Cloud Computing Task Scheduling Based on Improved Differential Evolution Algorithm

Abstract

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.