On the Optimal Repair-Scaling Trade-off in Locally Repairable Codes.

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Abstract

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 paper, we analyze the optimal trade-off between the repair and scaling performance of LRC in clustered storage systems. Specifically, we design placement strategies that operate along the optimal repair-scaling trade-off curve 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 scheme in repair and scaling operations.

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Key words

locally repairable codes,repair performance,erasure-coded storage,modern large-scale storage systems,repair-efficient erasure codes,mitigate the repair bandwidth,modern storage systems,frequent scaling operations,erasure-coded data,optimal trade-off,scaling performance,clustered storage systems,optimal repair-scaling trade-off curve subject

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