2017Unpublished venueRequires access

Low bandwidth repair of the RS(10,4) Reed-Solomon code

Iwan Duursma, Son Hoang Dau

Open publisher page 35 citations

Abstract

As an alternative to replication of data blocks, the Hadoop Distributed File System offers the possibility of erasure coding using Reed-Solomon codes. The use of Reed-Solomon codes significantly reduces storage overhead but has more expensive failure recovery. Using the shortened Reed-Solomon code RS(10,4), with 10 data symbols and 4 check symbols, standard erasure repair requires downloading 10 symbols or 80 bits. Known schemes attain a reduced repair bandwidth of 65 or 64 bits. In this paper we present three repair schemes with bandwidth 60, 56 and 54, respectively.

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What this paper is about

As an alternative to replication of data blocks, the Hadoop Distributed File System offers the possibility of erasure coding using Reed-Solomon codes. The use of Reed-Solomon codes significantly reduces storage overhead but has more expensive failure recovery. Using the shortened Reed-Solomon code RS(10,4), with 10 data symbols and 4 check symbols, standard erasure repair requires downloading 10 symbols or 80 bits. Known schemes attain a reduced repair bandwidth of 65 or 64 bits. In this paper we present three repair schemes with bandwidth 60, 56 and 54, respectively.

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Available abstract

As an alternative to replication of data blocks, the Hadoop Distributed File System offers the possibility of erasure coding using Reed-Solomon codes. The use of Reed-Solomon codes significantly reduces storage overhead but has more expensive failure recovery. Using the shortened Reed-Solomon code RS(10,4), with 10 data symbols and 4 check symbols, standard erasure repair requires downloading 10 symbols or 80 bits. Known schemes attain a reduced repair bandwidth of 65 or 64 bits. In this paper we present three repair schemes with bandwidth 60, 56 and 54, respectively.

Key concepts: Reed–Solomon error correction, Erasure code, Computer science, Bandwidth (computing), Erasure, Distributed data store, Error detection and correction, Overhead (engineering)

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