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Correlation-Aware Stripe Organization for Efficient Writes in Erasure-Coded Storage: Algorithms and Evaluation.

Authors :
Shen, Zhirong
Lee, Patrick P. C.
Shu, Jiwu
Guo, Wenzhong
Source :
IEEE Transactions on Parallel & Distributed Systems; Jul2019, Vol. 30 Issue 7, p1552-1564, 13p
Publication Year :
2019

Abstract

Erasure coding has been extensively employed for data availability protection in production storage systems by maintaining a low degree of data redundancy. However, how to mitigate the parity update overhead of partial stripe writes in erasure-coded storage systems is still a critical concern. In this paper, we study this problem from two new perspectives: data correlation and stripe organization. We propose $\mathsf{CASO}$CASO, a correlation-aware stripe organization algorithm, which captures data correlation of a data access stream and uses the data correlation characteristics for stripe organization. It packs correlated data into a small number of stripes to reduce the incurred I/Os in partial stripe writes, and further organizes uncorrelated data into stripes to leverage the spatial locality in later access. We implement $\mathsf{CASO}$CASO over Reed-Solomon codes and Azure's Local Reconstruction Codes, and show via extensive trace-driven evaluation that $\mathsf{CASO}$CASO reduces up to 29.8 percent of parity updates and reduces the write time by up to 46.7 percent. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10459219
Volume :
30
Issue :
7
Database :
Complementary Index
Journal :
IEEE Transactions on Parallel & Distributed Systems
Publication Type :
Academic Journal
Accession number :
136980793
Full Text :
https://doi.org/10.1109/TPDS.2018.2890635