Optimization of Load Balancing Algorithm in Cloud Computing

Abstract

A rapidly expanding service, cloud computing (CC) uses a pay-per-use business model. As far as capacity, organization, web administrations, and so forth, innovation offers various administrations. Regardless, the expansion of these organizations and the enormous flood in user demand has made it trying to stay aware of execution as per QoS assessment and SLA chronicles that cloud suppliers make available to businesses. This growth brought about difficulties like load balancing. In addition, it became challenging to meet customer expectations for response speed and work scheduling deadlines. This research suggests an optimal approach based on schedule limitations using the Machine Learning Classification technique to overcome these issues. The main goals of the suggested technique are to increase productivity, optimise server resources by taking into account the importance of various users' tasks, and prevent server failure. Based on the most recent literature, our suggested method will address the aforementioned problems and the existing research gap.