Research on Resource Scheduling of Cloud Computing Based on Improved Genetic Algorithm

• 作者: Fuli Xiong Juanzhi Zhang Zhongxing Duan
• 来源期刊: 电子研究与应用
• 学科: 工学
• 关键词: Cloud computing resource scheduling Genetic algorithms Adaptive improvement operator
• 年，卷（期）: 2020,（2）
• 页码范围: 4-9
• 页数: 6页
• 分类号: TP3

摘要

In order to solve the problem that the resource scheduling time of cloud data center is too long,this paper analyzes the two-stage resource scheduling mechanism of cloud data center.Aiming at the minimum task completion time,a mathematical model of resource scheduling in cloud data center is established.The two-stage resource scheduling optimization simulation is realized by using the conventional genetic algorithm.On the technology of the conventional genetic algorithm,an adaptive transformation operator is designed to improve the crossover and mutation of the genetic algorithm.The experimental results show that the improved genetic algorithm can significantly reduce the total completion time of the task,and has good convergence and global optimization ability.