用扩展行对角奇偶校验修复三重数据擦除

Xiaohe Liu
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引用次数: 0

摘要

随着大数据时代的到来,近年来存储的数据量呈指数级增长。在这样一个时代,数据存储安全成为一个重大挑战。随着数据量的增加,在存储过程中不可避免地会出现多次数据擦除。人们对双容错纠错码方法进行了大量的研究。偶数码、RDP (Row Diagonal Parity)码和HDP (Horizontal-Diagonal Parity)码可以实现双容错数据分布。这些自校正码允许最多两部分的源代码被擦除和被擦除的部分被恢复。然而,在许多情况下,固定两个数字是不够的。本文的重点是扩展行对角奇偶校验(E-RDP)来处理三次或更多的数据擦除。该数据结构可以有效地恢复基于RDP的三次擦除,继承了RDP的优点。本文详细阐述了E-RDP的编码过程,给出了一种直观的解码方法,最后讨论了E-RDP的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Repairing Triple Data Erasure with Extending Row Diagonal Parity
With the advent of the Big Data era, the amount of data stored has increased exponentially in recent years. In such an era, data storage security has become a significant challenge. As the volume of data increases, many data erasures during storage are inevitable. There has been a lot of research into dual fault-tolerant error correction code methods. EVENODD codes, Row Diagonal Parity (RDP) codes, and Horizontal-Diagonal Parity (HDP) codes can implement dual fault-tolerant data distribution. These self-correction codes allow up to two parts of the source code to be erased and the erased parts to be recovered. However, in many cases, it is not enough to fix two figures. This paper focuses on Extending Row Diagonal Parity (E-RDP) to cope with three or more data erasures. This data structure can efficiently recover three erasures based on RDP, which inherits the advantages of RDP. This article will explain the encoding process of E-RDP in detail, show an intuitive decoding method, and discuss the performance of E-RDP at the end.
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