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Declustering Two-Dimensional Datasets over MEMS-Based Storage

机译:在基于MEMS的存储上减少二维数据集

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摘要

Due to the large difference between seek time and transfer time in current disk technology, it is advantageous to perform large I/O using a single sequential access rather than multiple small random I/O accesses. However, prior optimal cost and data placement approaches for processing range queries over two-dimensional datasets do not consider this property. In particular, these techniques do not consider the issue of sequential data placement when multiple I/O blocks need to be retrieved from a single device. In this paper, we reevaluate the optimal cost of range queries by declustering two-dimensional datasets over multiple devices, and prove that, in general, it is impossible to achieve the new optimal cost. This is because disks cannot facilitate two-dimensional sequential access which is required by the new optimal cost. Fortunately, MEMS-based storage is being developed to reduce I/O cost. We first show that the two-dimensional sequential access requirement can not be satisfied by simply modeling MEMS-based storage as conventional disks. Then we propose a new placement scheme that exploits the physical properties of MEMS-based storage to solve this problem. Our theoretical analysis and experimental results show that the new scheme achieves almost optimal results.
机译:由于当前磁盘技术中查找时间和传输时间之间的巨大差异,使用单个顺序访问而不是多个小的随机I / O访问来执行大型I / O是有利的。但是,用于处理二维数据集范围查询的现有最佳成本和数据放置方法没有考虑此属性。特别是,当需要从单个设备中检索多个I / O块时,这些技术不会考虑顺序数据放置的问题。在本文中,我们通过对多个设备上的二维数据集进行聚类来重新评估范围查询的最佳成本,并证明一般而言,不可能获得新的最佳成本。这是因为磁盘无法促进二维顺序访问,这是新的最佳成本所要求的。幸运的是,正在开发基于MEMS的存储以降低I / O成本。我们首先表明,仅通过将基于MEMS的存储建模为常规磁盘无法满足二维顺序访问要求。然后,我们提出了一种新的放置方案,该方案利用了基于MEMS的存储的物理特性来解决此问题。我们的理论分析和实验结果表明,该新方案几乎可以达到最佳效果。

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