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Toward Virtual Machine Packing Optimization Based on Genetic Algorithm

  • Hidemoto Nakada
  • Takahiro Hirofuchi
  • Hirotaka Ogawa
  • Satoshi Itoh
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5518)

Abstract

To enable efficient resource provisioning in HaaS (Hardware as a Service) cloud systems, virtual machine packing, which migrate virtual machines to minimize running real node, is essential. The virtual machine packing problem is a multi-objective optimization problem with several parameters and weights on parameters change dynamically subject to cloud provider preference. We propose to employ Genetic Algorithm (GA) method, that is one of the meta-heuristics. We implemented a prototype Virtual Machine packing optimization mechanism on Grivon, which is a virtual cluster management system we have been developing. The preliminary evaluation implied the GA method is promising for the problem.

Keywords

Genetic Algorithm Virtual Machine Cloud System Genetic Algorithm Method Virtual Machine Migration 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Hidemoto Nakada
    • 1
  • Takahiro Hirofuchi
    • 1
  • Hirotaka Ogawa
    • 1
  • Satoshi Itoh
    • 1
  1. 1.National Institute of Advanced Industrial Science and Technology, TukubaIbarakiJapan

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