一种新的基于智能时间量子的轮循算法在云计算环境中的实现

Haifa Al-Shammare, Nehal Al-Otaiby
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摘要

近年来,云计算平台的普及程度急剧上升。由于云计算同时为数百万用户提供服务,因此它必须能够有效地处理所有这些用户的需求。因此,在云计算环境中,选择合适的调度算法以保证高效的性能和合理的服务质量(QoS)至关重要。本研究的主要目标是在云计算环境下对最近提出的一种基于智能时间量子(RR-STQ)的轮询算法进行实证实现和评估,并利用动态智能时间量子对RR-STQ进行增强。使用CloudSim工具模拟云计算平台实现RR-STQ,并使用不同场景下的几种算法对其进行评估。此外,在评估过程中使用了三个调度性能指标。在所有的比较场景中,(RR-STQ)在平均响应时间(RT)方面取得了显著的改善。此外,(RR- stq)算法在平均周转时间(TAT)、等待时间(WT)和响应时间(RT)方面都比传统的RR算法有更好的性能。同时,所实现的带有动态时间量子的RR-STQ算法具有比静态时间量子更好的性能。基于评价结果,将RR算法与其他调度模型(如最短作业优先(SJF))相结合,有利于提高WT和TAT的效率。此外,研究表明,动态时间量子提高了RR算法的性能。
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An Implementation of a New Proposed Round-Robin Algorithm with Smart Time Quantum in Cloud Computing Environment
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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