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Cluster Computing

, Volume 20, Issue 3, pp 2083–2094 | Cite as

A network aware approach for the scheduling of virtual machine migration during peak loads

  • Martin DugganEmail author
  • Jim Duggan
  • Enda Howley
  • Enda Barrett
Article

Abstract

Live virtual machine migration can have a major impact on how a cloud system performs, as it consumes significant amounts of network resources such as bandwidth. Migration contributes to an increase in consumption of network resources which leads to longer migration times and ultimately has a detrimental effect on the performance of a cloud computing system. Most industrial approaches use ad-hoc manual policies to migrate virtual machines. In this paper, we propose an autonomous network aware live migration strategy that observes the current demand level of a network and performs appropriate actions based on what it is experiencing. The Artificial Intelligence technique known as Reinforcement Learning acts as a decision support system, enabling an agent to learn optimal scheduling times for live migration while analysing current network traffic demand. We demonstrate that an autonomous agent can learn to utilise available resources when peak loads saturate the cloud network.

Keywords

Live migration Bandwidth Reinforcement learning Network flow Peak load 

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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  • Martin Duggan
    • 1
    Email author
  • Jim Duggan
    • 1
  • Enda Howley
    • 1
  • Enda Barrett
    • 1
  1. 1.College of Engineering and InformaticsNational University of IrelandGalwayIreland

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