Optimization of virtual resource deployment strategy in container cloud

doi:10.11772/j.issn.1001-9081.2018081662

Journal of Computer Applications ›› 2019, Vol. 39 ›› Issue (3): 784-789.DOI: 10.11772/j.issn.1001-9081.2018081662

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Optimization of virtual resource deployment strategy in container cloud

LI Qirui^1,2, PENG Zhiping², CUI Delong², HE Jieguang²

1. College of Mathematics and Information Science, Guangzhou University, Guangzhou Guangdong 510006, China;
2. College of Computer and Electronic Information, Guangdong University of Petrochemical Technology, Maoming Guangdong 525000, China

Received:2018-08-10 Revised:2018-09-10 Online:2019-03-10 Published:2019-03-11
Contact: 彭志平
Supported by:
This work is partially supported by the National Natural Science Foundation of China (61672174, 61772145), the Science and Technology Project of Guangdong Province (2017ZC0346), the Open Funds of Guangdong Research Center of Cloud Robot (Oriented to Petrochemical Industry) (650007), the Key Platform and Scientific Research Project of Guangdong Education Department (2016KQNCX105, 2017KTSCX128).

容器云环境虚拟资源配置策略的优化

李启锐^1,2, 彭志平², 崔得龙², 何杰光²

1. 广州大学数学与信息科学学院, 广州 510006;
2. 广东石油化工学院计算机与电子信息学院, 广东茂名 525000

作者简介:李启锐(1982-),男,广西玉林人,副教授,博士研究生,CCF会员,主要研究方向:云计算资源调度、通信安全;彭志平(1969-),男,福建泉州人,教授,博士,主要研究方向:云计算资源调度、机器学习;崔得龙(1978-),男,甘肃兰州人,副教授,硕士,主要研究方向:云计算资源调度;何杰光(1981-),男,广东茂名人,讲师,博士,主要研究方向:云计算资源调度。
基金资助:
国家自然科学基金资助项目（61672174，61772145）；广东省科技计划项目（2017ZC0346）；广东省云机器人（石油化工）工程技术研究中心开放基金资助项目（650007）；广东省教育厅重点平台及科研项目（2016KQNCX105，2017KTSCX128）。

Abstract

Abstract: Aiming at high energy consumption of data center in container cloud, a virtual resource deployment strategy based on host selection algorithm with Power Full (PF) was proposed. Firstly, the allocation and migration scheme of virtual resource in container cloud was proposed and the significant impact of host selection strategy on energy consumption of data center was found. Secondly, by studying the mathematical relationship between the utilization of host and the utilization of containers, between the utilization of host and the utilization of virtual machines and between the utilization of host and energy consumption of data center, a mathematical model of the energy consumption of data center in container cloud was constructed and an optimization objective function was defined. Finally, the function of host's energy consumption was simulated using linear interpolation method, and a host selection algorithm with PF was proposed according to the clustering property of the objects. Simulation results show that compared with First Fit (FF), Least Full (LF) and Most Full (MF), the energy consumption of the proposed algorithm is averagely reduced by 45%,53% and 49% respectively in the computing service of regular tasks and different host clusters; is averagely reduced by 56%,46% and 58% respectively in the computing service of regular tasks and same host cluster; is averagely reduced by 32%,24% and 12% respectively in the computing service of irregular tasks and different host clusters. The results indicate that the proposed algorithm realizes reasonable virtual resource deployment in container cloud, and has advantage in data center energy saving.

Key words: cloud computing, container, allocation of virtual resource, energy consumption of data center, utilization of resource

摘要： 针对容器化云环境中数据中心能耗较高的问题，提出了一种基于最佳能耗优先（Power Full，PF）物理机选择算法的虚拟资源配置策略。首先，提出容器云虚拟资源的配置和迁移方案，发现物理机选择策略对数据中心能耗有重要影响；其次，通过研究主机利用率与容器利用率，主机利用率与虚拟机利用率，主机利用率与数据中心能耗之间的数学关系，建立容器云数据中心能耗的数学模型，定义出优化目标函数；最后，通过对物理机的能耗函数使用线性插值进行模拟，依据邻近事物相类似的特性，提出改进的最佳能耗优先物理机选择算法。仿真实验将此算法与先来先得（First Fit，FF）、最低利用率优先（Least Fit，LF）、最高利用率优先（Most Full，MF）进行比较，实验结果表明，在有规律不同物理机群的计算服务中，其能耗比FF、LF、MF分别平均降低45%、53%和49%；在有规律相同物理机群的计算服务中，其能耗比FF、LF、MF分别平均降低56%、46%和58%；在无规律不同物理机群的计算服务中，其能耗比FF、LF、MF分别平均降低32%、24%和12%。所提算法实现了对容器云虚拟资源的合理配置，且在数据中心节能方面具有优越性。

关键词: 云计算, 容器, 虚拟资源配置, 数据中心能耗, 资源利用率

CLC Number:

TP391

LI Qirui, PENG Zhiping, CUI Delong, HE Jieguang. Optimization of virtual resource deployment strategy in container cloud[J]. Journal of Computer Applications, 2019, 39(3): 784-789.

李启锐, 彭志平, 崔得龙, 何杰光. 容器云环境虚拟资源配置策略的优化[J]. 计算机应用, 2019, 39(3): 784-789.

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Optimization of virtual resource deployment strategy in container cloud

容器云环境虚拟资源配置策略的优化

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