A Comprehensive Rearranging Priority Based Method To Accelerate the Reconstruction of RAID Arrays

Xin Xie, Chentao Wu, Chao Li, Jie Li, M. Guo, Fang Xu
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Abstract

With the development of cloud computing, the reliability of disk arrays are increasingly concerned. Data centers usually use erasure codes to provide high reliability. However, most of reconstruction methods on disk arrays focus on single/ multiple disk(s) recovery, which ignores how to efficiently reconstruct the lost data such as Latent Sector Errors (LSEs), etc. In real situations, local stripe errors are much more common than disk failures. It has become an urgent problem that how to improve reconstruction efficiently for stripes. This paper proposes a comprehensive rearranging priority reconstruction(CRPR), which combines temporal locality, spatial locality and coding characteristics together. CRPR divides different blocks into various priorities and recovers them sequentially. To demonstrate the effectiveness of CRPR, we conduct several simulations via disksim. The simulations results show that, the comprehensive rearranging priority reconstruction method keeps up with previous methods and can save up to 63.9% in terms of waiting time.
一种基于综合重排优先级的加速RAID重构方法
随着云计算的发展,磁盘阵列的可靠性越来越受到人们的关注。数据中心通常使用擦除码来提供高可靠性。然而,大多数磁盘阵列的重构方法都集中在单盘/多盘恢复上,而忽略了如何有效地重构丢失的数据,如潜在扇区错误(Latent Sector error, lse)等。在实际情况下,本地分条错误比磁盘故障更常见。如何提高条纹图像的重构效率已成为一个亟待解决的问题。提出了一种综合时间局部性、空间局部性和编码特征的重排优先级重构方法。CRPR将不同的块划分为不同的优先级,并依次恢复。为了证明CRPR的有效性,我们通过disksim进行了多次仿真。仿真结果表明,综合重排优先级重建方法与以往方法基本一致,可节省63.9%的等待时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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