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VMR:Virtual Machine Replacement Algorithm For QoS And Energy Efficiency In Cloud Data Centers

Posted on:2019-04-11Degree:MasterType:Thesis
Country:ChinaCandidate:RIAZ ALIFull Text:PDF
GTID:2428330590467358Subject:Computer Science&Engineering
Abstract/Summary:PDF Full Text Request
The Cloud computing paradigm facilitates customers to have on demand access to cloud resources.This leads to a large amount of physical machines and data centers in order to satisfy the requirements of customers,which are constantly on the growth.The progress in the quantity of running physical machines is directly proportionate to the rise in the energy consumption.Therefore,saving of energy utilization has become one of the foremost challenges of Cloud data centers.To minimize the energy consumption,a new technique with an adaptive threshold virtual machine replacement(VMR)algorithm that decreases the number of active physical machines in the Cloud data center was used.Virtualization scheme is being broadly applied across Information Technology infrastructure owing to its many benefits such as efficient resource utilization,ease of management,minimized energy consumption.Virtual machine is the basic unit of scheduling for saving energy consumption in Cloud data centers.VM replacement algorithm expands the performance of the whole system by efficiently balancing the load through physical machines.Virtualization is an important feature for Cloud computing data centers that has recently attracted considerable attention.Energy consumption is not measured in most of the migration schemes.In our thesis,we design a novel energy efficient approach that aims to minimize the energy consumption without reducing the Quality of Service(QoS)for users deadline requirements in Cloud data centers.We also propose a VM replacement algorithm for QoS and energyawareness in cloud data centers.We experimentally match the performance of our algorithm with other advanced algorithms(i.e.,the random algorithm and the first-fit algorithm).The experimental results illustrate that our solution improves first fit and random algorithms by twice and four times respectively,and is also energy efficient with reliable QoS while ensuring high level of Service Level Agreement(SLA).
Keywords/Search Tags:Cloud data center, virtual machine, physical machine, energy-efficiency, energy consumption, virtualization, VM replacement, QoS
PDF Full Text Request
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