Clustered Distributed Data Storage Repairing Multiple Failures

A clustered distributed storage system (DSS), also called a rack-aware storage system, is a distributed storage system in which the nodes are grouped into several clusters. The communication between two clusters may be restricted by their connectivity; that is to say, the communication cost between nodes differs depending on their location. As such, when repairing a failed node, downloading data from nodes that are in the same cluster is much cheaper and more efficient than downloading data from nodes in another cluster. In this article, we consider a scenario in which the failed nodes only download data from nodes in the same cluster, which is an extreme and important case that leverages the fact that the intra-cluster bandwidth is much cheaper than the cross-cluster repair bandwidth. Also, we study the problem of repairing multiple failures in this article, which allows for collaboration within the same cluster, i.e., failed nodes in the same cluster can exchange data with each other. We derive the trade-off between the storage and repair bandwidth for the clustered DSSs and provide explicit code constructions achieving two extreme points in the trade-off, namely the minimum storage clustered collaborative repair (MSCCR) point and the minimum bandwidth clustered collaborative repair (MBCCR) point, respectively.

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Publication Details

Journal
Entropy
Published
2025-03-17
DOI
https://doi.org/10.3390/e27030313
Primary Topic
Advanced Data Storage Technologies
Type
article
Field-Weighted Citation Impact
0.00

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article

Clustered Distributed Data Storage Repairing Multiple Failures

Qihui Wu, Shiqiu Liu, Fangwei Ye
Entropy
Advanced Data Storage Technologies
article

Clustered Distributed Data Storage Repairing Multiple Failures

Qihui Wu, Shiqiu Liu, Fangwei Ye
article en

Abstract

A clustered distributed storage system (DSS), also called a rack-aware storage system, is a distributed storage system in which the nodes are grouped into several clusters. The communication between two clusters may be restricted by their connectivity; that is to say, the communication cost between nodes differs depending on their location. As such, when repairing a failed node, downloading data from nodes that are in the same cluster is much cheaper and more efficient than downloading data from nodes in another cluster. In this article, we consider a scenario in which the failed nodes only download data from nodes in the same cluster, which is an extreme and important case that leverages the fact that the intra-cluster bandwidth is much cheaper than the cross-cluster repair bandwidth. Also, we study the problem of repairing multiple failures in this article, which allows for collaboration within the same cluster, i.e., failed nodes in the same cluster can exchange data with each other. We derive the trade-off between the storage and repair bandwidth for the clustered DSSs and provide explicit code constructions achieving two extreme points in the trade-off, namely the minimum storage clustered collaborative repair (MSCCR) point and the minimum bandwidth clustered collaborative repair (MBCCR) point, respectively.

EntropyVol. 27(3)
Peng Cheng Laboratory (CN), Ministry of Industry and Information Technology (CN), Nanjing University of Aeronautics and Astronautics (CN)
National Natural Science Foundation of China, Natural Science Foundation of Jiangsu Province
Partnerships for the goals
Openalex Percentile: Top 96%
Advanced Data Storage Technologies
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Clustered Distributed Data Storage Repairing Multiple Failures — Qihui Wu, Shiqiu Liu, et al. · Entropy (2025) | TGRS Research Map | TGRS