Performance Evaluation on Load Balancing Algorithms in Cloud Computing Environment: A Comparative Study

Abstract

In the realm of parallel and distributed computing, cloud computing is quickly becoming a viable alternative to the use of traditional physical hardware. Clouds are groupings of virtual resources that can be generated on demand to fulfill the particular needs of individual users. These requirements may be quite specific. Due to the large number of users, tasks, and data, processing in the cloud is also extremely significant. Load balancing is of tremendous benefit in cloud virtual environments where vital tasks are performed. Load balancing is a crucial topic of study because of the increasing prevalence of cloud computing and the consequent increase in the number of customers expecting more services and better outcomes. Recently, efficient work scheduling has become one of the cloud computing industry's primary obstacles. The primary objective of this study is to compare and contrast the most popular scheduling and load-balancing approaches as they apply to the cloud computing environment. The comparative analysis of HISA, DI-HISA, LBA, LB-HEFT, and LBMPSO techniques is provided in this work to illustrate the performance evaluation over 50 cloudlets and 5 virtual machines. The experiment's findings demonstrate that our second suggested approach, DI-HISA, obtained the shortest makespan of 84.87 milliseconds when compared with the other methods.