A Hybrid Optimization Approach in Cloud Computing Based on Yellow Saddle Goatfish and Particle Swarm Optimization Algorithms for Task Scheduling

Authors

  • Manpreet Kaur Department of Computer Science, Sri Guru Granth Sahib World University, Fatehgarh Sahib (140406), Punjab, India.
  • Sarpreet Singh Department of Computer Science, Sri Guru Granth Sahib World University, Fatehgarh Sahib (140406), Punjab, India

Keywords:

cloud computing, load balancing, workflow scheduling, resource management, optimization algorithms

Abstract

Task scheduling is a necessary component of any distributed infrastructure since it distributes jobs to the appropriate resources, for the process of execution. The task scheduling algorithm presented in this research uses an integrated optimization approach for scheduling tasks seamlessly and effectively on cloud computing. In the proposed work, we have used Yellow saddle Goat Fish algorithm (YSGA) along with particle swarm optimization (PSO) algorithm. Initially, a random population is generated upon which hybrid YPSO model is implemented to attain fitness values. Here, the proposed hybrid YPSO model analyzes six factors i.e., cost, average completion time, make span time, consumption of energy during process, utilization of available resource and handling of load to calculate its fitness value. The iteration with the least fitness value will be selected as the final one and all the task will be schedules as per this fitness value. The performance of YPSO model is then analyzed and compared with standard YSGA model in MATLAB Software under two scenarios. In the first case, we analyzed performance of proposed model with respect to standard YSGA model for varying tasks with 3 VMs, while as, in second case VMs are varied. Simulating outcomes depict that in both cases the fitness value keeps getting better in proposed hybrid YPSO model to prove its supremacy over other similar methods.   

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References

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Published

24.03.2024

How to Cite

Kaur, M. ., & Singh, S. . (2024). A Hybrid Optimization Approach in Cloud Computing Based on Yellow Saddle Goatfish and Particle Swarm Optimization Algorithms for Task Scheduling. International Journal of Intelligent Systems and Applications in Engineering, 12(20s), 08–19. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/5114

Issue

Vol. 12 No. 20s (2024)

Section

Research Article

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