Cloud Computing Task Scheduling Based on Improved Differential Evolution Algorithm

作者：Xueliang Fu, Yumeng Hu, Yang Sun · 年份：2020 · DOI：10.1145/3421766.3421785 · 被引用次数：3 · 研究领域：Cloud Computing and Resource Management、IoT and Edge/Fog Computing、Advanced Technology in Applications

In recent years, the introduction of intelligent optimization algorithm into cloud computing task scheduling to deal with the problem of massive task scheduling is a research hotspot. This paper proposes three improved differential evolution cloud computing task scheduling algorithms, and the application of the improved differential evolution algorithm in cloud computing task scheduling problem is mainly studied. The maximum task completion time is optimized by improving parameters F, CR, and variation strategies. Through two sets of simulation experiments, it is proved that three improved differential evolutionary cloud task scheduling algorithms have less task completion time than the traditional differential evolution algorithm, and the bigger the number of tasks, the more obvious the performance optimization of the algorithm.