Resource management at the network edge for federated learning Article Swipe
Silvana Trindade
,
Luiz F. Bittencourt
,
Nelson L. S. da Fonseca
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1016/j.dcan.2022.10.015
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1016/j.dcan.2022.10.015
Federated learning has been explored as a promising solution for training machine learning models at the network edge, without sharing private user data. With limited resources at the edge, new solutions must be developed to leverage the software and hardware resources as the existing solutions did not focus on resource management for network edge, specially for federated learning. In this paper, we describe the recent work on resource management at the edge and explore the challenges and future directions to allow the execution of federated learning at the edge. Problems such as the discovery of resources, deployment, load balancing, migration, and energy efficiency are discussed in the paper.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.dcan.2022.10.015
- OA Status
- diamond
- Cited By
- 20
- References
- 122
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4307570299
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4307570299Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1016/j.dcan.2022.10.015Digital Object Identifier
- Title
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Resource management at the network edge for federated learningWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2022Year of publication
- Publication date
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2022-10-26Full publication date if available
- Authors
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Silvana Trindade, Luiz F. Bittencourt, Nelson L. S. da FonsecaList of authors in order
- Landing page
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https://doi.org/10.1016/j.dcan.2022.10.015Publisher landing page
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YesWhether a free full text is available
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diamondOpen access status per OpenAlex
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https://doi.org/10.1016/j.dcan.2022.10.015Direct OA link when available
- Concepts
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Computer science, Leverage (statistics), Software deployment, Edge device, Enhanced Data Rates for GSM Evolution, Edge computing, Focus (optics), Shared resource, Software, Distributed computing, Computer network, Software engineering, Artificial intelligence, Operating system, Cloud computing, Physics, OpticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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20Total citation count in OpenAlex
- Citations by year (recent)
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2025: 3, 2024: 10, 2023: 7Per-year citation counts (last 5 years)
- References (count)
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122Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| corresponding_author_ids | https://openalex.org/A5039387826 |
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