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arXiv 1001.0107cs.ITmath.IT
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基于干涉对齐的分布式存储修复精确再生码

Exact Regeneration Codes for Distributed Storage Repair Using Interference Alignment

Changho Suh, Kannan Ramchandran

摘要:

(n,k)最大距离可分离(MDS)纠删码的高修复代价最近促使一类新的码(称为再生码)以最佳方式权衡存储代价和修复带宽。在再生码频谱的一端是最小存储再生(MSR)码,其可以匹配MDS码的最小存储成本,同时还显著降低修复带宽。在本文中,我们描述了精确MSR码,它允许任何失败的节点(无论是系统或奇偶校验节点)被重新生成,而不仅仅是功能或信息等价。我们表明,精确MSR码来没有损失的最优性相对于随机网络编码的MSR码(匹配基于割集的修复带宽的下限)的情况下:(a)k/n <= 1/2;和(b)k <= 3。我们的建设性的方法是基于干扰对齐技术,并且,与前一类的随机网络编码为基础的方法,我们提供明确的和确定性的编码方案,需要一个有限的字段大小最多为2(n-k)。

英文摘要:

The high repair cost of (n,k) Maximum Distance Separable (MDS) erasure codes has recently motivated a new class of codes, called Regenerating Codes, that optimally trade off storage cost for repair bandwidth. On one end of this spectrum of Regenerating Codes are Minimum Storage Regenerating (MSR) codes that can match the minimum storage cost of MDS codes while also significantly reducing repair bandwidth. In this paper, we describe Exact-MSR codes which allow for any failed nodes (whether they are systematic or parity nodes) to be regenerated exactly rather than only functionally or information-equivalently. We show that Exact-MSR codes come with no loss of optimality with respect to random-network-coding based MSR codes (matching the cutset-based lower bound on repair bandwidth) for the cases of: (a) k/n <= 1/2; and (b) k <= 3. Our constructive approach is based on interference alignment techniques, and, unlike the previous class of random-network-coding based approaches, we provide explicit and deterministic coding schemes that require a finite-field size of at most 2(n-k).

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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