Optimal Construction of Regenerating Code Through Rate-Matching in Hostile Networks

Abstract

Regenerating code is a class of distributed storage codes that can optimally trade the bandwidth required to repair a failed node with the amount of data stored per node. There are two optimal points in the regeneration tradeoff curve: the minimum storage regeneration code and the minimum bandwidth regeneration code. However, in hostile networks where the storage nodes may be compromised, the storage capacity of the network can be significantly affected. In this paper, we propose two optimal regenerating code constructions through rate-matching to combat this kind of adversarial attacks in hostile networks. We first develop a two-layer rate-matched regenerating code construction. By matching the parameters of the full rate code and the partial rate code, we can optimize the overall storage efficiency while maintaining the corrupted node detection probability. Through comprehensive analysis, we show that the two-layer rate-matched regenerating code can achieve 70% higher storage efficiency than the universally resilient regenerating code. We then propose an optimal $m$ -layer regenerating code construction. While the principle remains the same as the two-layer code, it is designed to optimize the total number of detectable corrupted nodes of $m$ layers from which the errors can be corrected under the constraint of any given code efficiency. Compared with the universally resilient regenerating code with the same rate, our $m$ -layer code can detect 50% more corrupted nodes.