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Optimal virtual machine scheduling in virtualized cloud environment using VIKOR method

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Abstract

This paper presents a Power and Resource Utilization-Aware Virtual Machine Scheduling (PRUVMS) algorithm for strengthening resource utilization and diminishing the energy consumption of servers in the cloud environment. The PRUVMS algorithm enhances the resource utilization by migrating the VMs from the underloaded/overloaded servers to a normal server, and it reduces the energy consumption by shutting down the underloaded servers after migrating the VMs. For selecting the suitable server for the VM placement, the ranking of the available servers is evaluated. An illustrative example is presented to validate the PRUVMS algorithm. Further, the PRUVMS algorithm is tested on the PlanetLab workload using the CloudSim simulator. The proposed PRUVMS algorithm improves resource utilization by 68.22% and 37.53% and decreases the energy consumption by 35.53% and 31.34% in comparison with PABFD and CAVMP algorithms, respectively. The improvement in computational results shows the acceptability of the proposed scheduling algorithm in the cloud environment.

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Data availability

Datasets used in the presented paper are available from https://github.com/beloglazov/planetlab-workload-traces.

Code availability

Code is available from the corresponding author on reasonable request.

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  1. Department of Computer Science and Engineering, Sant Longowal Institute of Engineering and Technology, Punjab, India

    Neha Garg, Damanpreet Singh & Major Singh Goraya

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  1. Neha Garg
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  2. Damanpreet Singh
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Correspondence to Neha Garg.

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Garg, N., Singh, D. & Goraya, M.S. Optimal virtual machine scheduling in virtualized cloud environment using VIKOR method. J Supercomput 78, 6006–6034 (2022). https://doi.org/10.1007/s11227-021-04081-z

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