Rashid, Norfazlin (2025) Enhanced Marine Predator Algorithms For Task Scheduling In Cloud Data Centres. PhD thesis, Perpustakaan Hamzah Sendut.
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Abstract
Deterministic task scheduling in traditional homogeneous cloud data centres is straightforward, but increasing resource heterogeneity has made efficient scheduling more complex. Deterministic methods struggle to meet quality of service constraints, as improper vm-to-task mapping can degrade performance, leading to underutilization or overutilization of virtual machines (vms). To address this challenge, researchers are turning to metaheuristic approaches, such as marine predator algorithm (mpa). This study proposes a modified mpa-based task scheduling method to minimize task completion time and makespan. Three variants are introduced: modified mpa task scheduling (mmpacts), mmpacts with heterogeneous vm capacity identification (mmpacts-h), and mmpacts with load balancing (mmpacts-hlb). Mmpacts adapts mpa for discrete task allocation and enhances it with selective mutation and also cauchy mutation. Mmpacts-h incorporates a vm capacity index to account for varying vm capabilities, while mmpacts-hlb employs a lottery-based vm selection counter to balance workloads.
| Item Type: | Thesis (PhD) |
|---|---|
| Subjects: | Q Science > QA Mathematics > QA75.5-76.95 Electronic computers. Computer science |
| Divisions: | Pusat Pengajian Sains Komputer (School of Computer Sciences) > Thesis |
| Depositing User: | Mr Hasmizar Mansor |
| Date Deposited: | 23 Jun 2026 00:56 |
| Last Modified: | 23 Jun 2026 00:56 |
| URI: | http://eprints.usm.my/id/eprint/64427 |
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