软件导刊2024，Vol.23Issue(10)：104-111,8.DOI:10.11907/rjdk.232048
基于混合策略鲸鱼优化算法的云计算任务调度研究
Research on Cloud Computing Task Scheduling Based on Mixed Strategy Whale Optimization Algorithm
摘要
Abstract
A cloud computing task scheduling method based on the Hybrid Strategy Whale Optimization Algorithm(MSWOA)is proposed to address issues such as long task execution time,high system execution costs,and imbalanced system loads in the process of cloud computing task scheduling.Firstly,use Tent chaotic mapping to initialize the whale population to enhance population diversity and make the distribution of whale individuals more uniform;Then,an adaptive probability threshold was proposed to balance the global search capability and local de-velopment capability of the algorithm,and the Levy flight strategy was introduced in the random search stage of the algorithm to expand the search space and search capability of the algorithm;Finally,a multi-objective fitness function was designed for the task scheduling process,and an algorithm was used to solve the multi-objective task scheduling problem in cloud computing.The simulation experiment of MSWOA was conducted using CloudSim cloud computing simulation software,and the results of comparing MSWOA with NOA,ZOA,OAWOA,and TSWOA algorithms showed that compared with other algorithms,MSWOA achieved better performance at different task scales.It not only re-duced the maximum completion time and system execution cost of tasks,but also improved the average load rate of the system,which has sig-nificant advantages in multi-objective task scheduling in cloud computing.关键词
云计算/任务调度/鲸鱼优化算法/多目标优化/莱维飞行Key words
cloud computing/task scheduling/whale optimization algorithm/multi-objective optimization/Levy flight分类
信息技术与安全科学引用本文复制引用
史爱武,黄河,罗干..基于混合策略鲸鱼优化算法的云计算任务调度研究[J].软件导刊,2024,23(10):104-111,8.基金项目
国家自然科学基金面上项目(61170093) （61170093）
湖北省教育厅科学技术研究计划重点基金项目(D20141603) （D20141603）
