Accelerating Data Access for Single Node in Distributed Storage Systems via MDS Codes

TL;DR

This paper introduces two algorithms that significantly reduce single-node data access latency in distributed storage systems using MDS codes, with theoretical guarantees and simulation validation.

Contribution

The paper proposes novel algorithms for faster single-node data access in MDS-coded storage, providing theoretical analysis and empirical validation.

Findings

Expected reduction ratios of rac{(n-k)(n-k+1)}{n(n+1)} and rac{n-k}{n} for different distributions.

Over 60% latency reduction in worst-case scenarios with specific parameters.

Simulation results show lower data access latency compared to baseline algorithms.

Abstract

Maximum distance separable (MDS) array codes are widely employed in modern distributed storage systems to provide high data reliability with small storage overhead. Compared with the data access latency of the entire file, the data access latency of a single node in a distributed storage system is equally important. In this paper, we propose two algorithms to effectively reduce the data access latency on a single node in different scenarios for MDS codes. We show theoretically that our algorithms have an expected reduction ratio of $\frac{(n-k)(n-k+1)}{n(n+1)}$ and $\frac{n-k}{n}$ for the data access latency of a single node when it obeys uniform distribution and shifted-exponential distribution, respectively, where $n$ and $k$ are the numbers of all nodes and the number of data nodes respectively. In the worst-case analysis, we show that our algorithms have a reduction ratio of more than $60\%$ when $(n,k)=(3,2)$. Furthermore, in simulation experiments, we use the Monte Carlo simulation algorithm to demonstrate less data access latency compared with the baseline algorithm.