Abstract
To mitigate severe physical resource consumption in cloud data centers, we propose an Improved Sparrow Search Algorithm-Based Virtual Machine Placement (ISSA-VMP) method. Incorporating Chebyshev chaotic mapping and Levy flight disturbance enhances resource allocation diversity in the search space. The mapping encoding scheme transforms virtual machine placement solutions into continuous positional information. ISSA-VMP establishes a cloud data center resource consumption model to maximize physical host resource utilization efficiency. The simulation results demonstrate the excellent performance of ISSA-VMP in virtual machine migration and physical resource utilization, significantly reducing task completion time. Compared to the best performing algorithm, the execution rate has increased by 5.57–18.11%. ISSA-VMP achieves high and stable physical resource utilization rates, ensuring efficient utilization, with a stable Service Level Agreement (SLA) violation rate. In summary, ISSA-VMP is a promising, efficient solution for optimizing resource allocation in cloud data centers.
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Funding
This work is supported by the National Natural Science Foundation of China (Grant No. 61871468), Zhejiang Provincial Key Laboratory of New Network Standards and Technologies (Grant No. 2013E10012), School-level Teaching Project of Zhejiang Gongshang University (Grant No. 1120XJ2918335), the Key Research and Development Program of Zhejiang Province (Grant No. 2021C01036).
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RQ and ZZ wrote the main manuscript text, ZB conducted data investigation and reviewed manuscript, and DL and JX prepared all figures and tables. All authors reviewed the manuscript.
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Ren, Q., Zhuge, B., Zhang, Z. et al. Improved sparrow algorithm based virtual machine placement. Cluster Comput 27, 6511–6525 (2024). https://doi.org/10.1007/s10586-024-04269-x
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DOI: https://doi.org/10.1007/s10586-024-04269-x