A penalty-based genetic algorithm for the migration cost-aware virtual machine placement problem in cloud data centers
Sarker, Tusher Kumer & Tang, Maolin (2015) A penalty-based genetic algorithm for the migration cost-aware virtual machine placement problem in cloud data centers. Neural Information Processing: 22nd International Conference, ICONIP 2015, Proceedings Part II [Lecture Notes in Computer Science, Volume 9490], pp. 161-169.
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In the past few years, the virtual machine (VM) placement problem has been studied intensively and many algorithms for the VM placement problem have been proposed. However, those proposed VM placement algorithms have not been widely used in today's cloud data centers as they do not consider the migration cost from current VM placement to the new optimal VM placement. As a result, the gain from optimizing VM placement may be less than the loss of the migration cost from current VM placement to the new VM placement. To address this issue, this paper presents a penalty-based genetic algorithm (GA) for the VM placement problem that considers the migration cost in addition to the energy-consumption of the new VM placement and the total inter-VM traffic flow in the new VM placement. The GA has been implemented and evaluated by experiments, and the experimental results show that the GA outperforms two well known algorithms for the VM placement problem.
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|Item Type:||Journal Article|
|Keywords:||VM placement, VM migration, penalty-based genetic algorithm|
|Divisions:||Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
|Copyright Owner:||Copyright 2015 Springer|
|Deposited On:||16 Sep 2015 00:17|
|Last Modified:||17 Dec 2015 05:18|
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