基于负载不确定性的虚拟机整合方法

doi:10.11772/j.issn.1001-9081.2017112741

计算机应用 ›› 2018, Vol. 38 ›› Issue (6): 1658-1664.DOI: 10.11772/j.issn.1001-9081.2017112741

基于负载不确定性的虚拟机整合方法

李双俐¹, 李志华^1,2, 喻新荣¹, 闫成雨¹

1. 江南大学物联网工程学院, 江苏无锡 214122;
2. 物联网应用技术教育部工程研究中心(江南大学), 江苏无锡 214122

收稿日期:2017-11-20 修回日期:2018-01-10 出版日期:2018-06-10 发布日期:2018-06-13
通讯作者: 李志华
作者简介:李双俐(1992-),女,河南新乡人,硕士研究生,CCF会员,主要研究方向:云计算、分布式计算;李志华(1969-),男,湖南保靖人,副教授,博士,主要研究方向:计算机网络、信息安全、数据挖掘;喻新荣(1992-),男,江苏南通人,硕士研究生,主要研究方向:云计算、并行计算、分布式计算;闫成雨(1992-),男,江苏徐州人,硕士,主要研究方向:云计算、网格与分布式计算。
基金资助:
江苏省科技厅产学研联合创新基金资助项目（BY2013015-23）。

Workload uncertainty-based virtual machine consolidation method

LI Shuangli¹, LI Zhihua^1,2, YU Xinrong¹, YAN Chengyu¹

1. School of Internet of Things Engineering, Jiangnan University, Wuxi Jiangsu 214122, China;
2. Engineering Research Center of IoT Technology Application Ministry of Education(Jiangnan University), Wuxi Jiangsu 214122, China

Received:2017-11-20 Revised:2018-01-10 Online:2018-06-10 Published:2018-06-13
Supported by:
This work is partially supported by the Innovations Fund for the Integration of Industry, Education and Research of Jiangsu Province(BY2013015-23).

摘要/Abstract

摘要： 物理主机工作负载的不确定性容易造成物理主机过载和资源利用率低，从而影响数据中心的能源消耗和服务质量。针对该问题，通过分析物理主机的工作负载记录与虚拟机资源请求的历史数据，提出了基于负载不确定性的虚拟机整合（WU-VMC）方法。为了稳定云数据中心各主机的工作负载，该方法首先利用虚拟机的资源请求拟合物理主机工作负载，并利用梯度下降方法计算虚拟机与物理主机的虚拟机匹配度；然后，利用匹配度进行虚拟机整合，从而解决负载不确定造成的能耗增加和服务质量下降等问题。仿真实验结果表明，WU-VMC方法降低了数据中心的能源消耗，减少了虚拟机迁移次数，提高了数据中心的资源利用率及服务质量。

关键词: 云计算, 数据中心, 虚拟机整合, 稳定负载, 梯度下降

Abstract: The uncertainty of workload in physical hosts easily leads to high overloaded risk and low resource utilization in physical hosts, which will further affect the energy consumption and service quality of data center. In order to solve this problem, a Workload Uncertainty-based Virtual Machine Consolidation (WU-VMC) method was proposed by analyzing the workload records of physical hosts and the historical data of virtual machine resource request. In order to stabilize the workload of each host in the cloud data center, firstly, the workloads of physical hosts were fitted according to resource requests of virtual machines, and the virtual machine matching degree between virtual machines and physical hosts was computed by using gradient descent method. Then, the virtual machines were integrated by using the matching degree to solve the problems such as increased energy consumption and decreased service quality which were caused by uncertain load. The simulation experimental results show that the proposed WU-VMC method can decrease energy consumption and virtual machine migration times of data center, improving the resource utilization and service quality of data center.

Key words: cloud computing, data center, virtual machine consolidation, stabilized workload, gradient descent

中图分类号:

TP393

李双俐, 李志华, 喻新荣, 闫成雨. 基于负载不确定性的虚拟机整合方法[J]. 计算机应用, 2018, 38(6): 1658-1664.

LI Shuangli, LI Zhihua, YU Xinrong, YAN Chengyu. Workload uncertainty-based virtual machine consolidation method[J]. Journal of Computer Applications, 2018, 38(6): 1658-1664.

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基于负载不确定性的虚拟机整合方法

Workload uncertainty-based virtual machine consolidation method

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