Progressive Decoding for Data Availability and Reliability in Distributed Networked Storage

TL;DR

This paper introduces a decentralized Reed Solomon coding scheme with progressive data retrieval that reduces communication and computation costs in distributed storage systems, especially under node failures.

Contribution

It presents a novel progressive decoding method that adapts to node failures, improves performance, and is flexible regardless of data generating node count.

Findings

Up to 35 times better computation performance for low Byzantine node rates.

Analytical and simulation validation of communication cost.

Flexible redundancy level independent of data generating nodes.

Abstract

To harness the ever growing capacity and decreasing cost of storage, providing an abstraction of dependable storage in the presence of crash-stop and Byzantine failures is compulsory. We propose a decentralized Reed Solomon coding mechanism with minimum communication overhead. Using a progressive data retrieval scheme, a data collector contacts only the necessary number of storage nodes needed to guarantee data integrity. The scheme gracefully adapts the cost of successful data retrieval to the number of storage node failures. Moreover, by leveraging the Welch-Berlekamp algorithm, it avoids unnecessary computations. Compared to the state-of-the-art decoding scheme, the implementation and evaluation results show that our progressive data retrieval scheme has up to 35 times better computation performance for low Byzantine node rates. Additionally, the communication cost in data retrieval is derived analytically and corroborated by Monte-Carlo simulation results. Our implementation is flexible in that the level of redundancy it provides is independent of the number of data generating nodes, a requirement for distributed storage systems