Enhanced Cloud Resource Optimization Using Secretary Bird Optimization Algorithm and Dynamic Workload Balancing

Authors

  • Guman Singh Chauhan John Tesla Inc, Texas, USA Author
  • Rahul Jadon Cargurus, USA Author
  • Kannan Srinivasan Senior Software Engineer Saiana Technologies Inc, New Jersey, USA Author
  • R. Hemnath Kaamadhenu Arts and Science College, Sathyamangalam, India. Author

DOI:

https://doi.org/10.70454/IJMRE.2022.20901

Keywords:

Cloud Resource Optimization, Secretary Bird Optimization Algorithm, Dynamic Workload Balancing, Task Scheduling, Metaheuristic Algorithms

Abstract

In this paper, a framework for optimizing cloud resource allocation using the Secretary Bird Optimization Algorithm and dynamic workload balancing has been presented. The presented method tackles inefficiency in cloud computing systems, such as inefficiency in task scheduling and resource overload, through dynamic task distribution among resources. With the introduction of SBOA, prompted by the innate behavior of secretary birds, and workload balancing, the approach achieves maximum resource utilization, minimum makespan, and lower computational expense. Global attention mechanisms are further incorporated into the framework to direct computational effort at the most salient features, which improves efficiency. Simulation results show improved cloud resource optimization by a significant extent over conventional approaches, rendering the method feasible for dynamic, large-scale cloud environments.

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Published

2022-09-30

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Articles

How to Cite

Enhanced Cloud Resource Optimization Using Secretary Bird Optimization Algorithm and Dynamic Workload Balancing. (2022). International Journal of Multidisciplinary Research and Explorer, 2(9), 30-42. https://doi.org/10.70454/IJMRE.2022.20901