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Journal of Zhejiang University SCIENCE C 1998 Vol.-1 No.-1 P.

http://doi.org/10.1631/FITEE.2100242


SA-RSR: a read-optimal data recovery strategy for XOR-coded distributed storage systems


Author(s):  Xingjun ZHANG, Ningjing LIANG, Yunfei LIU, Changjiang ZHANG

Affiliation(s):  School of Computer Science and Technology, Xi'an Jiaotong University, Xi’an 710049, China

Corresponding email(s):   xjzhang@xjtu.edu.cn, l_ningjing@stu.xjtu.edu.cn, liuyunfei@stu.xjtu.edu.cn, zcj9527@stu.xjtu.edu.cn

Key Words:  Distributed storage system, Data reliability and availability, XOR-based erasure codes, Single-node failure, Data recovery


Xingjun ZHANG, Ningjing LIANG, Yunfei LIU, Changjiang ZHANG. SA-RSR: a read-optimal data recovery strategy for XOR-coded distributed storage systems[J]. Frontiers of Information Technology & Electronic Engineering, 1998, -1(-1): .

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publisher="Zhejiang University Press & Springer",
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Abstract: 
To ensure the reliability and availability of data, redundancy strategies are always required for distributed storage systems. Erasure coding, one of the representative redundancy strategies, has the advantage of low storage overhead which facilitates its employment in distributed storage systems. Among the various erasure coding schemes, XOR-based erasure codes are becoming popular due to their fast computing speed. When single-node failure happens in such coding schemes, a process called data recovery takes place to retrieve the failed node’s lost data from the surviving nodes. However, the data transmission during the data recovery process usually requires a considerable amount of time. Current research has mainly focused on reducing the amount of data needed for data recovery to reduce the time required for data transmission, but has encountered problems such as significant complexity and local optima. In this paper, we propose a random search recovery algorithm, named SA-RSR, to speed up single-node failure recovery of XOR-based erasure codes. SA-RSR utilizes a simulated annealing technique to search for an optimal recovery solution that reads and transmits a minimum amount of data. In addition, this search process can be done in polynomial time. We evaluate SA-RSR with a variety of XOR-based erasure codes in simulations and in a real storage system, Ceph. Experiments in Ceph show that SA-RSR reduces the amount of data required for recovery by 20–30% and improves the performance of data recovery by 13–20% compared to the conventional recovery method.

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