The MDS Queue: Analysing the Latency Performance of Erasure Codes

TL;DR

This paper analyzes the latency performance of MDS erasure codes in data storage systems using queueing theory, providing analytical bounds, scheduling policies, and validation through simulations.

Contribution

It introduces the MDS queue model to analytically study latency in erasure-coded storage, offering new scheduling policies and insights into degraded read methods.

Findings

Analytical bounds for MDS queue latency performance

Scheduling policies that tightly bound latency

Validation of theoretical results through extensive simulations

Abstract

In order to scale economically, data centers are increasingly evolving their data storage methods from the use of simple data replication to the use of more powerful erasure codes, which provide the same level of reliability as replication but at a significantly lower storage cost. In particular, it is well known that Maximum-Distance-Separable (MDS) codes, such as Reed-Solomon codes, provide the maximum storage efficiency. While the use of codes for providing improved reliability in archival storage systems, where the data is less frequently accessed (or so-called "cold data"), is well understood, the role of codes in the storage of more frequently accessed and active "hot data", where latency is the key metric, is less clear. In this paper, we study data storage systems based on MDS codes through the lens of queueing theory, and term this the "MDS queue." We analytically characterize the (average) latency performance of MDS queues, for which we present insightful scheduling policies that form upper and lower bounds to performance, and are observed to be quite tight. Extensive simulations are also provided and used to validate our theoretical analysis. We also employ the framework of the MDS queue to analyse different methods of performing so-called degraded reads (reading of partial data) in distributed data storage.