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A Random Key Genetic Algorithm for Live Migration of Multiple Virtual Machines in Data Centers

  • Tusher Kumer Sarker
  • Maolin Tang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8835)

Abstract

Live migration of multiple Virtual Machines (VMs) has become an integral management activity in data centers for power saving, load balancing and system maintenance. While state-of-the-art live migration techniques focus on the improvement of migration performance of an independent single VM, only a little has been investigated to the case of live migration of multiple interacting VMs. Live migration is mostly influenced by the network bandwidth and arbitrarily migrating a VM which has data inter-dependencies with other VMs may increase the bandwidth consumption and adversely affect the performances of subsequent migrations. In this paper, we propose a Random Key Genetic Algorithm (RKGA) that efficiently schedules the migration of a given set of VMs accounting both inter-VM dependency and data center communication network. The experimental results show that the RKGA can schedule the migration of multiple VMs with significantly shorter total migration time and total downtime compared to a heuristic algorithm.

Keywords

Live migration virtual machine migration time downtime random key genetic algorithm 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Tusher Kumer Sarker
    • 1
  • Maolin Tang
    • 1
  1. 1.School of Electrical Engineering and Computer ScienceQueensland University of TechnologyBrisbaneAustralia

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