A modified max-min ant colony optimization algorithm for virtual machines replacement in cloud datacenter

  • Tiantian Ren
  • , Xinli Huang*
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

With the increasing scale of cloud datacenters, the volumes of traffic flows inside a single datacenter become larger. An effective virtual machine (VM) replacement among physical machines (PMs) can improve resource utilization rate and reduce overall network cost in cloud datacenters. In this paper, we propose a Modified Max-Min Ant Colony Optimization (M3ACO) algorithm which can be used to solve the VMs replacement problem. Furthermore, we apply the M3ACO algorithm into a new framework based on Software Defined Network (SDN), which provides an integrated solution for resource optimization problem in cloud datacenters.

Original languageEnglish
Title of host publication2014 IEEE 33rd International Performance Computing and Communications Conference, IPCCC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479975754
DOIs
StatePublished - 20 Jan 2015
Event33rd IEEE International Performance Computing and Communications Conference, IPCCC 2014 - Austin, United States
Duration: 5 Dec 20147 Dec 2014

Publication series

Name2014 IEEE 33rd International Performance Computing and Communications Conference, IPCCC 2014
Volume2014-January

Conference

Conference33rd IEEE International Performance Computing and Communications Conference, IPCCC 2014
Country/TerritoryUnited States
CityAustin
Period5/12/147/12/14

Keywords

  • Ant Colony Optimization (ACO)
  • Software Defined Network (SDN)
  • VMs replacement
  • cloud datacenter
  • network cost

Fingerprint

Dive into the research topics of 'A modified max-min ant colony optimization algorithm for virtual machines replacement in cloud datacenter'. Together they form a unique fingerprint.

Cite this