Skip to content Skip to navigation
University of Warwick
  • Study
  • |
  • Research
  • |
  • Business
  • |
  • Alumni
  • |
  • News
  • |
  • About

University of Warwick
Publications service & WRAP

Highlight your research

  • WRAP
    • Home
    • Search WRAP
    • Browse by Warwick Author
    • Browse WRAP by Year
    • Browse WRAP by Subject
    • Browse WRAP by Department
    • Browse WRAP by Funder
    • Browse Theses by Department
  • Publications Service
    • Home
    • Search Publications Service
    • Browse by Warwick Author
    • Browse Publications service by Year
    • Browse Publications service by Subject
    • Browse Publications service by Department
    • Browse Publications service by Funder
  • Help & Advice
University of Warwick

The Library

  • Login
  • Admin

Developing resource consolidation frameworks for moldable virtual machines in clouds

Tools
- Tools
+ Tools

He, Ligang, Zou, Deqing, Zhang, Zhang, Chen, Chao, Jin, Hai and Jarvis, Stephen A. (2014) Developing resource consolidation frameworks for moldable virtual machines in clouds. Future Generation Computer Systems, Volume 32 . pp. 69-81. doi:10.1016/j.future.2012.05.015 ISSN 0167-739X.

[img]
Preview
PDF
WRAP_fgcs-cloudmanagement-revised.pdf - Accepted Version - Requires a PDF viewer.
Available under License Creative Commons Attribution Non-commercial No Derivatives 4.0.

Download (665Kb) | Preview
Official URL: http://dx.doi.org/10.1016/j.future.2012.05.015

Request Changes to record.

Abstract

This paper considers the scenario where multiple clusters of Virtual Machines (i.e., termed Virtual Clusters) are hosted in a Cloud system consisting of a cluster of physical nodes. Multiple Virtual Clusters (VCs) cohabit in the physical cluster, with each VC offering a particular type of service for the incoming requests. In this context, VM consolidation, which strives to use a minimal number of nodes to accommodate all VMs in the system, plays an important role in saving resource consumption. Most existing consolidation methods proposed in the literature regard VMs as “rigid” during consolidation, i.e., VMs’ resource capacities remain unchanged. In VC environments, QoS is usually delivered by a VC as a single entity. Therefore, there is no reason why VMs’ resource capacity cannot be adjusted as long as the whole VC is still able to maintain the desired QoS. Treating VMs as “moldable” during consolidation may be able to further consolidate VMs into an even fewer number of nodes. This paper investigates this issue and develops a Genetic Algorithm (GA) to consolidate moldable VMs. The GA is able to evolve an optimized system state, which represents the VM-to-node mapping and the resource capacity allocated to each VM. After the new system state is calculated by the GA, the Cloud will transit from the current system state to the new one. The transition time represents overhead and should be minimized. In this paper, a cost model is formalized to capture the transition overhead, and a reconfiguration algorithm is developed to transit the Cloud to the optimized system state with low transition overhead. Experiments have been conducted to evaluate the performance of the GA and the reconfiguration algorithm.

Item Type: Journal Article
Subjects: Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
Divisions: Faculty of Science, Engineering and Medicine > Science > Computer Science
Library of Congress Subject Headings (LCSH): Cloud computing -- Genetic algorithms -- Research
Journal or Publication Title: Future Generation Computer Systems
Publisher: Elsevier Science BV
ISSN: 0167-739X
Official Date: March 2014
Dates:
DateEvent
March 2014Published
25 May 2012Available
30 October 2011Submitted
Volume: Volume 32
Page Range: pp. 69-81
DOI: 10.1016/j.future.2012.05.015
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
Date of first compliant deposit: 4 March 2016
Date of first compliant Open Access: 23 March 2016
Adapted As:
Embodied As: 1

Request changes or add full text files to a record

Repository staff actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics

twitter

Email us: wrap@warwick.ac.uk
Contact Details
About Us