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A Self-Matching Sliding Block Algorithm Applied to Deduplication in Distributed Storage System

机译:应用于分布式存储系统中重复数据删除的自匹配滑块算法

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The deduplication technology can significantly reduce the amount of storage in data centers, thus to save network bandwidth and decrease the cost of construction and maintenance. Having inspired by the sliding block method of the Sliding Block (SB) algorithm and independent block-dividing thought of the Content Defined Chunking (CDC) algorithm, a Self-Matching Sliding Block (SMSB) algorithm for deduplication is proposed. Via communication with metadata node, the storage system client builds a matching table in local memory that contains fingerprint and checksum, based on the matching table to realize sliding block self-matching so as to detect the duplicate blocks. The experimental results show that the deduplication rate and the disk space utilization rate of SMSB algorithm is respectively 2.03 times and 1.28 times of the CDC algorithm and that the data processing speed is 0.83 times of the CDC algorithm. The SMSB algorithm is suitable for distributed storage system.
机译:重复数据删除技术可以显着降低数据中心的存储量,从而节省网络带宽并降低建筑和维护的成本。通过滑动块(SB)算法的滑块方法和独立块分割思想的启发,提出了一种用于重复数据删除的自匹配滑块(SMSB)算法。通过与元数据节点进行通信,存储系统客户端在本地存储器中构建包含指纹和校验和的本地内存中的匹配表,基于匹配表来实现滑块自匹配以检测重复块。实验结果表明,SMSB算法的重复数据删除率和磁盘空间利用率分别为CDC算法的2.03倍和1.28倍,数据处理速度为CDC算法的0.83倍。 SMSB算法适用于分布式存储系统。

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