In cloud data centers,the consolidation of workload is one of the phases during which the available hosts are allocated tasks.This phenomenon ensures that the least possible number of hosts is used without compromise ...In cloud data centers,the consolidation of workload is one of the phases during which the available hosts are allocated tasks.This phenomenon ensures that the least possible number of hosts is used without compromise in meeting the Service Level Agreement(SLA).To consolidate the workloads,the hosts are segregated into three categories:normal hosts,under-loaded hosts,and over-loaded hosts based on their utilization.It is to be noted that the identification of an extensively used host or underloaded host is challenging to accomplish.Thresh-old values were proposed in the literature to detect this scenario.The current study aims to improve the existing methods that choose the underloaded hosts,get rid of Virtual Machines(VMs)from them,andfinally place them in some other hosts.The researcher proposes a Host Resource Utilization Aware(HRUAA)Algorithm to detect those underloaded and place its virtual machines on different hosts in a vibrant Cloud environment.The mechanism presented in this study is contrasted with existing mechanisms empirically.The results attained from the study estab-lish that numerous hosts can be shut down,while at the same time,the user's workload requirement can also be met.The proposed method is energy-efficient in workload consolidation,saves cost and time,and leverages active hosts.展开更多
文摘In cloud data centers,the consolidation of workload is one of the phases during which the available hosts are allocated tasks.This phenomenon ensures that the least possible number of hosts is used without compromise in meeting the Service Level Agreement(SLA).To consolidate the workloads,the hosts are segregated into three categories:normal hosts,under-loaded hosts,and over-loaded hosts based on their utilization.It is to be noted that the identification of an extensively used host or underloaded host is challenging to accomplish.Thresh-old values were proposed in the literature to detect this scenario.The current study aims to improve the existing methods that choose the underloaded hosts,get rid of Virtual Machines(VMs)from them,andfinally place them in some other hosts.The researcher proposes a Host Resource Utilization Aware(HRUAA)Algorithm to detect those underloaded and place its virtual machines on different hosts in a vibrant Cloud environment.The mechanism presented in this study is contrasted with existing mechanisms empirically.The results attained from the study estab-lish that numerous hosts can be shut down,while at the same time,the user's workload requirement can also be met.The proposed method is energy-efficient in workload consolidation,saves cost and time,and leverages active hosts.
