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Improving Virtual Machine Migration Effects in Cloud Computing Environments Using Depth First Inspired Opportunity Exploration

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  • Kamal Kumar

    (National Institute of Technology, Uttarakhand, India)

  • Jyoti Thaman

    (Independent Researcher, India)

Abstract

The cloud platform has established itself as the de-facto standard in IT outsourcing. This is resulting in large-scale migration of infrastructure and development platforms from in-house to cloud service providers. Many recent proposals on cloud platforms have addressed several issues that appeared on the cloud horizon. VM placement (VMP) has been a serious concern when it comes to placement of VMs after migration or VM reallocation. Most of the recent works have lacked multiple VM placement (MVMP) problem instances. A recently researched idea of MVMP through depth first opportunistic exploration (DFOE) is proposed in this paper. The performance of MVMP is compared with existing single VM placement benchmark algorithm. Improvement in terms of number of VM migrations, energy consumption, and VM reallocation is reported through simulation of real-time load scenario. Cloud environments can benefit from MVMP and improve operating margins in terms of power saving and load balancing.

Suggested Citation

  • Kamal Kumar & Jyoti Thaman, 2022. "Improving Virtual Machine Migration Effects in Cloud Computing Environments Using Depth First Inspired Opportunity Exploration," International Journal of Cloud Applications and Computing (IJCAC), IGI Global, vol. 12(1), pages 1-22, January.
    • Handle: RePEc:igg:jcac00:v:12:y:2022:i:1:p:1-22
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