The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Dynamic VMs placement for energy efficiency by PSO in cloud computing
Abstract
Recently, cloud computing is growing fast and helps to realise other high technologies. In this paper, we propose a hieratical architecture to satisfy both providers' and consumers' requirements in these technologies. We design a new service in the PaaS layer for scheduling consumer tasks. In the providers' perspective, incompatibility between specification of physical machine and user requests in cloud leads to problems such as energy-performance trade-off and large power consumption so that profits are decreased. To guarantee Quality of service of users' tasks, and reduce energy efficiency, we proposed to modify Particle Swarm Optimisation to reallocate migrated virtual machines in the overloaded host. We also dynamically consolidate the under-loaded host which provides power saving. Simulation results in CloudSim demonstrated that whatever simulation condition is near to the real environment, our method is able to save as much as 14% more energy and the number of migrations and simulation time significantly reduces compared with the previous works.
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Citations
Cites
Towards energy-aware scheduling in data centers using machine learning
Berral, J. L., Goiri, Í., Nou, R., Julià, F., Guitart, J., Gavaldà, R., & Torres, J. (2010) · Proceedings of the 1st International Conference on Energy-Efficient Computing and Networking · doi:10.1145/1791314.1791349 · Cited by 262 · cited 1×
“Additionally, others such as Berral et al. (2010) and Buyya, B, & Abawajy (2010) have proposed to extend these mechanisms with enhanced migration and server activation policies to reduce Service Level Agreement (SLA) violations.”
Background
Cited by
Elhoseny, M., Abdelaziz, A., Salama, A. S., Riad, A. M., Muhammad, K., & Sangaiah, A. K. (2018) · Future Generation Computer Systems · doi:10.1016/j.future.2018.03.005 · Cited by 341
Metadata
- Authors
- Dashti, S. E., & Rahmani, A. M.
- Venue
- Journal of Experimental & Theoretical Artificial Intelligence
- Publisher
- Informa UK Limited
- Published
- 2015-04-07
- Volume
- 28
- Issue
- 1-2
- Pages
- 97-112
- ISSN
- 0952-813X (ISSN-L)
- 1362-3079
- OpenAlex
- W2064288903
- Cited by
- 161
- References
- 1
- FWCI
- 36.04
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Dynamic VMs placement for energy efficiency by PSO in cloud computing. https://app.cochat.ai/papers/10.1080/0952813x.2015.1020519
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- Dashti, S. E., & Rahmani, A. M. (2016). Dynamic VMs placement for energy efficiency by PSO in cloud computing. Journal of Experimental & Theoretical Artificial Intelligence. https://doi.org/10.1080/0952813x.2015.1020519
Data sources
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.