A Fast Approach of Provisioning Virtual Machines by Using Image Content Similarity in Cloud

To quickly provision multiple virtual machines (VMs) is a challenge in nowadays cloud data centers (CDCs). By utilizing the content similarity among the virtual machine image (VMI) files, the amount of data transferred in the VM provisioning is reduced, and hence, the provisioning time can be shorte...

Full description

Bibliographic Details
Main Authors: Huixi Li, Shaokai Wang, Chang Ruan
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8684951/
id doaj-0df460ee3dc743ebac4a0027e806d7fc
record_format Article
spelling doaj-0df460ee3dc743ebac4a0027e806d7fc2021-03-29T22:17:23ZengIEEEIEEE Access2169-35362019-01-017450994510910.1109/ACCESS.2019.29075968684951A Fast Approach of Provisioning Virtual Machines by Using Image Content Similarity in CloudHuixi Li0Shaokai Wang1Chang Ruan2https://orcid.org/0000-0003-3576-1208Information Science School, Guangdong University of Finance and Economics, Guangzhou, ChinaSchool of Computer Science and Engineering, Central South University, Changsha, ChinaSchool of Computer Science and Engineering, Central South University, Changsha, ChinaTo quickly provision multiple virtual machines (VMs) is a challenge in nowadays cloud data centers (CDCs). By utilizing the content similarity among the virtual machine image (VMI) files, the amount of data transferred in the VM provisioning is reduced, and hence, the provisioning time can be shortened. Thus, minimizing the total amount of transferred VMI file data is helpful for accelerating the VM provisioning. Meanwhile, packing the VMs into the minimum number of physical machines (PMs) is also crucial for the CDCs. To solve these two problems at the same time, we propose a heuristic algorithm, called fast balance placement (FBP), by utilizing several tables to precompute and store the similarity relationships among different VMI files. Comparing to the balance-placement algorithm, the simulation results show that FBP uses less PMs to pack the VMs and its running time is shorter, and it transfers almost the same amount of the VMI file data.https://ieeexplore.ieee.org/document/8684951/Virtual machine provisioningvirtual machine packingvirtual machine imagecontent similarity
collection DOAJ
language English
format Article
sources DOAJ
author Huixi Li
Shaokai Wang
Chang Ruan
spellingShingle Huixi Li
Shaokai Wang
Chang Ruan
A Fast Approach of Provisioning Virtual Machines by Using Image Content Similarity in Cloud
IEEE Access
Virtual machine provisioning
virtual machine packing
virtual machine image
content similarity
author_facet Huixi Li
Shaokai Wang
Chang Ruan
author_sort Huixi Li
title A Fast Approach of Provisioning Virtual Machines by Using Image Content Similarity in Cloud
title_short A Fast Approach of Provisioning Virtual Machines by Using Image Content Similarity in Cloud
title_full A Fast Approach of Provisioning Virtual Machines by Using Image Content Similarity in Cloud
title_fullStr A Fast Approach of Provisioning Virtual Machines by Using Image Content Similarity in Cloud
title_full_unstemmed A Fast Approach of Provisioning Virtual Machines by Using Image Content Similarity in Cloud
title_sort fast approach of provisioning virtual machines by using image content similarity in cloud
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2019-01-01
description To quickly provision multiple virtual machines (VMs) is a challenge in nowadays cloud data centers (CDCs). By utilizing the content similarity among the virtual machine image (VMI) files, the amount of data transferred in the VM provisioning is reduced, and hence, the provisioning time can be shortened. Thus, minimizing the total amount of transferred VMI file data is helpful for accelerating the VM provisioning. Meanwhile, packing the VMs into the minimum number of physical machines (PMs) is also crucial for the CDCs. To solve these two problems at the same time, we propose a heuristic algorithm, called fast balance placement (FBP), by utilizing several tables to precompute and store the similarity relationships among different VMI files. Comparing to the balance-placement algorithm, the simulation results show that FBP uses less PMs to pack the VMs and its running time is shorter, and it transfers almost the same amount of the VMI file data.
topic Virtual machine provisioning
virtual machine packing
virtual machine image
content similarity
url https://ieeexplore.ieee.org/document/8684951/
work_keys_str_mv AT huixili afastapproachofprovisioningvirtualmachinesbyusingimagecontentsimilarityincloud
AT shaokaiwang afastapproachofprovisioningvirtualmachinesbyusingimagecontentsimilarityincloud
AT changruan afastapproachofprovisioningvirtualmachinesbyusingimagecontentsimilarityincloud
AT huixili fastapproachofprovisioningvirtualmachinesbyusingimagecontentsimilarityincloud
AT shaokaiwang fastapproachofprovisioningvirtualmachinesbyusingimagecontentsimilarityincloud
AT changruan fastapproachofprovisioningvirtualmachinesbyusingimagecontentsimilarityincloud
_version_ 1724191919595061248