An Extended Ameliorated Round Robin Algorithm in Cloud Computing for Task Scheduling

Cloud computing is a cutting-edge technology that provides a variety of services on demand. Due to the substantial volume of requests received from cloud users, it is crucial to manage these requests efficiently. As such, task scheduling becomes a vital aspect of cloud computing. The allocation of computational resources within the cloud is managed by cloud providers, highlighting the necessity for designing high-efficiency scheduling algorithms compatible with diverse computing paradigms.

This chapter introduces a new method for task scheduling in cloud computing called the Ameliorated Round Robin Algorithm (ARRA). The proposed algorithm enhances the traditional Round Robin approach by developing an optimal time quantum based on the average burst time of tasks. This is achieved through both fixed and dynamic methodologies, allowing the algorithm to adapt to varying workloads more effectively.

The chapter provides a comprehensive analysis of the ARRA, demonstrating its superior performance through experimental results. These results indicate that ARRA significantly outperforms existing algorithms, such as Improved Round Robin (IRR), Enhanced Round Robin (ERR), Dynamic Time Quantum Approach (ARR), and Enhanced Round Robin with RAST (RAST ERR). The improvements are evident in key performance metrics, including average waiting time, average turnaround time, and response time.

By optimizing these metrics, ARRA not only enhances the efficiency of task scheduling in cloud computing but also contributes to better resource utilization and user satisfaction. This chapter delves into the technical details of the ARRA, provides comparative analyses with other algorithms, and discusses the implications of these findings for future research and practical applications in cloud computing environments.