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.

中文翻译：

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局部可修复代码中的最佳修复缩放权衡：分析和评估

如何提高纠删码存储的修复性能是维持现代大规模存储系统高可靠性的关键问题。本地可修复代码 (LRC) 是一种流行的修复高效擦除代码系列，可减少修复带宽并在实践中部署。为了适应不断变化的访问效率和容错需求，现代存储系统还对纠删码数据进行频繁的扩展操作。在本文中，我们分析了集群存储系统中 LRC 的修复和扩展性能之间的最佳权衡。具体来说，我们专注于两个最佳修复缩放权衡，以及设计布局策略，该策略沿着受容错约束的两个最佳修复缩放权衡曲线运行。