Accelerate RAID scaling by reducing disk I/Os and XOR operations

Zhu Yuan, Ping Xie, Xiaojuan Zhang, Shengling Geng, Jun Ma
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Abstract

In order to suffice the storage requirements under the big data environment, scaling method is generally adopted to increase the storage capacity of the storage system with the exponential growth of data in the current. RAID has received wide attention in the academic and the industry due to good independence and redundancy. After long-term development, RAID has derived different RAID levels according to distinct requirements of users. In order to achieve load balance including old and new, some data need to be migrated from old data disks to new data disks. However, there will generate the disk I/O operations and the XOR computational operations because of the existence of independent parity disk during the migration process. These affect the efficiency of scaling to a certain extent and lead the problem of long scaling time. In this paper, the scaling process for RAID-4 is optimized by reducing the disk I/O operations and the XOR computational overhead. In the comparison experiment analysis of real storage system scaling, the scaling time of optimization approach is reduced by 49.9% to 57.3% compared with the traditional scaling approach.
通过减少磁盘I/ o和异或操作加速RAID扩展
为了满足大数据环境下的存储需求,在当前数据呈指数级增长的情况下,一般采用扩容的方式来增加存储系统的存储容量。RAID由于具有良好的独立性和冗余性而受到学术界和业界的广泛关注。经过长期的发展,RAID根据用户的不同需求衍生出了不同的RAID级别。为了实现新旧负载均衡,需要将部分数据从旧数据磁盘迁移到新数据磁盘上。但是,由于在迁移过程中存在独立的奇偶盘,因此会产生磁盘I/O操作和异或计算操作。这些都在一定程度上影响了除垢效率,导致了除垢时间过长的问题。在本文中,通过减少磁盘I/O操作和异或计算开销来优化RAID-4的扩展过程。在实际存储系统扩容的对比实验分析中,优化方法的扩容时间比传统的扩容方法缩短了49.9% ~ 57.3%。
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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