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Optimal Data Placement for Stripe Merging in Locally Repairable Codes

Si Wu, Qingpeng Du, Patrick P. C. Lee, Yongkun Li, Yinlong Xu

2022Year
23Citations
1Top-tier citations

Abstract

Erasure coding is a storage-efficient redundancy scheme for modern clustered storage systems by storing stripes of data and parity blocks across the nodes of multiple clusters; in particular, locally repairable codes (LRC) continue to be one popular family of practical erasure codes that achieve high repair efficiency. To efficiently adapt to the dynamic requirements of access efficiency and reliability, storage systems often perform redundancy transitioning by tuning erasure coding parameters. In this paper, we apply a stripe merging approach for redundancy transitioning of LRC in clustered storage systems, by merging multiple LRC stripes to form a large LRC stripe with low storage redundancy. We show that the random placement of multiple LRC stripes that are being merged can lead to high cross-cluster transitioning bandwidth. To this end, we design an optimal data placement scheme that provably minimizes the cross-cluster traffic for stripe merging, by judiciously placing the blocks to be merged in the same cluster while maintaining the repair efficiency of LRC. We prototype and implement our optimal data placement scheme on a local cluster. Our evaluation shows that it significantly reduces the transitioning time by up to 43.2% compared to the baseline.

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