In the age of online workload explosion,cloud users are increasing exponentialy.Therefore,large scale data centers are required in cloud environment that leads to high energy consumption.Hence,optimal resource utiliza...In the age of online workload explosion,cloud users are increasing exponentialy.Therefore,large scale data centers are required in cloud environment that leads to high energy consumption.Hence,optimal resource utilization is essential to improve energy efficiency of cloud data center.Although,most of the existing literature focuses on virtual machine(VM)consolidation for increasing energy efficiency at the cost of service level agreement degradation.In order to improve the existing approaches,load aware three-gear THReshold(LATHR)as well as modified best fit decreasing(MBFD)algorithm is proposed for minimizing total energy consumption while improving the quality of service in terms of SLA.It offers promising results under dynamic workload and variable number of VMs(1-290)allocated on individual host.The outcomes of the proposed work are measured in terms of SLA,energy consumption,instruction energy ratio(IER)and the number of migrations against the varied numbers of VMs.From experimental results it has been concluded that the proposed technique reduced the SLA violations(55%,26%and 39%)and energy consumption(17%,12%and 6%)as compared to median absolute deviation(MAD),inter quartile range(IQR)and double threshold(THR)overload detection policies,respectively.展开更多
文摘In the age of online workload explosion,cloud users are increasing exponentialy.Therefore,large scale data centers are required in cloud environment that leads to high energy consumption.Hence,optimal resource utilization is essential to improve energy efficiency of cloud data center.Although,most of the existing literature focuses on virtual machine(VM)consolidation for increasing energy efficiency at the cost of service level agreement degradation.In order to improve the existing approaches,load aware three-gear THReshold(LATHR)as well as modified best fit decreasing(MBFD)algorithm is proposed for minimizing total energy consumption while improving the quality of service in terms of SLA.It offers promising results under dynamic workload and variable number of VMs(1-290)allocated on individual host.The outcomes of the proposed work are measured in terms of SLA,energy consumption,instruction energy ratio(IER)and the number of migrations against the varied numbers of VMs.From experimental results it has been concluded that the proposed technique reduced the SLA violations(55%,26%and 39%)and energy consumption(17%,12%and 6%)as compared to median absolute deviation(MAD),inter quartile range(IQR)and double threshold(THR)overload detection policies,respectively.
