引用本文:郑瑛.云计算数据中心节能调度算法改进研究[J].西南大学学报(自然科学版),2019,41(12):135~142
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云计算数据中心节能调度算法改进研究
郑瑛
内蒙古民族大学 学术期刊社, 内蒙古 通辽 028043
摘要:
针对传统方法对云计算数据中心调度时能耗过高,虚拟机迁移次数过多等问题,本文提出一种新的云计算数据中心节能调度算法.采用面向实时任务的云计算数据中心节能调度算法,保证云数据中心任务完成率;为了进一步降低云数据中心的能耗,构建云计算数据中心功耗模型,分析云数据中心SLA协议违约率和虚拟机迁移功耗对数据中心的能耗影响,采用基于能耗感知的虚拟机节能调度算法合理安置和迁移虚拟机,使虚拟机安装在物理机后无任何负载较低节点,实现云计算数据中心的节能调度.模拟实验结果表明,本文算法与对比算法相比,大幅度降低了云计算数据中心的能耗,且虚拟机迁移次数少,可有效降低虚拟机多次迁移带来的额外支出,是一种有效的云数据中心节能调度算法.
关键词:  云计算  数据中心  节能调度  功耗模型  虚拟机  能耗感知
DOI:10.13718/j.cnki.xdzk.2019.12.018
分类号:TP308
基金项目:内蒙古自治区高等学校科学研究项目(NJZC16191).
Improvement of Energy-Saving Scheduling Algorithm in Cloud Computing Data Centers
ZHENG Ying
Academic Periodicals Agency, Inner Mongolia University for Nationalities, Tongliao Inner Mongolia 028043, China
Abstract:
Aiming at the problems of high energy consumption in cloud computing data center scheduling and excessive virtual machine migration of traditional methods, this paper proposes a new cloud computing data center energy-saving scheduling algorithm. A real-time task-oriented cloud computing data center energy-saving scheduling algorithm is adopted to ensure the completion rate of data center tasks. In order to further reduce the energy consumption of the data center, a cloud computing data center power consumption model is built, and the impact of the data center SLA protocol default rate and virtual machine migration power consumption on the energy consumption of the data center is analyzed An energy-awareness-based virtual machine energy-saving scheduling algorithm is used to properly locate and migrate the virtual machine, so that the virtual machine is installed on the physical machine without any nodes with a lower load, and the energy-saving scheduling of the cloud computing data center is realized. Simulation results show that compared with the contrast algorithm, the proposed algorithm significantly reduces the energy consumption of data centers in cloud computing and the number of virtual machine migration is less, which can effectively reduce the additional costs of multiple virtual machine migration. Therefore, it is an effective energy-saving scheduling algorithm for data centers.
Key words:  cloud computing  data center  energy-saving scheduling  power consumption model  virtual machine  energy consumption perception
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