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A multi-objective krill herd algorithm for virtual machine placement in cloud computing
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“The techniques include EAGLE algorithm [139], Imperialist competitive algorithm [140], Krill herd algorithm [141].”
From Energy efficiency in cloud computing data centers: a survey on software technologies (2023) · cites this paper as [141]
Citations
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Cited by
Sorted by citations
Energy efficiency in cloud computing data centers: a survey on software technologies
Katal, A., Dahiya, S., & Choudhury, T. (2023) · Cluster Computing · doi:10.1007/s10586-022-03713-0 · Cited by 516
“The techniques include EAGLE algorithm [139], Imperialist competitive algorithm [140], Krill herd algorithm [141].”
Method
Metadata
- Authors
- Baalamurugan, K. M., & Vijay Bhanu, S.
- Affiliations
- Annamalai University (IN)
- Corresponding author
- Baalamurugan, K. M.
- ORCID
- Baalamurugan, K. M.
- Venue
- The Journal of Supercomputing
- Published
- 2018-08-17
- Volume
- 76
- Issue
- 6
- Pages
- 4525-4542
- ISSN
- 0920-8542 (ISSN-L)
- 1573-0484
- OpenAlex
- W2887651464
- Cited by
- 26
- References
- 52
- Citations by year
- 2025: 4 · 2024: 2 · 2023: 4 · 2022: 4 · 2021: 6 · 2020: 4 · 2019: 2
- FWCI
- 4.63
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- The Journal of Supercomputing (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Cloud Computing and Resource Management
- Physical Sciences › Computer Science › Artificial Intelligence › Metaheuristic Optimization Algorithms Research
- Physical Sciences › Computer Science › Hardware and Architecture › Energy Efficiency in Computing
- Keywords
- virtual machine placement, cloud computing, krill herd algorithm, multi-objective optimization, power consumption, resource utilization, Pareto optimal solutions, metaheuristic optimization
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