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A metaheuristic virtual machine placement framework toward power efficiency of sustainable cloud environment

Soft Computing volume 27, pages 3817–3828 (2023)Cite this article

Abstract

The primary aim of Virtual Machine Placement (VMP) is the mapping of Virtual Machines (VMs) to Physical Machines (PMs), such that the PMs may be utilized to their maximum efficiency, where the already active VMs are not to be interrupted. It provides a list of live VM migrations that must be accomplished to get the optimum solution and reduces energy consumption significantly. The inefficient VMP leads to wastage of resources and excessive energy consumption and increases the overall operational cost of the data center. A Metaheuristic Virtual Machine Placement Framework towards the Power Efficiency of Sustainable Cloud Environment (MV-PESC) approach is suggested to address the issues mentioned above. An Extended Flower Pollination Optimization algorithm is suggested, which combines the concept of the Random Fit algorithm and the Flower Pollination Optimization algorithm. The proposed work’s performance is evaluated using actual workload traces of the benchmark Google Cluster Data set. The obtained results are compared with various state-of-the-art and demonstrate a notable reduction in power consumption, the number of active PMs, and execution time up to 64.89%, 35%, and 21.12%, respectively.

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Data Availability

The data are available upon reasonable request to the corresponding authors.

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Acknowledgements

The authors would like to thank the National Institute of Technology, Kurukshetra, India, for financially supporting this research work.

Funding

Funding was provided by National Institute of Technology Kurukshetra.

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Authors and Affiliations

  1. Department of Computer Applications, National Institute of Technology, Kurukshetra, Haryana, 136119, India

    Ashutosh Kumar Singh & Smruti Rekha Swain

  2. Department of Computer Science and Engineering, National Sun Yat-sen University, Kaohsiung, 804201, Taiwan

    Chung Nan Lee

Authors
  1. Ashutosh Kumar Singh
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  2. Smruti Rekha Swain
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  3. Chung Nan Lee
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Contributions

All the authors have discussed and constructed the ideas, designed the Virtual Machine Placement framework, and wrote the paper together.

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Correspondence to Smruti Rekha Swain.

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Singh, A.K., Swain, S.R. & Lee, C.N. A metaheuristic virtual machine placement framework toward power efficiency of sustainable cloud environment. Soft Comput 27, 3817–3828 (2023). https://doi.org/10.1007/s00500-022-07578-8

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Keywords

  • Virtual machine
  • Physical machine
  • Energy consumption
  • Random fit algorithm
  • Flower pollination optimization