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Efficient in-place update with grouped and pipelined data transmission in erasure-coded storage systems

机译:在擦除编码存储系统中通过分组和流水线数据传输进行有效的就地更新

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摘要

Distributed storage systems usually adopt erasure coding to achieve better tradeoff between the space efficiency and the data reliability. In-place updates are often used to overwrite the existing data rather than append the new data so as to ensure the data access efficiency. However, existing in-place update approaches either introduce significant I/O overhead or cause low update efficiency in erasure-coded storage systems due to the consistent update of parity blocks. In this paper, we propose a grouped and pipelined update scheme based on erasure codes, called Group-U, which comprises four key design features. (1) It groups the data nodes to complete the data transmission and dynamically adjusts the group size according to the update workload. (2) It pipelines the data transmission and distributes the update computation to all the participating nodes to improve the update efficiency. (3) It adopts the in-time update for data nodes and lazy-update for parity nodes to further reduce the update overhead. (4) It adjusts the occasion triggering the update to be compatible with the node failure. We design and implement Group-U on our Raid Distributed Storage System (RDFS) and conduct testbed experiments on different update schemes under various parameter settings. The analysis and experimental results show that Group-U consumes 22% increase of update overhead compared with PUM and achieves 46% reduction of update overhead compared with PDP-P and PUS. Furthermore, Group-U achieves 69%, 34% and 21% reduction of update time on average compared with PUM, PDP-P and PUS respectively.
机译:分布式存储系统通常采用擦除编码,以在空间效率和数据可靠性之间取得更好的平衡。就地更新通常用于覆盖现有数据,而不是附加新数据,以确保数据访问效率。但是,由于奇偶校验块的一致性更新,现有的就地更新方法要么会引入大量的I / O开销,要么会在擦除编码存储系统中导致较低的更新效率。在本文中,我们提出了一种基于擦除码的分组流水线更新方案,称为Group-U,它包含四个关键设计功能。 (1)分组数据节点以完成数据传输,并根据更新工作量动态调整组大小。 (2)通过管道传输数据并将更新计算分配给所有参与的节点,以提高更新效率。 (3)对数据节点采用及时更新,对奇偶校验节点采用延迟更新,以进一步减少更新开销。 (4)调整触发更新的时机以与节点故障兼容。我们在Raid分布式存储系统(RDFS)上设计并实现了Group-U,并在各种参数设置下针对不同的更新方案进行了测试平台实验。分析和实验结果表明,Group-U与PUM相比,消耗了22%的更新开销,与PDP-P和PUS相比,减少了46%的更新开销。此外,与PUM,PDP-P和PUS相比,Group-U分别平均减少了69%,34%和21%的更新时间。

著录项

  • 来源
    《Future generation computer systems》 |2017年第4期|24-40|共17页
  • 作者单位

    National Key Laboratory for Parallel and Distributed Processing, College of Computer, National University of Defense Technology, Changsha, Hunan, 410073, PR China;

    National Key Laboratory for Parallel and Distributed Processing, College of Computer, National University of Defense Technology, Changsha, Hunan, 410073, PR China;

    National Key Laboratory for Parallel and Distributed Processing, College of Computer, National University of Defense Technology, Changsha, Hunan, 410073, PR China;

    National Key Laboratory for Parallel and Distributed Processing, College of Computer, National University of Defense Technology, Changsha, Hunan, 410073, PR China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    In-place; Update; Grouping; In-time; Lazy-update;

    机译:到位;更新;分组;及时;延迟更新;

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