Title: VMO-HNIA: virtual machine optimisation using hybrid nature inspired algorithm for cloud resources efficiency

Authors: Ruaa Ali Khamees

Addresses: Department of Information and Communication Technology, Middle Technical University Institute of Technology, Baghdad, Iraq

Abstract: Optimisation for cloud data centres, virtual machine (VM) consolidation is advised, however performance trade-offs are difficult. VM optimisation utilising the hybrid nature inspired algorithm (VMO-HNIA) is a new VM consolidation framework. The HNI-based VM consolidation system uses a multi-resources aware decision algorithm (MADA) to identify host overload or underload dynamically. To enhance the optimisation of VM resources and load balancing, the MADA calculates numerous resources to inform decision-making. The correct classification of each host further boosts VM consolidation processes like VM selection, migration, and placement. To improve the process of selecting and placing VMs in a VM consolidation architecture, we suggest using a new technique called the hybrid whale optimisation technique (HWOA) for VM selection and placement. To improve VM consolidation, the HWOA places the best host utilising several objective functions. Experimental findings show the VMO-NHI framework employing CloudSim outperforms underlying solutions.

Keywords: cloud computing; decision-making; host placement; nature-inspired; VM selection; VM placement; resources optimisation.

DOI: 10.1504/IJCSE.2025.149759

International Journal of Computational Science and Engineering, 2025 Vol.28 No.6, pp.650 - 661

Received: 19 Jul 2024
Accepted: 04 Jan 2025
Published online: 12 Nov 2025 *

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