案在提高云存储系统的性能方面起着重要作用。为了实现并发查询服务和高可管理性,索引方案应满足高可伸缩性和低延迟的要求。在本文中,我们提出了RB-Index,这是一种具有BCube拓扑的模块化数据中心的高效,可扩展的多维索引方案。 RB-Index是将基于BCube的路由协议和基于R-tree的索引结构集成在一起的两层索引方案。在RB-Index中,我们构建了几个不同的索引空间,并根据查询历史记录选择了维度。每个服务器根据映射方案负责一部分索引空间。提出了一种数据预处理方法和一种发布方案,以将全局索引均匀分布在网络中的所有服务器上。索引维护策略旨在将系统成本保持在较低水平。还引入了高效,完整的查询策略来支持高度并发的查询。我们在Amazon EC2平台上进行实验,以评估RB-Index的性能,并将其性能与RT-CAN和FT-Index进行比较。实验结果证明了我们索引方案的效率和可扩展性。

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