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The Concept of Workload Delay as a Quality-of-Service Metric for Consolidated Cloud Environments

Rawal, Itendra
Master thesis
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itendrar_thesis_upload.pdf (9.396Mb)
Year
2018
Permanent link
http://urn.nb.no/URN:NBN:no-66412

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  • Institutt for informatikk [3604]
Abstract
Cloud computing is one of the fastest emerging technology. Increase in demands of cloud computing leads to increase in data centers. These data center consists of a huge number of interconnected Physical Machines (PMs). Increase in data center leads to increase in energy and power consumption and also increase in financial expenses like maintenance cost. Virtual Machine (VM) consolidation in data centers is important aspects for cloud service providers. VM consolidation consists of numerous benefits including deduction of deployed physical machines, reduction in power and energy consumption and also decrease in expenses. Two experiments were performed. In a first experiment, a single VM was assigned to each PMs and a workload was dispatched and On the basis of that total time taken by the VM for the completion of workload execution and CPU utilization done by VM during the workload-execution were figured out. Similarly, in the second experiment, multiple VMs were consolidated inside single PM and a workload was dispatched to all the VMs at the same time. On the basis of that total time taken by the VMs for the completion of workload execution and CPU utilization done by the VMs during the workload-execution were figured out. CPU utilization was low during the first experiment. Lots of resources and system memories were unutilized. But in the second experiment, CPU utilization was high. Single PM has done the work of multiple PMs. There was no degradation in the quality of outcome. Performed experiments result in better computing efficiency, lower power and cooling cost and flexibility to migrate workloads and VMs. This paper shows up the way for cloud service providers for making efficient use of hardware and resources and also save their budget by deploying less PMs in their respective data centers and eventually maintaining the Quality of Service.
 
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