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Multi-Objective Dynamic Virtual Machine Consolidation in the Cloud Using Ant Colony System

Adnan Ashraf, Ivan Porres, Multi-Objective Dynamic Virtual Machine Consolidation in the Cloud Using Ant Colony System. International Journal of Parallel, Emergent and Distributed Systems , 1–18, 2017.

http://dx.doi.org/10.1080/17445760.2017.1278601

Abstract:

In this paper, we present a novel multi-objective ant colony system algorithm for virtual machine (VM) consolidation in cloud data centres. The proposed algorithm builds VM migration plans, which are then used to minimise over-provisioning of physical machines (PMs) by consolidating VMs on under-utilised PMs. It optimises two objectives that are ordered by their importance. The first and foremost objective in the proposed algorithm is to maximise the number of released PMs. Moreover, since VM migration is a resource-intensive operation, it also tries to minimise the number of VM migrations. The proposed algorithm is empirically evaluated in a series of experiments. The experimental results show that the proposed algorithm provides an efficient solution for VM consolidation in cloud data centres. Moreover, it outperforms two existing ant colony optimization-based VM consolidation algorithms in terms of number of released PMs and number of VM migrations.

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BibTeX entry:

@ARTICLE{jAsPo17a,
  title = {Multi-Objective Dynamic Virtual Machine Consolidation in the Cloud Using Ant Colony System},
  author = {Ashraf, Adnan and Porres, Ivan},
  journal = {International Journal of Parallel, Emergent and Distributed Systems},
  publisher = {Taylor & Francis},
  pages = {1–18},
  year = {2017},
  keywords = {Virtual machines, consolidation, metaheuristic, ant colony system, cloud computing},
  ISSN = {1744-5779},
}

Belongs to TUCS Research Unit(s): Software Engineering Laboratory (SE Lab)

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