On the Duality and File Size Hierarchy of Fractional Repetition Codes

TL;DR

This paper explores the duality and file size hierarchy of fractional repetition codes in distributed storage, providing new bounds, optimal constructions from t-designs, and a tensor product technique for code combination.

Contribution

It introduces a duality analysis for FR codes, derives an improved file size bound, and presents a tensor product method for constructing codes with hierarchical properties.

Findings

Derived an improved dual bound on supported file size.

FR codes from t-designs are optimal for large files.

Presented a tensor product technique for code combination.

Abstract

Distributed storage systems that deploy erasure codes can provide better features such as lower storage overhead and higher data reliability. In this paper, we focus on fractional repetition (FR) codes, which are a class of storage codes characterized by the features of uncoded exact repair and minimum repair bandwidth. We study the duality of FR codes, and investigate the relationship between the supported file size of an FR code and its dual code. Based on the established relationship, we derive an improved dual bound on the supported file size of FR codes. We further show that FR codes constructed from $t$-designs are optimal when the size of the stored file is sufficiently large. Moreover, we present the tensor product technique for combining FR codes, and elaborate on the file size hierarchy of resulting codes.