Multilevel error-control codes for data storage channels

Abdel-Ghaffar, Khaled; Hassner, M.

doi:10.1109/18.79944

Cited by 19 publications

(19 citation statements)

References 7 publications

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“…In general, an II code is not an optimal LRC code since its minimum distance does not achieve the bound given by (1). However, we will see that in some cases the minimum distance is not the crucial parameter in the performance of LRC codes, but the average number of erasures to data loss.…”

Section: Reading the Symbols Ofmentioning

confidence: 87%

Integrated interleaved codes as locally recoverable codes: properties and performance

Blaum

Hetzler

2016

IJICOT

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Considerable interest has been paid in recent literature to codes combining local and global properties for erasure correction. Applications are in cloud type of implementations, in which fast recovery of a failed storage device is important, but additional protection is required in order to avoid data loss, and in RAID type of architectures, in which total device failures coexist with silent failures at the page or sector level in each device. Existing solutions to these problems require in general relatively large finite fields. The techniques of integrated interleaved codes (which are closely related to generalised concatenated codes) are proposed to reduce significantly the size of the finite field, and it is shown that when the parameters of these codes are judiciously chosen, they outperform codes optimising the minimum distance with respect to the average number of erasures that the code can correct.

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Section: Reading the Symbols Ofmentioning

confidence: 87%

Integrated interleaved codes as locally recoverable codes: properties and performance

Blaum

Hetzler

2016

IJICOT

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“…The first step to retrieve the erased entries consists of computing the rm+s syndromes. Using the parity-check matrix H(m, n, r, s; f (x)) given by (1), the syndromes are…”

Section: Code Constructionmentioning

confidence: 99%

“…In this section, we assume that r = 1, thus, the parity-check matrix H(m, n, 1, s) given by (1) can be written as…”

Section: The Case R =mentioning

confidence: 99%

“…Comparing Tables 3 and 4, we can see that for values of p, m and n for which C (1) (m, n, 1, 3; M p (x)) is PMDS, also C(m, n, 1, 3; M p (x)) is PMDS. However, for p = 23, C(3, 7, 1, 3; M p (x)) is PMDS but C (1) (3, 7, 1, 3; M p (x)) is not, for p = 41, C(5, 8, 1, 3; M p (x)) is PMDS but C (1) (5, 8, 1, 3; M p (x)) is not, and for p = 113, C(3, 7, 10, 11; M p (x)), C(3, 7, 11, 10; M p (x)) and C (3, 7, 12, 9; M p (x)) are PMDS but C (1) (3, 7, 10, 11; M p (x)), C (1) (3, 7, 11, 10; M p (x)) and C (1) (3, 7, 12, 9; M p (x)) are not.…”

Section: The Case Cmentioning

confidence: 99%

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Partial-MDS Codes and Their Application to RAID Type of Architectures

Blaum

Hafner

Hetzler

2013

IEEE Trans. Inform. Theory

157

221

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A family of codes with a natural two-dimensional structure is presented, inspired by an application of RAID type of architectures whose units are solid state drives (SSDs). Arrays of SSDs behave differently to arrays of hard disk drives (HDDs), since hard errors in sectors are common and traditional RAID approaches (like RAID 5 or RAID 6) may be either insufficient or excessive. An efficient solution to this problem is given by the new codes presented, called partial-MDS (PMDS) codes.

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“…We say that a block error happens if one or several small squares in a column of the array are altered. 1 In our setting, we think of the symbol errors and block errors as being caused by two different mechanisms. In this model, an observer cannot distinguish a block error from one or multiple symbol errors in the same column.…”

Section: Introductionmentioning

confidence: 99%

Coding for combined block-symbol error correction

Roth

Vontobel

2013

2013 IEEE International Symposium on Information Theory

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We design low-complexity error correction coding schemes for channels that introduce different types of errors and erasures: on the one hand, the proposed schemes can successfully deal with symbol errors and erasures, and, on the other hand, they can also successfully handle phased burst errors and erasures.Index Terms-Decoding, generalized Reed-Solomon (GRS) code, Feng-Tzeng algorithm, phased burst erasure, phased burst error, symbol erasure, symbol error.

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Multilevel error-control codes for data storage channels

Cited by 19 publications

References 7 publications

Integrated interleaved codes as locally recoverable codes: properties and performance

Integrated interleaved codes as locally recoverable codes: properties and performance

Partial-MDS Codes and Their Application to RAID Type of Architectures

Coding for combined block-symbol error correction

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