一种基于云存储系统的自适应数据碎片恢复优化方法

An Adaptive Defragmentation Restore Optimization Method Based on Cloud Storage System

  • 摘要: 针对基于重删后云存储系统中数据碎片引起恢复性能降低的问题,采用自适应碎片分组设计了一个云存储系统中重删后优化数据恢复的处理方法.该方法不使用固定大小的读窗口,根据数据块地址关联性分成可变大小的逻辑组,旨在选择有限数量的容器,为备份提供更多不同的引用块,减少所选容器中重复或未引用块的数量,减少磁盘访问,以精确识别和删除碎片数据,提升数据恢复性能以及重删率.实验结果表明,该方法在提高恢复性能的同时减少重写数据量.

     

    Abstract: To solve the problem of the recovery performance drop caused by data fragmentation in the deduplication-based cloud storage system,an adaptive fragmentation grouping was used to design a method for data recovery after deduplication in a cloud storage system.The approach was arranged not to use a fixed-size read window,to identify and delete the fragmentation,and to select a different reference chunk to minimize the number of containers.The number of referenced blocks could reduce disk access to accurately identify and remove fragmented data,improving data recovery performance and deduplication rates.The results show that,the approach can improve restore performance while reducing the amount of rewrite data.

     

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