A Server Placement Algorithm for Reducing Risk and Improving Power Utilization in Data Centers Article Swipe
Rui Chen
,
Huikang Huang
,
Xiaoxuan Luo
,
Weiwei Lin
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.26599/tst.2023.9010009
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.26599/tst.2023.9010009
As the power demand in data centers is increasing, the power capacity of the power supply system has become an essential resource to be optimized. Although many data centers use power oversubscription to make full use of the power capacity, there are unavoidable power supply risks associated with it. Therefore, how to improve the data center power capacity utilization while ensuring power supply security has become an important issue. To solve this problem, we first define it and propose a risk evaluation metric called Weighted Power Supply Risk (WPSRisk). Then, a method, named Hybrid Genetic Algorithm with Ant Colony System (HGAACS), is proposed to improve power capacity utilization and reduce power supply risks by optimizing the server placement in the power supply system. HGAACS uses historical power data of each server to find a better placement solution by population iteration. HGAACS possesses not only the remarkable local search ability of Ant Colony System (ACS), but also enhances the global search capability by incorporating genetic operators from Genetic Algorithm (GA). To verify the performance of HGAACS, we experimentally compare it with five other placement algorithms. The experimental results show that HGAACS can perform better than other algorithms in both improving power utilization and reducing the risk of power supply system.
Related Topics
Concepts
Genetic algorithm
Computer science
Power (physics)
Data center
Reliability engineering
Metric (unit)
Population
Ant colony optimization algorithms
Mathematical optimization
Engineering
Algorithm
Computer network
Operations management
Mathematics
Machine learning
Physics
Quantum mechanics
Sociology
Demography
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.26599/tst.2023.9010009
- https://ieeexplore.ieee.org/ielx7/5971803/10225032/10225278.pdf
- OA Status
- diamond
- Cited By
- 1
- References
- 35
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4386041564
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4386041564Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.26599/tst.2023.9010009Digital Object Identifier
- Title
-
A Server Placement Algorithm for Reducing Risk and Improving Power Utilization in Data CentersWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-08-21Full publication date if available
- Authors
-
Rui Chen, Huikang Huang, Xiaoxuan Luo, Weiwei LinList of authors in order
- Landing page
-
https://doi.org/10.26599/tst.2023.9010009Publisher landing page
- PDF URL
-
https://ieeexplore.ieee.org/ielx7/5971803/10225032/10225278.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
-
https://ieeexplore.ieee.org/ielx7/5971803/10225032/10225278.pdfDirect OA link when available
- Concepts
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Genetic algorithm, Computer science, Power (physics), Data center, Reliability engineering, Metric (unit), Population, Ant colony optimization algorithms, Mathematical optimization, Engineering, Algorithm, Computer network, Operations management, Mathematics, Machine learning, Physics, Quantum mechanics, Sociology, DemographyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1Per-year citation counts (last 5 years)
- References (count)
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35Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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