Multi- Objective Hybrid Algorithm for Energy Efficeincy in Task Scheduling in Cloud Computing

  • Neha Dutta, Dr. Pardeep Cheema

Abstract

The on-demand facility of virtual resources is supplied as a service with the assist of virtualization even without unnecessary waiting period, and cloud computing has progressively assumed a significant role in scientific applications. For job scheduling difficulties based on a time limitation, energy usage is lowered, resulting in a decline in energy cost. In this paper, we propose an Innovated energy efficiency algorithm benefits of ACO and PSO (Particle Swarm Optimization) algorithm. It is focused on the voltage scaling factor for the reduction of energy consumption. Performance of an Innovated energy efficiency When contrasted to ACO, the algorithm is significantly improved from 50 tasks forward. Energy consumption is the same as the ACO algorithm because as the number of tasks increases (40 to 75) there is a considerable decrease in the energy consumption rate. Furthermore, we examined energy usage for numerous processes and its pace of growth - up to 7 processors, energy consumption is significantly decreased, and energy consumption likely to be stable as the count of processors increases.

Published
2021-11-22
How to Cite
Neha Dutta, Dr. Pardeep Cheema. (2021). Multi- Objective Hybrid Algorithm for Energy Efficeincy in Task Scheduling in Cloud Computing. Design Engineering, 14325 - 14332. Retrieved from http://www.thedesignengineering.com/index.php/DE/article/view/6562
Section
Articles