A new median-average round Robin scheduling algorithm: An optimal approach for reducing turnaround and waiting time

Author's Department

Mathematics & Actuarial Science Department

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https://doi.org/10.1016/j.aej.2022.04.006

All Authors

Sakshi, Chetan Sharma, Shamneesh Sharma, Sandeep Kautish, Shami A. M. Alsallami, E.M. Khalil, Ali Wagdy Mohamed

Document Type

Research Article

Publication Title

Alexandria Engineering Journal

Publication Date

Winter 12-1-2022

doi

10.1016/j.aej.2022.04.006

Abstract

A variety of algorithms handles processes on the CPU. The round-robin algorithm is an efficient CPU scheduling mechanism for a time-sharing operating system. The system processes the methods based on the time slice; however, determining the time slice has proven highly challenging for the researchers. As a result, a variety of dynamic time quantum scheduling techniques are presented by various academics to address this challenge. This study aims to determine how to best schedule resources to maximize efficiency. It is important to note that this scheduling mechanism rotates between the processes after the static quantum time is complete. However, the quantum decision affects how effectively and efficiently the procedures may be scheduled. Additionally, the quantum decision has an impact on the scheduling of processes. The average waiting time, turnaround time, and context switch times of the Round Robin scheduling algorithm are high enough to influence the system's performance. To get over the round-drawbacks, robin's the authors in this study suggest using the improved algorithm Median-Average Round Robin (MARR). Using the median and average of the burst time of each process, the author proposes a dynamic time quantum for the system. The authors compared the proposed model with four other scheduling algorithms. The results vividly depict that the proposed algorithms successfully give effective results with reduced average turnaround time and waiting time. In the future, cost and RAM utilization will be considered to enhance the algorithm.

First Page

10527

Last Page

10538

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