微信服务号

微信订阅号

2025-4-9- 16
Home > Archive>Volume 27, Issue 2, 2016 >466-480. DOI:10.13328/j.cnki.jos.004878
PDF HTML XML Export Cite reminder
Virtual Machine Image Deduplication Method Based on Clustering
Author:
Affiliation:

Fund Project:

National Natural Science Foundation of China (61402450); National Key Technology Research and Development Program of China (2013BAH45F01); National High-Tech R&D Program of China (863) (2013AA041301); Beijing Natural Science Foundation of China (4154088)

  • Article
    • | |
  • Metrics
    • |
  • Reference
    • |
  • Related
    • |
  • Cited by
    • | |
  • Comments
    Abstract:

    Virtualization technology is becoming more and more prevalence with the rise of cloud computing. The physical machines for service hosting are gradually being replaced by virtual ones. Driven by reliability and flexibility considerations, virtual machine images increase sharply, and how to manage them efficiently and economically has become a big challenge. Since large amount of duplicated data blocks exist in different virtual machine images, an efficient deduplication method is vital to the virtual machine image management. The existing deduplication works are not very suitable for cloud environments as they employ time-consuming algorithms which can cause serious performance interference to the neighboring virtual machines. This paper proposes a local deduplication method which can greatly optimize the deduplication process of virtual machine. The main idea of the method is to convert the global deduplication to a local one, thus considerably reducing the space and time complexity. In this method, the images are classified into different groups through an improved k-means clustering algorithm according to image similarities. When a new image is entered, a sampling method is used to choose an appropriate group to perform the deduplication operation. Experiments show that this approach is robust and effective. It can significantly reduce (more than 50%) the performance interference to hosting virtual machine with an acceptable increase (about 1%) in disk space usage.

    Reference
    Related
    Cited by
Get Citation

徐继伟,张文博,魏峻,钟华,黄涛.一种基于聚类分组的虚拟机镜像去冗余方法.软件学报,2016,27(2):466-480

Copy
Share
Article Metrics
  • Abstract:3479
  • PDF: 5227
  • HTML: 1288
  • Cited by: 0
History
  • Received:April 23,2014
  • Revised:December 31,2014
  • Online: November 17,2015
Links:Institute of Software, CASChina Computer FederationCASNSFC
You are the first2034140Visitors
Copyright: Institute of Software, Chinese Academy of Sciences Beijing ICP No. 05046678-4
Address：4# South Fourth Street, Zhong Guan Cun, Beijing 100190,Postal Code：100190
Phone：010-62562563 Fax：010-62562533 Email：jos@iscas.ac.cn
Technical Support：Beijing Qinyun Technology Development Co., Ltd.

Beijing Public Network Security No. 11040202500063