Abstract

The popularity of cloud computing platforms has risen dramatically in recent years. As cloud computing serves millions of users at the same time, it must be able to handle all those users' demands efficiently. Thus, choosing a suitable scheduling algorithm is crucial in the cloud computing environment in order to ensure efficient performance with a reasonable degree of quality of service (QoS). The primary goal of this research is to empirically implement and evaluate a recently proposed Round-Robin algorithm with smart time quantum (RR-STQ) in a cloud computing environment, as well as, to enhance the RR-STQ with a dynamic smart time quantum. The CloudSim tool was used to simulate the cloud computing platform to implement RR-STQ and evaluate it with several algorithms using different scenarios. In addition, three scheduling performance metrics were used in the evaluation process. In all comparison scenarios, the (RR-STQ) achieved a significant improvement rate in terms of average response time (RT). Moreover, (RR-STQ) has a better performance in the average turnaround time (TAT), waiting time (WT), and response time (RT) than the traditional RR algorithm. Also, the implemented algorithm (RR-STQ) with dynamic time quantum has a better performance than static time quantum. Based on the evaluation results, it is beneficial to integrate the RR algorithm with other scheduling models such as shortest job first (SJF) to enhance the WT and TAT. Furthermore, the investigations revealed that the dynamic time quantum improves the performance of the RR algorithm.

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