Modified Bat Algorithm for Optimal VM's in Cloud Computing

• Published in: Computers, materials & continua Vol. 72; no. 2; pp. 2877 - 2894
• Main Authors: Sundas, Amit, Badotra, Sumit, Alotaibi, Youseef, Alghamdi, Saleh, Ibrahim Khalaf, Osamah
• Format: Journal Article
• Language: English
• Published: Henderson Tech Science Press 2022
• Subjects: Algorithms; Cloud computing; Load balancing; Optimization; Task scheduling; Virtual environments
• ISSN: 1546-2226; 1546-2218; 1546-2226
• DOI: 10.32604/cmc.2022.025658

All task scheduling applications need to ensure that resources are optimally used, performance is enhanced, and costs are minimized. The purpose of this paper is to discuss how to Fitness Calculate Values (FCVs) to provide application software with a reliable solution during the initial stages of load balancing. The cloud computing environment is the subject of this study. It consists of both physical and logical components (most notably cloud infrastructure and cloud storage) (in particular cloud services and cloud platforms). This intricate structure is interconnected to provide services to users and improve the overall system's performance. This case study is one of the most important segments of cloud computing, i.e., Load Balancing. This paper aims to introduce a new approach to balance the load among Virtual Machines (VM's) of the cloud computing environment. The proposed method led to the proposal and implementation of an algorithm inspired by the Bat Algorithm (BA). This proposed Modified Bat Algorithm (MBA) allows balancing the load among virtual machines. The proposed algorithm works in two variants: MBA with Overloaded Optimal Virtual Machine (MBA-OOVM) and Modified Bat Algorithm with Balanced Virtual Machine (MBA-BVM). MBA generates cost-effective solutions and the strengths of MBA are finally validated by comparing it with Bat Algorithm.