N. Venkata Subramanian1, V. S. Shankar Sriram2,*
Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3279-3294, 2023, DOI:10.32604/iasc.2023.023700
- 17 August 2022
Abstract
Live Virtual Machine (VM) migration is one of the foremost techniques for progressing Cloud Data Centers’ (CDC) proficiency as it leads to better resource usage. The workload of CDC is often dynamic in nature, it is better to envisage the upcoming workload for early detection of overload status, underload status and to trigger the migration at an appropriate point wherein enough number of resources are available. Though various statistical and machine learning approaches are widely applied for resource usage prediction, they often failed to handle the increase of non-linear CDC data. To overcome this issue,
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