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Adaptive overlapped declustering: a highly available data-placement method balancing access load and space utilization

机译：自适应重叠聚类：一种高可用性的数据放置方法，平衡访问负载和空间利用率

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摘要

This paper proposes a new data-placement method named adaptive overlapped declustering, which can be applied to a parallel storage system using a value range partitioning-based distributed directory and primary-backup data replication, to improve the space utilization by balancing their access loads. The proposed method reduces data skews generated by data migration for balancing access load. While some data-placement methods capable of balancing access load or reducing data skew have been proposed, both requirements satisfied simultaneously. The proposed method also improves the reliability and availability of the system because it reduces recovery time for damaged backups after a disk failure. The method achieves this acceleration by reducing a large amount of network communications and disk I/O. Mathematical analysis shows the efficiency of space utilization under skewed access workloads. Queuing simulations demonstrated that the proposed method halves backup restoration time, compared with the traditional chained declustering method.
机译：本文提出了一种新的数据放置方法，称为自适应重叠分簇，该方法可以应用于基于值范围分区的分布式目录和主备份数据复制的并行存储系统，以通过平衡访问负载来提高空间利用率。所提出的方法减少了由数据迁移产生的数据偏斜，以平衡访问负载。虽然已经提出了一些能够平衡访问负载或减少数据偏斜的数据放置方法，但同时满足了这两个要求。所提出的方法还提高了系统的可靠性和可用性，因为它减少了磁盘故障后损坏的备份的恢复时间。该方法通过减少大量的网络通信和磁盘I / O来实现这种加速。数学分析显示了在倾斜访问工作负载下空间利用的效率。排队模拟表明，与传统的链式分簇聚类方法相比，该方法可将备份恢复时间缩短一半。

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