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Applied Mathematics & Information Sciences
An International Journal
               
 
 
 
 
 
 
 
 
 
 
 
 
 

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Volumes > Volume 18 > No. 1

 
   

Thermal-Aware Resource Allocation Strategy For Data Centers

PP: 32-35
doi:10.18576/amis/170592
Author(s)
K Prasanth, M Priyanka, S Vignesh, A Selva Ganapathy,
Abstract
Virtual Machines (VMs) in Cloud systems scheduled to hosts based on how much resource they immediately use (e.g., hosts with greatest available RAM),instead of utilizing them extensively and over time. Furthermore, The placement and scheduling processes are often computationally intensive and have an effect on the efficiency of deployed VMs. In this article, provide a Cloud VM scheduling method that considers existing VM resource consumption gradually by assessing previous VM utilization levels to be able to schedule VMs while maximizing performance using the PSO technique. Because Cloud management activities the like VM placement have an impact on previously deployed systems, the goal is to minimize such performance deterioration. Furthermore, because overcrowded VMs tend to grab resources from neighboring VMs, the task enhances the VMs true CPU consumption. The outcomes reveal that our method improves conventional Instant- based physical machine choice as it gains knowledge and adapts to system performance over time. The idea of VM scheduling based on resource monitoring information taken from previous resource utilizations (VMs).

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