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A Reliability Optimization Method Using Disk Reliability Degree and Data Heat Degree

机译:一种可靠性优化方法,使用磁盘可靠度和数据热度

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The reliability of the traditional storage system can utilize data recovery and reconstruction operations to recover data in case of the disk failure; however it will result in longer data recovery time and increase the possibility of secondary failure. Hence, reliability optimization has become one of the key subjects of storage system research. In this paper we propose a novel reliability optimization method, which uses disk reliability degree to evaluate the reliability of disk based on SMART technology. And it uses data heat degree to compute the heat degree of data and the utilization degree of disk at the present time, so according to disk reliability degree and disk utilization degree we can protect current hotspots data. Data heat degree also predicts hotspots data in the future based on the current rank of data access frequency and Zipf-like distribution; we can also protect predicted new hotspots data according to disk reliability degree. Our experiment shows that disk reliability degree satisfies the actual usage and data heat degree achieves very high prediction accuracy. In order to evaluate the system performance's influence of our method, the experimental results of data migration based on RAID system demonstrate that reliability optimization method has little or no impact on the normal system performance, and outperforms the traditional reconstruct RAID system.
机译:传统存储系统的可靠性可以利用数据恢复和重建操作来恢复数据,以便在磁盘发生故障时恢复数据;但是它将导致更长的数据恢复时间并增加二次失败的可能性。因此,可靠性优化已成为存储系统研究的关键科目之一。本文提出了一种新颖的可靠性优化方法,它利用磁盘可靠度来评估智能技术的磁盘可靠性。并且它使用数据热程来计算当前时间的数据和利用程度,因此根据磁盘可靠度和磁盘利用程度,我们可以保护电流热点数据。数据热度还基于当前的数据访问频率和ZIPF样分布的当前等级来预测将来的热点数据;我们还可以根据磁盘可靠性度保护预测的新热点数据。我们的实验表明,磁盘可靠性程度满足实际使用量和数据热度达到非常高的预测精度。为了评估系统性能对我们方法的影响,基于RAID系统的数据迁移的实验结果表明,可靠性优化方法对正常系统性能几乎没有影响,并且优于传统的重建RAID系统。

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