Update-Efficient Error-Correcting Product-Matrix Codes

TL;DR

This paper introduces new update-efficient error-correcting product-matrix regenerating codes for distributed storage, improving error correction, update complexity, and node access efficiency in MSR and MBR codes.

Contribution

It generalizes previous work by integrating Reed-Solomon codes into encoding matrices, optimizing update complexity and error correction capabilities.

Findings

MSR codes with minimal update complexity achieved

Enhanced error correction with fewer node accesses

New decoding schemes improve error correction for MBR codes

Abstract

Regenerating codes provide an efficient way to recover data at failed nodes in distributed storage systems. It has been shown that regenerating codes can be designed to minimize the per-node storage (called MSR) or minimize the communication overhead for regeneration (called MBR). In this work, we propose new encoding schemes for $[n,d]$ error-correcting MSR and MBR codes that generalize our earlier work on error-correcting regenerating codes. We show that by choosing a suitable diagonal matrix, any generator matrix of the $[n,\alpha]$ Reed-Solomon (RS) code can be integrated into the encoding matrix. Hence, MSR codes with the least update complexity can be found. By using the coefficients of generator polynomials of $[n,k]$ and $[n,d]$ RS codes, we present a least-update-complexity encoding scheme for MBR codes. A decoding scheme is proposed that utilizes the $[n,\alpha]$ RS code to perform data reconstruction for MSR codes. The proposed decoding scheme has better error correction capability and incurs the least number of node accesses when errors are present. A new decoding scheme is also proposed for MBR codes that can correct more error-patterns.