الگوریتم بهینه سازی RIME آشوب ناک مبتنی بر درون یابی درجه دوم تعمیم یافته با پرواز لوی برای زمان بندی وظایف در رایانش ابری

Task scheduling in cloud computing still remains a crucial issue regarding system performance and user satisfaction. As organizations increasingly rely on cloud infrastructure to manage and execute their computational tasks, the need for effective scheduling becomes paramount. The main purpose of task scheduling is to assign submitted tasks to available appropriate resources while maintaining the quality of service and service level agreement. An effective task scheduling algorithm must be able to reduce the makespan as a crucial performance metric in cloud computing systems. In this paper, we have introduced a new efficient task scheduling algorithm called GQIRIME based on the RIME optimization algorithm to reduce the makespan, cost, and total execution time of the cloud system. An enhanced exploitation strategy is proposed based on generalized quadratic interpolation and levy flight to increase convergence rate while maintaining robust search. Furthermore, the proposed algorithm is integrated with chaos mapping to get a more diversified initial population. We have evaluated the effectiveness of our proposed approach using the Cloudsim toolkit. The results analysis demonstrates that our proposed algorithm outperforms other methods and significantly improves key performance metrics in task scheduling. According to the experiment results, the proposed task scheduling algorithm achieved a lower cost, makespan, and total execution time. The results show a ۲۹.۳% improvement in terms of makespan, ۶۱.۸% improvement in cost, and ۲۹.۴% improvement in total execution time on average compared to counterparts.

کلیدواژه ها:

زمان بندی وظایف ، الگوریتم بهینه سازی RIME ، رایانش ابری ، درون یابی درجه دوم ، فرا اکتشافی