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Optimal Meta-Heuristic Elastic Scheduling (OMES) for VM selection and migration in cloud computing

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Abstract

Virtualization is a powerful technique that allows numerous applications can execute on a single cloud server. The process is carried out by cramming software into Virtual Machines (VMs), so that many programs may execute in parallel which leads to an increase in speed. It reduces the overall cost of the cloud data centers by applying migration, and load balancing techniques on the virtual machines. However, the associated energy consumption and Service Level Agreement (SLA) breaches have been extremely high because of increased network traffic and the bandwidth requirements of the applications. To address this issue, the current study presented a novel approach based on the food selection technique used by honey bees to allocate and utilize resources to the VMs. The proposed Optimal Meta-Heuristic Elastic Scheduling (OMES) integrates the Artificial Bee Colony algorithm with flower pollination to select VMs for specific clusters. The simulation is applied on 1000 VMs and analyzed based on VM migration, energy consumption, and SLA violation performance metrics. The comparative analysis performed against existing studies demonstrates highest unit improvement of 0.47 for VM migrations, 0.485 for power consumption, and 0.305 for SLA-V.

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Authors and Affiliations

  1. University Institute of Computing, Chandigarh University, Mohali, Punjab, India

    Krishan Tuli & Manisha Malhotra

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  1. Krishan Tuli
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  2. Manisha Malhotra
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Correspondence to Krishan Tuli.

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Tuli, K., Malhotra, M. Optimal Meta-Heuristic Elastic Scheduling (OMES) for VM selection and migration in cloud computing. Multimed Tools Appl 83, 34601–34627 (2024). https://doi.org/10.1007/s11042-023-16820-w

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