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George, Kurian (2024) Optimizing Resource Scheduling in Cloud Environments with Docker Containers and Advanced Auto-Scaling Algorithms. Masters thesis, Dublin, National College of Ireland.
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Abstract
This research presents a novel approach to optimizing resource scheduling in cloud environments by integrating Docker containers with an advanced Ant Colony Optimization (ACO) algorithm. The newly proposed version of the ACO algorithm addresses the inefficiencies of traditional resource scheduling methods by cost-efficiently handling dynamic and fluctuating workloads in cloud infrastructure. This proposed algorithm features adaptive pheromone updating strategies and an improved decision-making process to allocate resources more effectively while minimizing operational costs. This study uses the EdgeSimPy simulator, in which the servers are made as Docker containers for an effective testing environment. This study demonstrates that the proposed new ACO algorithm outperforms conventional methods like First Come First Serve (FCFS) and offers a better and more cost-efficient solution for managing cloud resources. This study marks a significant contribution to cloud resource management by providing an optimal resource scheduling solution in variable cloud environments.
| Item Type: | Thesis (Masters) |
|---|---|
| Supervisors: | Name Email Gupta, Punit 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 Q Science > QA Mathematics > Algebra > Algorithms > Computer algorithms |
| Divisions: | School of Computing > Master of Science in Cloud Computing |
| Depositing User: | Ciara O'Brien |
| Date Deposited: | 03 Jul 2025 10:21 |
| Last Modified: | 03 Jul 2025 10:21 |
| URI: | https://norma.ncirl.ie/id/eprint/8016 |
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