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.
Author
(s) Details
Nermeen
Ghazy
Department of Mathematics, Faculty of Science (Girls), Al-Azhar
University, Cairo, Egypt.
Afaf
Abdelkader
Department of Mathematics, Faculty of Science (Girls), Al-Azhar
University, Cairo, Egypt.
Mervat
S. Zaki
Department of Mathematics, Faculty of Science (Girls), Al-Azhar University,
Cairo, Egypt.
Kamal
A. Eldahshan
Department of Mathematics, Faculty of Science, Al-Azhar
University, Cairo, Egypt.
Please see the book here:- https://doi.org/10.9734/bpi/mcscd/v4/1711
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