感知应用特征与网络带宽的虚拟机在线迁移优化策略

李湘; 陈宁江; 杨尚林; 李华

doi:10.11959/j.issn.1000-436x.2017268

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感知应用特征与网络带宽的虚拟机在线迁移优化策略

学术论文 | 更新时间：2024-06-05

- 感知应用特征与网络带宽的虚拟机在线迁移优化策略
- Optimization strategy of virtual machine online migration with awareness of application characteristics and network bandwidth migration
- 通信学报 2017年38卷第Z2期页码：147-155
- 作者机构：
  
  1. 广西大学计算机与电子信息学院，广西南宁 530004
  2. 广西大学广西多媒体通信与网络技术重点实验室，广西南宁 530004
- 作者简介：
  
  [ "李湘（1991-），女，广西贺州人，广西大学硕士生，主要研究方向为软件工程、网络分布式计算。" ]
  [ "陈宁江（1975-），男，广西南宁人，博士，广西大学教授，主要研究方向为软件工程、网络分布式计算、云计算、大数据等。" ]
  [ "杨尚林（1992-），男，山东腾州人，广西大学硕士生，主要研究方向为软件工程、网络分布式计算。" ]
  [ "李华（1994-），男，广西北海人，广西大学硕士生，主要研究方向为网络软件工程。" ]
- 基金信息：
  
  国家自然科学基金资助项目(61363003);国家科技支撑计划课题基金资助项目(2015BAH55F02);广西自然科学基金资助项目(2017GXNSFAA198141)
- DOI：10.11959/j.issn.1000-436x.2017268
  中图分类号： TP393
- 网络出版日期：2017-11，
  
  纸质出版日期：2017-11-25
- 稿件说明：
移动端阅览
李湘, 陈宁江, 杨尚林, 等. 感知应用特征与网络带宽的虚拟机在线迁移优化策略[J]. 通信学报, 2017,38(Z2):147-155.

Xiang LI, Ning-jiang CHEN, Shang-lin YANG, et al. Optimization strategy of virtual machine online migration with awareness of application characteristics and network bandwidth migration[J]. Journal on communications, 2017, 38(Z2): 147-155.
李湘, 陈宁江, 杨尚林, 等. 感知应用特征与网络带宽的虚拟机在线迁移优化策略[J]. 通信学报, 2017,38(Z2):147-155. DOI： 10.11959/j.issn.1000-436x.2017268.

Xiang LI, Ning-jiang CHEN, Shang-lin YANG, et al. Optimization strategy of virtual machine online migration with awareness of application characteristics and network bandwidth migration[J]. Journal on communications, 2017, 38(Z2): 147-155. DOI： 10.11959/j.issn.1000-436x.2017268.

摘要

首先对虚拟机在迁移过程中，内存脏页面产生数量与不同应用特征的密切关系进行了实验验证。在感知不同的虚拟机应用特征环境的基础上，使用GM(1

N)灰色预测模型对每次迭代周期产生的内存脏页面数进行预测。同时使用残差修正进行误差调整，使预测结果更可靠，结合预测的内存脏页面数量进行网络带宽动态预留调整。实验表明：与传统的pre-copy策略相比，本方法在含网络密集型应用或内存密集应用的虚拟机迁移时，能够有效提高网络性能，降低迁移时间。

Abstract

Firstly the experiments to verify the relationship between the number of dirty memory pages and application characteristics which exist in virtual machine migration was conducted.Then

different virtual machine application characteristics were perceived

with which the number of dirty memory pages produced during the migrations was predicted by the use of GM(1

N) grey prediction model.At the same time

using residual correction to adjust error makes results more reliable.According to the prediction of memory dirty pages

network bandwidth was adjusted and reserved.Compared with the traditional pre-copy strategy

the given experiments show that the optimized strategy proposed can improve the performance of network and reduce migratory cost for the memory-intensive and network-intensive applications.

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Keywords

references

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基于安全等级的虚拟机动态迁移方法