Optimal Task Scheduling using Egyptian Vulture Optimization Algorithm

  • Gagandeep Kaur, Anurag Sharma ,
Keywords: Cloud Computing, Egyptian Vulture Optimization Algorithm, Internet of Things, Task Scheduling.

Abstract

This paper proposes an optimal task scheduling algorithm for cloud computing. The main contribution of this work is to enhance the convergence rate to find the optimal task scheduling. This is achieved by deploying the Egyptian Vulture Optimization (EVO) algorithm. The EVO algorithm performs simple operations such as hitting with pebble, rolling with twigs, and change of the angle to find the optimal solution. Due to these operations, the exploring rate to find the optimal solution is higher than existing optimization algorithms. Besides that, a multi-objective-based fitness function is designed to find the optimal solution in place of a single objective. A number of different tasks are considered, and their file size is randomly generated to validate the proposed method. Further, various performance metrics are measured, such as Makespan, Average Waiting Time (AWT), as well as Average Turnaround Time (ATT). In comparison to the existing algorithms, the proposed method is determined to be superior.

Published
2021-09-17
How to Cite
Anurag Sharma , , G. K. (2021). Optimal Task Scheduling using Egyptian Vulture Optimization Algorithm. Design Engineering, 12542-12552. Retrieved from http://www.thedesignengineering.com/index.php/DE/article/view/4464
Section
Articles