A large-scale task scheduling algorithm based on clustering and duplication
Wengang Huang, Zhichen Shi, Zheng Xiao, Cen Chen, Kenli Li · Journal of Smart Environments and Green Computing · 2022
Aim: Our research aims to explore a fast and efficient scheduling algorithm. The purpose is to schedule large-scale tasks on a limited number of processors reasonably while improving resource utilization. Methods: This paper proposes a clustering and duplication-based method for large-scale task scheduling on a limited amount of processors. We cluster large-scale task to reduce the scale of the task in our method at first. Second, duplication-based task scheduling is carried out. Third, we optimize the local effect more precisely by deduplication in the last stage. Results: We compare our algorithm with the state-of-the-art algorithms in the article. The results demonstrate that our scheduling scheme obtains about 30% optimization compared to existing large-scale scheduling methods and runs roughly ten times faster than existing duplication-based algorithms when scheduling large-scale tasks to a limited number of processors as compared to similar algorithms. Conclusion: In this paper, we propose a task scheduling algorithm that can decrease the scheduling time of large- scale tasks on a limited number of processors and speed up the global execution time of the task. Further, we will study large-scale task scheduling on heterogeneous processor clusters. Keywords