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Design and optimization for distributed indexing scheme in switch-centric cloud storage system

机译:以交换机为中心的云存储系统中分布式索引方案的设计与优化

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The capacity of data management and the query performance are two main metrics for today's cloud storage system. In this paper, we design a two-layer indexing scheme of distributed secondary index on switch-centric data center network (DCN) topologies. We take advantage of the desirable features of switch-centric topologies, such as stability, scalability, and fault tolerance, and successfully improve the query efficiency for cloud storage system. We choose B+-tree as the local layer index to locate data in each local host, while implement segment tree as the global layer index to manage a portion of metadata published from local hosts. We also optimize the query processing protocols to reduce false positives and network cost. In addition, we propose a top-down index selection method for maintenance. We then analyze the efficiency of query processing theoretically and calculate the expected number of routing cost for each query precisely. Finally we validate the efficiency of our design by experiments and comparison with a previous work.
机译:数据管理的容量和查询性能是当今云存储系统的两个主要指标。在本文中,我们设计了以交换机为中心的数据中心网络(DCN)拓扑结构的分布式二级索引的两层索引方案。我们利用以交换机为中心的拓扑的理想功能,例如稳定性,可伸缩性和容错能力,并成功提高了云存储系统的查询效率。我们选择B +树作为本地层索引以在每个本地主机中定位数据,而将段树作为全局层索引来管理从本地主机发布的部分元数据。我们还优化了查询处理协议,以减少误报和网络成本。另外,我们提出了一种自上而下的维护指标选择方法。然后,我们从理论上分析查询处理的效率,并精确计算每个查询的预期路由成本数量。最后,我们通过实验并与以前的工作进行比较来验证设计的效率。

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