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arXiv 0906.4913cs.ITmath.IT
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分布式存储最优精确再生码的显式构造

Explicit Construction of Optimal Exact Regenerating Codes for Distributed Storage

K. V. Rashmi, Nihar B. Shah, P. Vijay Kumar, Kannan Ramchandran

摘要:

擦除编码技术用于提高分布式存储系统的可靠性,同时最小化存储开销。同样令人感兴趣的是最小化节点故障后修复系统所需的带宽。在最近的一篇论文中,Wu等人描述了修复带宽和每个节点存储的数据量之间的权衡。他们还证明了再生代码的存在,实现了这种权衡。在本文中,我们介绍了精确再生码,这是再生码具有额外的属性,能够复制存储在一个失败的节点的数据。这种代码需要低的处理和通信开销,使系统实用且易于维护。明确建设的确切再生代码提供的最小带宽点的存储修复带宽的权衡,相关的分布式邮件服务器的应用程序。一个子空间为基础的方法,并示出产生的必要条件和充分条件的线性代码具有确切的再生性能,以及证明我们的建设的唯一性。还包括在该文件中,是一个明确的建设再生代码的最小存储点的参数相关的存储在对等系统。这种结构支持可变数量的节点,并且可以处理多个同时发生的节点故障。文中给出的所有结构都是低复杂度的,特别是需要低的域大小。

英文摘要:

Erasure coding techniques are used to increase the reliability of distributed storage systems while minimizing storage overhead. Also of interest is minimization of the bandwidth required to repair the system following a node failure. In a recent paper, Wu et al. characterize the tradeoff between the repair bandwidth and the amount of data stored per node. They also prove the existence of regenerating codes that achieve this tradeoff. In this paper, we introduce Exact Regenerating Codes, which are regenerating codes possessing the additional property of being able to duplicate the data stored at a failed node. Such codes require low processing and communication overheads, making the system practical and easy to maintain. Explicit construction of exact regenerating codes is provided for the minimum bandwidth point on the storage-repair bandwidth tradeoff, relevant to distributed-mail-server applications. A subspace based approach is provided and shown to yield necessary and sufficient conditions on a linear code to possess the exact regeneration property as well as prove the uniqueness of our construction. Also included in the paper, is an explicit construction of regenerating codes for the minimum storage point for parameters relevant to storage in peer-to-peer systems. This construction supports a variable number of nodes and can handle multiple, simultaneous node failures. All constructions given in the paper are of low complexity, requiring low field size in particular.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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