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Task Based System Load Balancing Approach in Cloud Environments

  • Fahimeh Ramezani
  • Jie Lu
  • Farookh Hussain
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 214)

Abstract

Live virtual machine (VM) migration is a technique for transferring an active VM from one physical host to another without disrupting the VM. This technique has been proposed to reduce the downtime for migrated overload VMs. As VMs migration takes much more times and cost in comparison with tasks migration, this study develops a novel approach to confront with the problem of overload VM and achieving system load balancing, by assigning the arrival task to another similar VM in a cloud environment. In addition, we propose a multi-objective optimization model to migrate these tasks to a new VM host applying multi-objective genetic algorithm (MOGA). In the proposed approach, there is no need to pause VM during migration time. In addition, as contrast to tasks migration, VM live migration takes longer to complete and needs more idle capacity in host physical machine (PM), the proposed approach will significantly reduce time, downtime memory, and cost consumption.

Keywords

Cloud computing Multi-objective genetic algorithm Virtual machine migration Task based system load balancing algorithm 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.Decision Systems and e-Service Intelligence Laboratory, Faculty of Engineering and IT, School of Software, Centre for QCISUniversity of TechnologySydneyAustralia

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