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

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 th...

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Vydané v:IEEE transactions on parallel and distributed systems Ročník 30; číslo 7; s. 1552 - 1564
Hlavní autori: Shen, Zhirong, Lee, Patrick P. C., Shu, Jiwu, Guo, Wenzhong
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York IEEE 01.07.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Algorithms
Correlation
Data correlation
Distributed databases
Encoding
erasure code
Maintenance engineering
Organizations
Parity
partial stripe writes
Redundancy
Reed-Solomon codes
Storage systems
stripe organization
ISSN:1045-9219, 1558-2183
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Shrnutí: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.
Bibliografia:ObjectType-Article-1
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ISSN:1045-9219
1558-2183
DOI:10.1109/TPDS.2018.2890635