An Extended Ameliorated Round Robin Algorithm in Cloud Computing for Task Scheduling | Chapter 7 | Mathematics and Computer Science: Contemporary Developments Vol. 4

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

Study on Proposed Resource Allocation Management for Cloud Computing Using Tabu Search Algorithm | Chapter 7 | Current Topics on Mathematics and Computer Science Vol. 6

 Cloud computing is a new technology that allows users to request computing resources on demand. This demand or supply of resources can be scheduled with the help of some policies. Resource allocation management should provide resources in a shorter time and at a lower cost. Cloud computing offers software as a service, platform as a service, and infrastructure as a service. A dynamically optimised system This study develops a resource allocation management method based on three criteria: optimum solution, timeline constraint, and cost constraint. The Tabu Search Algorithm is used in the algorithm, which is followed by prioritisation and task grouping.

Author (S) Details

Md Imran Alam
School of Computer Engineering, Kiit University, India.

Manjusha Pandey
School of Computer Engineering, Kiit University, India.

Siddharth S. Rautaray
School of Computer Engineering, Kiit University, India.

View Book :- https://stm.bookpi.org/CTMCS-V6/article/view/2587