Regenerating Codes: A System Perspective

TL;DR

This paper analyzes regenerating codes from a system perspective, examining parameter impacts and computational costs to aid practitioners in optimizing their use in cloud storage systems.

Contribution

It provides a system-level analysis of regenerating codes and compares implementation efficiencies, aiding practical parameter selection and system design.

Findings

System-level impact of code parameters analyzed

Comparison of computational costs for different code implementations

Guidelines for choosing optimal regenerating code parameters

Abstract

The explosion of the amount of data stored in cloud systems calls for more efficient paradigms for redundancy. While replication is widely used to ensure data availability, erasure correcting codes provide a much better trade-off between storage and availability. Regenerating codes are good candidates for they also offer low repair costs in term of network bandwidth. While they have been proven optimal, they are difficult to understand and parameterize. In this paper we provide an analysis of regenerating codes for practitioners to grasp the various trade-offs. More specifically we make two contributions: (i) we study the impact of the parameters by conducting an analysis at the level of the system, rather than at the level of a single device; (ii) we compare the computational costs of various implementations of codes and highlight the most efficient ones. Our goal is to provide system designers with concrete information to help them choose the best parameters and design for regenerating codes.