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

机译:利用磁盘可靠性和数据热度的可靠性优化方法

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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在磁盘故障的情况下利用数据恢复和重建操作来恢复数据。但是,这将导致更长的数据恢复时间并增加二次故障的可能性。因此,可靠性优化已成为存储系统研究的关键课题之一。在本文中,我们提出了一种新的可靠性优化方法,该方法使用磁盘可靠性度来评估基于SMART技术的磁盘可靠性。并且它使用数据热度来计算当前数据的热度和磁盘的利用率,因此根据磁盘的可靠性程度和磁盘的利用率,可以保护当前的热点数据。数据热度还根据当前的数据访问频率等级和类似Zipf的分布来预测未来的热点数据;我们还可以根据磁盘的可靠性程度来保护预测的新热点数据。我们的实验表明,磁盘可靠性可以满足实际使用情况,数据热度可以达到很高的预测精度。为了评估本方法对系统性能的影响,基于RAID系统的数据迁移实验结果表明,可靠性优化方法对正常系统性能的影响很小或没有影响,并且优于传统的重构RAID系统。

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