A Load-Balanced Collaborative Repair Algorithm for Single-Disk Failures in Erasure Coded Storage Systems Article Swipe
Zhijie Huang
,
Y. Shi
,
Chengjia Zhao
,
Haoran Li
,
Nannan Zhao
,
Shujie Han
,
Xiao Zhang
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1145/3762648
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1145/3762648
In large-scale cloud data centers and distributed storage systems, erasure coding is usually employed to enhance data availability and storage efficiency. However, with the explosive growth of data volume and the continuous expansion of storage system scale, traditional erasure coding techniques face significant challenges in handling single-disk failures. These challenges are primarily reflected in low data recovery efficiency and imbalanced system load distribution, which ultimately result in excessive I/O load and network bandwidth consumption, severely limiting the overall performance of the system. To address these issues, this article proposes a load-balanced data repair algorithm for single disk failures in erasure coded storage systems, called MNCR (Multi-Node Cooperative Repair). This algorithm improves data recovery efficiency in single-disk failure scenarios by minimizing data reading and inter-disk data transmission, using a cooperative repair strategy among disks. In addition, the algorithm designs a dynamic load balancing mechanism, which effectively resolves the issue of imbalanced data load distribution among disks during the repair process, thus avoiding performance bottlenecks caused by overloaded disks. Experimental results show that the MNCR algorithm significantly outperforms traditional methods in terms of repair efficiency and load balancing, providing an effective solution for single disk failure recoveries in erasure coding based large-scale storage systems.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1145/3762648
- https://dl.acm.org/doi/pdf/10.1145/3762648
- OA Status
- bronze
- References
- 23
- Related Works
- 10
- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4413499141Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1145/3762648Digital Object Identifier
- Title
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A Load-Balanced Collaborative Repair Algorithm for Single-Disk Failures in Erasure Coded Storage SystemsWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-08-25Full publication date if available
- Authors
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Zhijie Huang, Y. Shi, Chengjia Zhao, Haoran Li, Nannan Zhao, Shujie Han, Xiao ZhangList of authors in order
- Landing page
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https://doi.org/10.1145/3762648Publisher landing page
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https://dl.acm.org/doi/pdf/10.1145/3762648Direct link to full text PDF
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YesWhether a free full text is available
- OA status
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bronzeOpen access status per OpenAlex
- OA URL
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https://dl.acm.org/doi/pdf/10.1145/3762648Direct OA link when available
- Concepts
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Erasure, Computer science, Erasure code, Distributed computing, Algorithm, Parallel computing, Decoding methods, Programming languageTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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23Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.that | 170 |
| abstract_inverted_index.this | 86 |
| abstract_inverted_index.thus | 159 |
| abstract_inverted_index.with | 22 |
| abstract_inverted_index.These | 48 |
| abstract_inverted_index.among | 131, 153 |
| abstract_inverted_index.based | 198 |
| abstract_inverted_index.cloud | 2 |
| abstract_inverted_index.coded | 100 |
| abstract_inverted_index.disks | 154 |
| abstract_inverted_index.issue | 147 |
| abstract_inverted_index.terms | 179 |
| abstract_inverted_index.these | 84 |
| abstract_inverted_index.using | 126 |
| abstract_inverted_index.which | 63, 143 |
| abstract_inverted_index.called | 103 |
| abstract_inverted_index.caused | 163 |
| abstract_inverted_index.coding | 10, 39, 197 |
| abstract_inverted_index.disks. | 132, 166 |
| abstract_inverted_index.during | 155 |
| abstract_inverted_index.growth | 25 |
| abstract_inverted_index.repair | 92, 129, 157, 181 |
| abstract_inverted_index.result | 65 |
| abstract_inverted_index.scale, | 36 |
| abstract_inverted_index.single | 95, 191 |
| abstract_inverted_index.system | 35, 60 |
| abstract_inverted_index.volume | 28 |
| abstract_inverted_index.address | 83 |
| abstract_inverted_index.article | 87 |
| abstract_inverted_index.centers | 4 |
| abstract_inverted_index.designs | 137 |
| abstract_inverted_index.dynamic | 139 |
| abstract_inverted_index.enhance | 15 |
| abstract_inverted_index.erasure | 9, 38, 99, 196 |
| abstract_inverted_index.failure | 116, 193 |
| abstract_inverted_index.issues, | 85 |
| abstract_inverted_index.methods | 177 |
| abstract_inverted_index.network | 71 |
| abstract_inverted_index.overall | 77 |
| abstract_inverted_index.reading | 121 |
| abstract_inverted_index.results | 168 |
| abstract_inverted_index.storage | 7, 19, 34, 101, 200 |
| abstract_inverted_index.system. | 81 |
| abstract_inverted_index.usually | 12 |
| abstract_inverted_index.However, | 21 |
| abstract_inverted_index.Repair). | 107 |
| abstract_inverted_index.avoiding | 160 |
| abstract_inverted_index.employed | 13 |
| abstract_inverted_index.failures | 97 |
| abstract_inverted_index.handling | 45 |
| abstract_inverted_index.improves | 110 |
| abstract_inverted_index.limiting | 75 |
| abstract_inverted_index.process, | 158 |
| abstract_inverted_index.proposes | 88 |
| abstract_inverted_index.recovery | 56, 112 |
| abstract_inverted_index.resolves | 145 |
| abstract_inverted_index.severely | 74 |
| abstract_inverted_index.solution | 189 |
| abstract_inverted_index.strategy | 130 |
| abstract_inverted_index.systems, | 8, 102 |
| abstract_inverted_index.systems. | 201 |
| abstract_inverted_index.addition, | 134 |
| abstract_inverted_index.algorithm | 93, 109, 136, 173 |
| abstract_inverted_index.balancing | 141 |
| abstract_inverted_index.bandwidth | 72 |
| abstract_inverted_index.effective | 188 |
| abstract_inverted_index.excessive | 67 |
| abstract_inverted_index.expansion | 32 |
| abstract_inverted_index.explosive | 24 |
| abstract_inverted_index.failures. | 47 |
| abstract_inverted_index.primarily | 51 |
| abstract_inverted_index.providing | 186 |
| abstract_inverted_index.reflected | 52 |
| abstract_inverted_index.scenarios | 117 |
| abstract_inverted_index.balancing, | 185 |
| abstract_inverted_index.challenges | 43, 49 |
| abstract_inverted_index.continuous | 31 |
| abstract_inverted_index.efficiency | 57, 113, 182 |
| abstract_inverted_index.imbalanced | 59, 149 |
| abstract_inverted_index.inter-disk | 123 |
| abstract_inverted_index.mechanism, | 142 |
| abstract_inverted_index.minimizing | 119 |
| abstract_inverted_index.overloaded | 165 |
| abstract_inverted_index.recoveries | 194 |
| abstract_inverted_index.techniques | 40 |
| abstract_inverted_index.ultimately | 64 |
| abstract_inverted_index.(Multi-Node | 105 |
| abstract_inverted_index.Cooperative | 106 |
| abstract_inverted_index.bottlenecks | 162 |
| abstract_inverted_index.cooperative | 128 |
| abstract_inverted_index.distributed | 6 |
| abstract_inverted_index.effectively | 144 |
| abstract_inverted_index.efficiency. | 20 |
| abstract_inverted_index.large-scale | 1, 199 |
| abstract_inverted_index.outperforms | 175 |
| abstract_inverted_index.performance | 78, 161 |
| abstract_inverted_index.significant | 42 |
| abstract_inverted_index.single-disk | 46, 115 |
| abstract_inverted_index.traditional | 37, 176 |
| abstract_inverted_index.Experimental | 167 |
| abstract_inverted_index.availability | 17 |
| abstract_inverted_index.consumption, | 73 |
| abstract_inverted_index.distribution | 152 |
| abstract_inverted_index.distribution, | 62 |
| abstract_inverted_index.load-balanced | 90 |
| abstract_inverted_index.significantly | 174 |
| abstract_inverted_index.transmission, | 125 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 7 |
| citation_normalized_percentile.value | 0.43195481 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |