Eliminating the downtime faced by the IaaS hosted web applications during vertical scaling

Chopra, Tanya (2020) Eliminating the downtime faced by the IaaS hosted web applications during vertical scaling. Masters thesis, Dublin, National College of Ireland.

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Abstract

In the computer world today, cloud computing is becoming a major division that is evolving as a result of technological advancement. The scope of this technology is also very broad. Even though Platform as a Service (PaaS) solutions are known by a lot of people than IaaS, there is a lot of scope for personalized solutions with Infrastructure as a Service (IaaS). The dynamic workload of any web application becomes a problem for the end users. As it is not predictable, the IaaS availability is affected. One way to overcome this drawback is by using vertical scaling of the VMs. While the VM is being up scaled or down-scaled, the waiting time is avoided for the end-users. The most crucial part of the solution to this problem is to cut down the downtime with this method. This auto-scaling happens automatically, depending on the workload faced when a web application is hosted in the IaaS. Creating a VM’s image of a similar size is done by the ’MakeShift Cross Scale Algorithm’. This algorithm is used to track the workloads as it changes. This process is done without actually changing the existing VM. Cloning the existing VM into the new machine helps in scaling up the existing VM, according to the user requests. Once the process of cloning is completed, the old VM is decommissioned. Thus, this project eliminates any downtime that occurs during the whole process. With the help of vertical scaling, the performance of the system is improved through high availability in this research project. This approach of vertical scaling of the applications has resulted in high throughput. The average cloning time of the VM is approximately 8.8 minutes and the average deletion time of the old VM and its resources is approximately 4.5 minutes.

Item Type:	Thesis (Masters)
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Cloud computing
Divisions:	School of Computing > Master of Science in Cloud Computing
Depositing User:	Dan English
Date Deposited:	28 Jan 2021 13:29
Last Modified:	28 Jan 2021 13:29
URI:	https://norma.ncirl.ie/id/eprint/4530

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