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Virtual Machine Migration in Cloud Infrastructures: Problem Formalization and Policies Proposal

Papadopoulos, Alessandro Vittorio LU and Maggio, Martina LU (2016) 54th IEEE Conference on Decision and Control In 2015 54th IEEE Conference on Decision and Control (CDC) p.6698-6705
Abstract
Cloud computing has dramatically simplified the deployment of new software and, indeed, the number of applications that are hosted by cloud providers every day is increasing. The data center owner should provide computing capacity to a set of customers, each of them powering up and down virtual machines dynamically, to handle variations in the incoming requests. Cloud providers, however, should also optimize for quantities like energy consumption and managements costs, therefore trying to host all the customers virtual machines with the fewest amount of physical hardware machines possible. This leads to virtual machine co-location and potential performance inefficiency. To limit the inefficiency, virtual machines are migrated from one... (More)
Cloud computing has dramatically simplified the deployment of new software and, indeed, the number of applications that are hosted by cloud providers every day is increasing. The data center owner should provide computing capacity to a set of customers, each of them powering up and down virtual machines dynamically, to handle variations in the incoming requests. Cloud providers, however, should also optimize for quantities like energy consumption and managements costs, therefore trying to host all the customers virtual machines with the fewest amount of physical hardware machines possible. This leads to virtual machine co-location and potential performance inefficiency. To limit the inefficiency, virtual machines are migrated from one physical machine to another when overload conditions are detected. This paper analyzes the problem of virtual machine migration and presents some heuristic solutions to decide when to migrate a virtual machine from a physical machine to a different one. Experimental results show the differences between the proposed heuristics, providing a basis for a fair comparison among the techniques. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
2015 54th IEEE Conference on Decision and Control (CDC)
pages
6698 - 6705
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
conference name
54th IEEE Conference on Decision and Control
external identifiers
  • Scopus:84962013936
ISBN
978-1-4799-7884-7
DOI
10.1109/CDC.2015.7403274
project
LCCC
language
English
LU publication?
yes
id
346708d2-6ac5-498e-b8f6-aa7b54ae80ed (old id 7852890)
date added to LUP
2015-09-04 09:09:35
date last changed
2016-10-13 05:10:08
@misc{346708d2-6ac5-498e-b8f6-aa7b54ae80ed,
  abstract     = {Cloud computing has dramatically simplified the deployment of new software and, indeed, the number of applications that are hosted by cloud providers every day is increasing. The data center owner should provide computing capacity to a set of customers, each of them powering up and down virtual machines dynamically, to handle variations in the incoming requests. Cloud providers, however, should also optimize for quantities like energy consumption and managements costs, therefore trying to host all the customers virtual machines with the fewest amount of physical hardware machines possible. This leads to virtual machine co-location and potential performance inefficiency. To limit the inefficiency, virtual machines are migrated from one physical machine to another when overload conditions are detected. This paper analyzes the problem of virtual machine migration and presents some heuristic solutions to decide when to migrate a virtual machine from a physical machine to a different one. Experimental results show the differences between the proposed heuristics, providing a basis for a fair comparison among the techniques.},
  author       = {Papadopoulos, Alessandro Vittorio and Maggio, Martina},
  isbn         = {978-1-4799-7884-7 },
  language     = {eng},
  pages        = {6698--6705},
  publisher    = {ARRAY(0xa680ef0)},
  series       = {2015 54th IEEE Conference on Decision and Control (CDC) },
  title        = {Virtual Machine Migration in Cloud Infrastructures: Problem Formalization and Policies Proposal},
  url          = {http://dx.doi.org/10.1109/CDC.2015.7403274},
  year         = {2016},
}