基于OpenStack私有云平台的资源动态调度方法  

Dynamic Resource Scheduling Method for OpenStack-Based Private Cloud Platform

作　　者：李逸凡 吴怡 杨辉 LI Yifan;WU Yi;YANG Hui(College of Optoelectronics and Information Engineering,Fujian Normal University,Fuzhou 350117,China;Fujian Centerm Information Co.,Ltd,Fuzhou 350108,China)

机构地区：[1]福建师范大学光电与信息工程学院,福建福州350117 [2]福建升腾资讯有限公司,福建福州350108

出　　处：《福建师范大学学报(自然科学版)》2025年第2期1-8,共8页Journal of Fujian Normal University:Natural Science Edition

基　　金：福建省中央引导地方科技发展资金项目(2024L3007、2021L3010);福建省促进海洋与渔业产业高质量发展专项资金项目(FJHYF-ZH-2023-03);福建省省直单位教育和科研专项项目(闽财指[2023]834号)。

摘　　要：针对OpenStack云平台下的计算资源动态调度问题,提出一种基于CPU、内存和存储的综合负载均值算法。该算法通过实时监测和评估计算节点的资源利用率,动态调整虚拟机的部署与迁移策略,以实现云数据中心资源的负载均衡。结果表明,与传统调度策略相比,该算法能够有效降低平台各项资源的使用负载,优化虚拟机的部署效率,从而提高云平台的整体性能。Aiming at the dynamic scheduling of computing resources in the OpenStack cloud platform,this paper proposes a comprehensive load average algorithm based on CPU,memory,and storage.By real-time monitoring and evaluating the resource utilization of computing nodes,the algorithm dynamically adjusts the deployment and migration strategies of virtual machines,thereby achieving load balancing in cloud data centers.Experimental results demonstrate that,compared with traditional scheduling strategies,this algorithm effectively reduces the usage load of various resources on the platform,optimizes virtual machine deployment efficiency,and consequently enhances the overall performance of the cloud platform.

关 键 词：OPENSTACK 私有云 云平台 资源调度 蚁群算法 

分 类 号：TN99[电子电信—信号与信息处理]