Load Balancing in Cloud Environment by Implementing Enhanced Dragonfly Algorithm

  • P.Neelima, Dr. A. Rama Mohan Reddy

Abstract

The breakthroughs in processing and storage technologies as well as the popularity of the Internet have made computer resources more economical, powerful and widely available than ever before. A new computer model known as cloud computing has emerged as a result of this technical advancement. Scheduling is a key cloud application. In contrast, task scheduling in cloud computing is an NP-hard optimization issue. A fundamental part of cloud task planning is the load balancing of non-preventive, autonomous workloads on virtual machines (VMs). The technique of moving tasks from overburdened VMs to under burdened VMs is known as load balancing. When operating an application, load balancing might have an impact on the overall performance of the system. A load balancing algorithm tries to improve the response time of user-submitted applications by guaranteeing maximum utilization of available resources. To address this issue, we developed a novel cloud load balancing approach based on the Enhanced Dragonfly algorithm (EDA). In addition, we create a multi-objective function based on three variables: completion time, processing expenses, and load. The major goal is to perform the task in a shorter amount of time, with lower processing costs and load balancing. The experimental results suggest that the proposed strategy outperforms existing approaches in terms of load balancing (lower cost and time).

Published
2021-11-10
How to Cite
P.Neelima, Dr. A. Rama Mohan Reddy. (2021). Load Balancing in Cloud Environment by Implementing Enhanced Dragonfly Algorithm . Design Engineering, 11128 - 11135. Retrieved from http://www.thedesignengineering.com/index.php/DE/article/view/6174
Section
Articles