摘要
由于云平台承载系统的计算能力是动态变化的,导致传统任务调度方法难以充分利用云资源,提出以云平台承载系统时基于粒子群优化算法的云任务调度方法。以任务完成时间最短、任务完成成本最小、负载均衡为目标,构建一个以云平台承载系统时云任务调度数学模型,采用粒子群优化算法求解模型,得到最佳以云平台承载系统时云任务调度策略。实验结果表明,设计方法下服务资源负载均衡度指标数值为0.23,该方法可以很好地解决以云平台承载系统时云任务调度问题。
Due to the dynamic changes in computing power of cloud platform hosting systems,traditional task scheduling methods find it difficultto fully utilize cloud resources.Therefore,a cloud task scheduling method based on particle swarm optimization algorithm is proposed when hosting systems on cloud platforms.A mathematical model for cloud task scheduling is constructed with the goals of minimizing task completion time,minimizing task completion cost,and load balancing when the system is hosted on a cloud platform.The model is solved using particle swarm optimization algorithm to obtain the optimal cloud task scheduling strategy when the system is hosted on a cloud platform.The experimental results show that the service resource load balancing index value under the design method is 0.23,which can effectively solve the cloud task scheduling problem when the system is hosted on a cloud platform.
作者
赵润程
郑明钊
ZHAO Runcheng;ZHENG Mingzhao(China Mobile Communications Group Design Institute Co.,LTD.Shandong Branch,Jinan 250013,China)
出处
《长江信息通信》
2025年第1期213-215,共3页
Changjiang Information & Communications
关键词
云平台承载系统
粒子群优化算法
云任务
算力调度
调度方法
Cloud platform bearer system
Particle swarm optimization algorithm
Cloud tasks
Computational power scheduling
Scheduling method
