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Virtual Machine Migration: Greedy Heuristics and Mathematical Models

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Virtual Machine Migration: Greedy Heuristics and Mathematical Models

Boudreau, Charles (2020) Virtual Machine Migration: Greedy Heuristics and Mathematical Models. Masters thesis, Concordia University.

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Abstract

Live Migration of virtual machines between different physical hosts is an important process for datacenter management, essential for safeguarding hardware integrity and controlling power consumption, among other functions, with no perceptible interruptions for the user of the virtual machine. As the migration operation has a cost in terms of power and service quality degradation, it is of interest to examine how to best conduct multiple live migrations such that the total time needed to complete all planned migrations is minimized. Scheduling of multiple VM migrations may also take into account the risk of bringing the system to a state where all planned migrations cannot be resolved due to deadlocks caused by resource dependencies.

In this work, we propose a set of solutions based on greedy heuristics for the VM migration problem. We have selected four possible criteria to base scheduling decisions on, and we evaluate the total migration time degree of completion of the planned migrations next to a baseline algorithm. Additionally, we propose two decomposed linear programming models intended for column generation solution: a time-based formulation, followed by a precedence-based formulation. We suppose that these decomposed formulations will lead to faster solution times over conventional, “compact” formulations due to their structure permitting the elimination of a large number of variables from explicit consideration when the continuous relaxation is solved with column generation techniques.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Computer Science and Software Engineering
Item Type:Thesis (Masters)
Authors:Boudreau, Charles
Institution:Concordia University
Degree Name:M. Comp. Sc.
Program:Computer Science
Date:24 December 2020
Thesis Supervisor(s):Jaumard, Brigitte
ID Code:987889
Deposited By: CHARLES BOUDREAU
Deposited On:29 Jun 2021 21:07
Last Modified:29 Jun 2021 21:07
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