Optimal Construction of Regenerating Code through Rate-matching in Hostile Networks

TL;DR

This paper introduces two novel rate-matched regenerating code constructions for distributed storage systems in hostile networks, enhancing error detection, correction, and storage efficiency against adversaries.

Contribution

It proposes 2-layer and m-layer rate-matched regenerating codes that improve error correction and storage efficiency in adversarial environments.

Findings

Achieves optimal storage efficiency with 2-layer code.

Enhances error detection and correction over existing methods.

Maximizes storage capacity through parameter optimization.

Abstract

Regenerating code is a class of code very suitable for distributed storage systems, which can maintain optimal bandwidth and storage space. Two types of important regenerating code have been constructed: the minimum storage regeneration (MSR) code and the minimum bandwidth regeneration (MBR) code. However, in hostile networks where adversaries can compromise storage nodes, the storage capacity of the network can be significantly affected. In this paper, we propose two optimal constructions of regenerating codes through rate-matching that can combat against this kind of adversaries in hostile networks: 2-layer rate-matched regenerating code and $m$-layer rate-matched regenerating code. For the 2-layer code, we can achieve the optimal storage efficiency for given system requirements. Our comprehensive analysis shows that our code can detect and correct malicious nodes with higher storage efficiency compared to the universally resilient regenerating code which is a straightforward extension of regenerating code with error detection and correction capability. Then we propose the $m$-layer code by extending the 2-layer code and achieve the optimal error correction efficiency by matching the code rate of each layer's regenerating code. We also demonstrate that the optimized parameter can achieve the maximum storage capacity under the same constraint. Compared to the universally resilient regenerating code, our code can achieve much higher error correction efficiency.