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Content-Based Chunk Placement Scheme for Decentralized Deduplication on Distributed File Systems

机译:基于内容的分布式文件系统分散重复数据删除的基于内容的块放置方案

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The rapid growth of data size causes several problems such as storage limitation and increment of data management cost. In order to store and manage massive data, Distributed File System (DFS) is widely used. Furthermore, in order to reduce the volume of storage, data deduplication schemes are being extensively studied. The data deduplication increases the available storage capacity by eliminating duplicated data. However, deduplication process causes performance overhead such as disk I/O. In this paper, we propose a content-based chunk placement scheme to increase deduplication rate on the DFS. To avoid performance overhead caused by deduplication process, we use lessfs in each chunk server. With our design, our system performs decentralized deduplication process in each chunk server. Moreover, we use consistent hashing for chunk allocation and failure recovery. Our experimental results show that the proposed system reduces the storage space by 60% than the system without consistent hashing.
机译:数据大小的快速增长导致若干问题,例如存储限制和数据管理成本的增量。为了存储和管理大规模数据,广泛使用分布式文件系统(DFS)。此外,为了降低存储量,正在广泛研究数据重复数据删除方案。数据重复数据删除通过消除复制数据来增加可用的存储容量。但是,重复数据删除过程会导致性能开销,例如磁盘I / O.在本文中,我们提出了一种基于内容的块放置方案,以增加DFS上的重复数据删除速率。为避免由重复数据删除过程引起的性能开销,我们将在每个块服务器中使用小程序。通过我们的设计,我们的系统在每个块服务器中执行分散的重复数据删除过程。此外,我们使用一致的散列进行块分配和故障恢复。我们的实验结果表明,建议的系统将存储空间减少60%而不是系统而无一致散列。

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