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Research Paper | Computer Science | China | Volume 12 Issue 3, March 2023 | Rating: 4.9 / 10
Multi-Job Scheduling and Optimization Model for Cloud Computing
Dzikunu Andrews Dodzi Kobla | Kenneth Owusu | Amos Peprah | Koukoyi Ebenezer
Abstract: Among the most frequently encountered problems in the cloud computing system seems to be independent job scheduling. The Grey Wolf Optimization and Artificial Bee Colony (GWO-ABC) approach is a brand-new hybrid optimization technique that is proposed in this work. The GWO-ABC is used to enhance multi-job scheduling inside a cloud computing system. It imitates the hunting and grouping behaviour of wolves and ants. The proposed multi-objective model seems to be the foundation of the GWO-ABC scheduler. In aspects of cost, degree of imbalance, makespan, resource utilisation, and energy usage, the experiment outcomes on the trialed data demonstrated that the GWO-ABC scheduler outperforms the outcomes of the Round Robin (RR) method, conventional Whale Optimization Algorithm (WOA), and Vocalisation of Humpback WOA (VWOA). The results of the simulation clearly show that the GWO-ABC method is better than the algorithms that are currently being used.
Keywords: Optimization, Job Scheduling, Cloud Computing, Bee Colony, Exploitation
Edition: Volume 12 Issue 3, March 2023,
Pages: 713 - 720