Optimal Repair-Scaling Trade-off in Locally Repairable Codes: Analysis and Evaluation
Optimal Repair-Scaling Trade-off in Locally Repairable Codes: Analysis and Evaluation
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DOI：
10.1109/tpds.2021.3087352
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发表时间：
2022-01
影响因子：
5.3
通讯作者：
Si Wu;Zhirong Shen;P. Lee;Yinlong Xu
中科院分区：
文献类型：
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作者：
Si Wu;Zhirong Shen;P. Lee;Yinlong Xu
如何提高纠删编码存储的修复性能是保证现代大型存储系统高可靠性的关键问题。局部可修复码（LRC）是一种流行的修复高效擦除码，它减少了修复带宽，并在实践中得到了应用。为了适应不断变化的访问效率和容错需求，现代存储系统还对擦除编码数据进行频繁的扩容操作。在本文中，我们分析了LRC在集群存储系统中的修复性能和扩展性能之间的最优权衡。具体来说，我们关注的是两个最优修复-缩放权衡，并设计了在容错约束下沿着两个最优修复-缩放权衡曲线运行的放置策略。我们在局域网测试平台上对我们的放置策略进行了原型和评估，并表明它们在修复和缩放操作中优于传统的放置方案。
How to improve the repair performance of erasure-coded storage is a critical issue for maintaining high reliability of modern large-scale storage systems. Locally repairable codes (LRC) are one popular family of repair-efficient erasure codes that mitigate the repair bandwidth and are deployed in practice. To adapt to the changing demands of access efficiency and fault tolerance, modern storage systems also conduct frequent scaling operations on erasure-coded data. In this article, we analyze the optimal trade-off between the repair and scaling performance of LRC in clustered storage systems. Specifically, we focus on two optimal repair-scaling trade-offs, and design placement strategies that operate along the two optimal repair-scaling trade-off curves subject to the fault tolerance constraints. We prototype and evaluate our placement strategies on a LAN testbed, and show that they outperform the conventional placement schemes in repair and scaling operations.