Error-Correcting Regenerating and Locally Repairable Codes via Rank-Metric Codes

Natalia Silberstein, Ankit Singh Rawat, Sriram Vishwanath

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

Abstract

This paper presents and analyzes a novel concatenated coding scheme for enabling error resilience in two distributed storage settings: one being storage using existing regenerating codes and the second being storage using locally repairable codes. The concatenated coding scheme brings together a maximum rank distance code as an outer code and either a globally regenerating or a locally repairable code as an inner code. In addition, error resilience for combination of locally repairable codes with regenerating codes is considered. This concatenated coding system is designed to handle two different types of adversarial errors: the first type includes an adversary that can replace the content of an affected node only once; while the second type studies an adversary that is capable of polluting data an unbounded number of times. The paper establishes an upper bound on the resilience capacity for a locally repairable code. This paper also proves that the proposed concatenated coding approach attains the upper bound on the resilience capacity in the presence of the first type of adversary for both minimum storage regenerating codes and locally repairable codes. Further, this paper presents mechanisms that combine the presented concatenated coding scheme with subspace signatures to achieve error resilience for the second type of errors.

Original languageEnglish
Article number7273884
Pages (from-to)5765-5778
Number of pages14
JournalIEEE Transactions on Information Theory
Volume61
Issue number11
DOIs
StatePublished - 1 Nov 2015
Externally publishedYes

Keywords

  • Coding for distributed storage systems
  • error correcting codes
  • locally repairable codes
  • rank-metric codes
  • regenerating codes

ASJC Scopus subject areas

  • Information Systems
  • Computer Science Applications
  • Library and Information Sciences

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