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首页> 外文期刊>Mathematical Problems in Engineering: Theory, Methods and Applications >Data Placement Algorithm for Improving I/O Load Balance without Using Popularity Information
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Data Placement Algorithm for Improving I/O Load Balance without Using Popularity Information

机译:用于改善I / O负载平衡而不使用人气信息的数据放置算法

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摘要

Data placement considerably affects the I/O performance of distributed storage systems such as HDFS. An ideal placement algorithm should keep the I/O load evenly distributed among different storage nodes. Most of the existing placement algorithms with I/O load balance guarantee depend on the information of data popularity to make the placement decisions. However, the popularity information is typically not available in the data placement phase. Furthermore, it usually varies during the data lifecycle. In this paper, we propose a new placement algorithm called Balanced Distribution for Each Age Group (BEAG), which makes data placement decisions in the absence of the popularity information. This algorithm maintains multiple counters for each storage node, with each counter representing the amount of data belonging to a certain age group. It ensures that the data in each age group are equally scattered among the different storage nodes. As the popularity variance of the data belonging to the same age group is considerably smaller than that of the entire data, BEAG significantly improves the I/O load balance. Experimental results show that compared to other popularity independent algorithms, BEAG decreases the I/O load standard deviation by 11.6% to 30.4%.
机译:数据展示位置显着影响分布式存储系统(如HDF)的I / O性能。理想的放置算法应保持不同存储节点中的I / O负载均匀分布。具有I / O负载平衡保证的大多数现有的放置算法取决于数据流行度的信息,以进行放置决策。然而,人气信息通常不可用数据放置阶段。此外,它通常在数据生命周期期间变化。在本文中,我们提出了一种称为每个年龄组(BEAG)的平衡分布的新放置算法,其在不存在受欢迎信息的情况下使数据放置决策。该算法为每个存储节点维护多个计数器,每个计数器表示属于特定年龄组的数据量。它确保每个年龄组中的数据在不同的存储节点之间同样地分散。由于属于同一年龄组的数据的受欢迎程度大于整个数据的数据,因此Beag显着提高了I / O负载平衡。实验结果表明,与其他普及独立算法相比,Beg将I / O负荷标准偏差降低11.6%至30.4%。

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