Optimization of Multi-Cloud Workload Placement for Performance and Cost Efficiency

Sinha, Rishabh (2023) Optimization of Multi-Cloud Workload Placement for Performance and Cost Efficiency. Masters thesis, Dublin, National College of Ireland.

Preview	PDF (Master of Science) Download (1MB) | Preview
Preview	PDF (Configuration Manual) Download (2MB) | Preview

Abstract

This research project aims to optimize the performance and cost efficiency of deploying multiple application components on various cloud providers in a multicloud environment. The project proposes a solution based on Stochastic Hill Climbing and Simulated Annealing algorithms to search for cost-efficient and optimal configuration parameters in Azure and AWS cloud environments. The solution retrieves current pricing and instance-specific configuration data from AWS and Azure APIs, and searches configuration parameters for up to 20 application components. The project also conducts experiments with various advanced machine learning algorithms to predict the optimal CPU and memory requirements of a workload for optimal performance. In addition, the project implements a simulation script for the new workload to be tested by executing the workload on a Docker container and estimating the CPU and memory requirement of the workload based on application characteristics. Both of these are implemented for performance optimization. The proposed solution suggests which application components should be deployed to which cloud service provider, and aims to provide an optimal solution for cost optimization in a real-world scenario.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Kazmi, Aqeel UNSPECIFIED
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:	Ciara O'Brien
Date Deposited:	11 Apr 2025 08:50
Last Modified:	11 Apr 2025 08:50
URI:	https://norma.ncirl.ie/id/eprint/7416

Actions (login required)

View Item