An Automatic Decision-Making Mechanism for Virtual Machine Live Migration in Private Clouds
Due to the increasing number of computer hosts deployed in an enterprise, automatic management of electronic applications is inevitable. To provide diverse services, there will be increases in procurement, maintenance, and electricity costs. Virtualization technology is getting popular in cloud comp...
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Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2014/328536 |
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doaj-ea3b4778aebe45bdb4319b0e9e6db2802020-11-24T21:12:40ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472014-01-01201410.1155/2014/328536328536An Automatic Decision-Making Mechanism for Virtual Machine Live Migration in Private CloudsMing-Tsung Kao0Yu-Hsin Cheng1Shang-Juh Kao2Department of Computer Science and Engineering, National Chung-Hsing University, 250 Kuo-Kuang Rd., 40227 Taichung City, TaiwanDepartment of Information Networking and System Administration, 1 Ling Tung Road, Taichung, TaiwanDepartment of Computer Science and Engineering, National Chung-Hsing University, 250 Kuo-Kuang Rd., 40227 Taichung City, TaiwanDue to the increasing number of computer hosts deployed in an enterprise, automatic management of electronic applications is inevitable. To provide diverse services, there will be increases in procurement, maintenance, and electricity costs. Virtualization technology is getting popular in cloud computing environment, which enables the efficient use of computing resources and reduces the operating cost. In this paper, we present an automatic mechanism to consolidate virtual servers and shut down the idle physical machines during the off-peak hours, while activating more machines at peak times. Through the monitoring of system resources, heavy system loads can be evenly distributed over physical machines to achieve load balancing. By integrating the feature of load balancing with virtual machine live migration, we successfully develop an automatic private cloud management system. Experimental results demonstrate that, during the off-peak hours, we can save power consumption of about 69 W by consolidating the idle virtual servers. And the load balancing implementation has shown that two machines with 80% and 40% CPU loads can be uniformly balanced to 60% each. And, through the use of preallocated virtual machine images, the proposed mechanism can be easily applied to a large amount of physical machines.http://dx.doi.org/10.1155/2014/328536 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ming-Tsung Kao Yu-Hsin Cheng Shang-Juh Kao |
spellingShingle |
Ming-Tsung Kao Yu-Hsin Cheng Shang-Juh Kao An Automatic Decision-Making Mechanism for Virtual Machine Live Migration in Private Clouds Mathematical Problems in Engineering |
author_facet |
Ming-Tsung Kao Yu-Hsin Cheng Shang-Juh Kao |
author_sort |
Ming-Tsung Kao |
title |
An Automatic Decision-Making Mechanism for Virtual Machine Live Migration in Private Clouds |
title_short |
An Automatic Decision-Making Mechanism for Virtual Machine Live Migration in Private Clouds |
title_full |
An Automatic Decision-Making Mechanism for Virtual Machine Live Migration in Private Clouds |
title_fullStr |
An Automatic Decision-Making Mechanism for Virtual Machine Live Migration in Private Clouds |
title_full_unstemmed |
An Automatic Decision-Making Mechanism for Virtual Machine Live Migration in Private Clouds |
title_sort |
automatic decision-making mechanism for virtual machine live migration in private clouds |
publisher |
Hindawi Limited |
series |
Mathematical Problems in Engineering |
issn |
1024-123X 1563-5147 |
publishDate |
2014-01-01 |
description |
Due to the increasing number of computer hosts deployed in an enterprise, automatic management of electronic applications is inevitable. To provide diverse services, there will be increases in procurement, maintenance, and electricity costs. Virtualization technology is getting popular in cloud computing environment, which enables the efficient use of computing resources and reduces the operating cost. In this paper, we present an automatic mechanism to consolidate virtual servers and shut down the idle physical machines during the off-peak hours, while activating more machines at peak times. Through the monitoring of system resources, heavy system loads can be evenly distributed over physical machines to achieve load balancing. By integrating the feature of load balancing with virtual machine live migration, we successfully develop an automatic private cloud management system. Experimental results demonstrate that, during the off-peak hours, we can save power consumption of about 69 W by consolidating the idle virtual servers. And the load balancing implementation has shown that two machines with 80% and 40% CPU loads can be uniformly balanced to 60% each. And, through the use of preallocated virtual machine images, the proposed mechanism can be easily applied to a large amount of physical machines. |
url |
http://dx.doi.org/10.1155/2014/328536 |
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