Improving Efficiency And User Satisfaction In Cloud Computing Through Task Scheduling: A Comparision Among Different Scheduling Alorithms

Abstract

This study explores task scheduling algorithms in the context of cloud computing environments, considering multiple factors. Efficient task scheduling is crucial for optimizing resource utilization and improving system performance in the cloud. We investigate various factors, such as task priority, resource availability, and load balancing, and their impact on scheduling algorithms. Our research contributes to a deeper understanding of how to design and implement effective task scheduling strategies that meet the diverse requirements of cloud computing systems, leading to enhanced overall efficiency and user satisfaction. In this study, methods for scheduling tasks based on priority were studied in relation to virtual machines and tasks. This method achieves satisfactory results when it comes to balancing the load, however it does not perform well in terms of cost performance. A comparative analysis of the many different scheduling methods has also been included in this research and was carried out using the Cloudsim simulator.