Ilunga, Nday Daniel and Covenant University, Theses (2024) A BIO-INSPIRED APPROACH TO TASK SCHEDULING IN FEDERATED CLOUDS USING WALRUS OPTIMIZATION ALGORITHM. Masters thesis, Covenant University.
Full text not available from this repository.Abstract
Cloud computing has witnessed an exponential rise in popularity, leading to a substantial increase in cloud users. This surge in demand for cloud services has introduced significant challenges in delivering high-quality services and optimizing resource allocation. As the demand for cloud services expands, effective task scheduling becomes paramount for improving system performance. Current task scheduling approaches are limited in that they cannot guarantee finding the globally optimal solution for optimization problems; often, they settle for locally optimal or suboptimal solutions, leading to underutilization of resources, increased expenditure, and customer dissatisfaction. This research investigates the potential of the Walrus Optimization Algorithm (WaOA) for task scheduling in federated clouds. The algorithm's performance was compared with existing approaches using standard metrics such as makespan, execution time, and throughput across various workload scenarios. The study utilizes Java and CloudSim for implementation and evaluation. Results demonstrate WaOA's efficiency in enhancing task scheduling within federated clouds, achieving the shortest makespan, highest throughput, and lowest execution time among the algorithms tested. Its ability to adapt to dynamic environments and optimize resource utilization consistently proved valuable across diverse scenarios. As the number of data centers increased, WaOA consistently performed well, indicating its potential for handling larger workloads and improving resource utilization efficiency. Overall, the study concludes that WaOA is a promising solution for enhancing task scheduling efficiency in federated clouds, highlighting the significance of algorithm selection and data center configuration in cloud computing environment.
| Item Type: | Thesis (Masters) |
|---|---|
| Uncontrolled Keywords: | Cloud Computing; Federated Cloud, Task Scheduling, Walrus Optimization Algorithm. |
| Subjects: | Q Science > QA Mathematics Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science |
| Depositing User: | nwokealisi |
| Date Deposited: | 11 Apr 2024 12:01 |
| Last Modified: | 11 Apr 2024 12:01 |
| URI: | http://eprints.covenantuniversity.edu.ng/id/eprint/17899 |
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