LINEAR PROGRAMMING BOUNDS FOR DISTRIBUTED STORAGE CODES

Ali TEBBI, Terence CHAN, Chi Wan SUNG

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

3 Citations (Scopus)

Abstract

A major issue of locally repairable codes is their robustness. If a local repair group is not able to perform the repair process, this will result in increasing the repair cost. Therefore, it is critical for a locally repairable code to have multiple repair groups. In this paper we consider robust locally repairable coding schemes which guarantee that there exist multiple distinct (not necessarily disjoint) alternative local repair groups for any single failure such that the failed node can still be repaired locally even if some of the repair groups are not available. We use linear programming techniques to establish upper bounds on the size of these codes. We also provide two examples of robust locally repairable codes that are optimal regarding our linear programming bound. Furthermore, we address the update efficiency problem of the distributed data storage networks. Any modification on the stored data will result in updating the content of the storage nodes. Therefore, it is essential to minimise the number of nodes which need to be updated by any change in the stored data. We characterise the update-efficient storage code properties and establish the necessary conditions of existence update-efficient locally repairable storage codes.
Original languageEnglish
Pages (from-to)333-357
JournalAdvances in Mathematics of Communications
Volume14
Issue number2
Online publishedSept 2019
DOIs
Publication statusPublished - May 2020

Research Keywords

  • Distributed storage network
  • erasure code
  • linear programming
  • locally repairable code
  • update complexity

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