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Scheduling of Parallel Migration for Multiple Virtual Machines

Authors: Koichi Onoue; Satoshi Imai; Naoki Matsuoka;

Scheduling of Parallel Migration for Multiple Virtual Machines

Abstract

Virtualization technology can readily change the placement of an execution environment, such as a virtual machine (VM), in accordance with the current statuses. To effectively manage system resources in the virtualized infrastructure, the elasticity of a virtualized infrastructure has attracted significant attention for determining on which server VM should be deployed. However, there has been little attention to how long it takes to relocate VMs and in what order VMs migrate. It is difficult to determine the migration order of VMs in consideration of the residual resources of the destination server and network topology. In this paper, we propose two methods for scheduling the parallel migration of multiple VMs to reduce the impact on performance degradation due to VM migrations. We first formulate an integer linear programming (ILP) model to determine the VM migration order. To solve the problem in an acceptable time for large infrastructures, we also design a heuristic method based on dependencies between VM migrations and network bandwidth. Simulation results demonstrate that the heuristic-based method obtained the solutions in a few seconds for the settings with small differences with the optimal solutions obtained from the ILP-based method.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Average
Average
Average
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