Correlation-based virtual machine migration in dynamic cloud environments

Correlation-based virtual machine migration in dynamic cloud environments Virtual machine (VM) migration enables flexible and efficient resource management in modern data centers. Although various VM migration algorithms have been proposed to improve the utilization of physical resources in data centers, they generally focus on how to select VMs to be migrated only according to their resource requirements and ignore the relationship between the VMs and servers with respect to their varying resource usage as well as the time at which the VMs should be migrated. This may dramatically degrade the algorithm performance and increase the operating and the capital cost when the resource requirements of the VMs change dynamically over time. In this paper, we propose an integrated VM migration strategy to jointly consider and address these issues. First, we establish a service level agreement-based soft migration mechanism to significantly reduce the number of VM migrations. Then, we develop two algorithms to solve the VM and server selection issues, in which the correlation between the VMs and the servers is used to identify the appropriate VMs to be migrated and the destination servers for them. The experimental results obtained from extensive simulations show the effectiveness of the proposed algorithms compared to traditional schemes in terms of the rate of resource usage, the operating cost and the capital cost. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Photonic Network Communications Springer Journals

Correlation-based virtual machine migration in dynamic cloud environments

Loading next page...
 
/lp/springer_journal/correlation-based-virtual-machine-migration-in-dynamic-cloud-NtHCclKp9z
Publisher
Springer US
Copyright
Copyright © 2015 by Springer Science+Business Media New York
Subject
Computer Science; Computer Communication Networks; Electrical Engineering; Characterization and Evaluation of Materials
ISSN
1387-974X
eISSN
1572-8188
D.O.I.
10.1007/s11107-015-0539-6
Publisher site
See Article on Publisher Site

Abstract

Virtual machine (VM) migration enables flexible and efficient resource management in modern data centers. Although various VM migration algorithms have been proposed to improve the utilization of physical resources in data centers, they generally focus on how to select VMs to be migrated only according to their resource requirements and ignore the relationship between the VMs and servers with respect to their varying resource usage as well as the time at which the VMs should be migrated. This may dramatically degrade the algorithm performance and increase the operating and the capital cost when the resource requirements of the VMs change dynamically over time. In this paper, we propose an integrated VM migration strategy to jointly consider and address these issues. First, we establish a service level agreement-based soft migration mechanism to significantly reduce the number of VM migrations. Then, we develop two algorithms to solve the VM and server selection issues, in which the correlation between the VMs and the servers is used to identify the appropriate VMs to be migrated and the destination servers for them. The experimental results obtained from extensive simulations show the effectiveness of the proposed algorithms compared to traditional schemes in terms of the rate of resource usage, the operating cost and the capital cost.

Journal

Photonic Network CommunicationsSpringer Journals

Published: Aug 5, 2015

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 12 million articles from more than
10,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Unlimited reading

Read as many articles as you need. Full articles with original layout, charts and figures. Read online, from anywhere.

Stay up to date

Keep up with your field with Personalized Recommendations and Follow Journals to get automatic updates.

Organize your research

It’s easy to organize your research with our built-in tools.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve Freelancer

DeepDyve Pro

Price
FREE
$49/month

$360/year
Save searches from Google Scholar, PubMed
Create lists to organize your research
Export lists, citations
Access to DeepDyve database
Abstract access only
Unlimited access to over
18 million full-text articles
Print
20 pages/month
PDF Discount
20% off