Two-Phase Virtual Machine Placement Algorithms for Cloud Computing: An Experimental Evaluation under Uncertainty

Cloud computing providers must support requests for resources in dynamic environments, considering service elasticity and overbooking of physical resources. Due to the randomness of requests, Virtual Machine Placement (VMP) problems should be formulated under uncertainty. In this context, a renewed...

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Autores principales: Chamas, Nabil, López-Pires, Fabio, Barán, Benjamín
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2017
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Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/65519
Aporte de:
id I19-R120-10915-65519
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
virtual machine placement
cloud computing
overbooking
elasticity
uncertainty
incremental vmp
vmp reconfiguration
spellingShingle Ciencias Informáticas
virtual machine placement
cloud computing
overbooking
elasticity
uncertainty
incremental vmp
vmp reconfiguration
Chamas, Nabil
López-Pires, Fabio
Barán, Benjamín
Two-Phase Virtual Machine Placement Algorithms for Cloud Computing: An Experimental Evaluation under Uncertainty
topic_facet Ciencias Informáticas
virtual machine placement
cloud computing
overbooking
elasticity
uncertainty
incremental vmp
vmp reconfiguration
description Cloud computing providers must support requests for resources in dynamic environments, considering service elasticity and overbooking of physical resources. Due to the randomness of requests, Virtual Machine Placement (VMP) problems should be formulated under uncertainty. In this context, a renewed formulation of the VMP problem is presented, considering the optimization of four objective functions: (i) power consumption, (ii) economical revenue, (iii) resource utilization and (iv) reconfiguration time. To solve the presented formulation, a two-phase optimization scheme is considered, composed by an online incremental VMP phase (iVMP) and an offline VMP reconfiguration (VMPr) phase. An experimental evaluation of five algorithms taking into account 400 different scenarios was performed, considering three VMPr Triggering and two VMPr Recovering methods as well as three VMPr resolution alternatives. Experimental results indicate which algorithm outperformed the other evaluated algorithms, improving the quality of solutions in a scenario-based uncertainty model considering the following evaluation criteria: (i) average, (ii) maximum and (iii) minimum objective function costs.
format Objeto de conferencia
Objeto de conferencia
author Chamas, Nabil
López-Pires, Fabio
Barán, Benjamín
author_facet Chamas, Nabil
López-Pires, Fabio
Barán, Benjamín
author_sort Chamas, Nabil
title Two-Phase Virtual Machine Placement Algorithms for Cloud Computing: An Experimental Evaluation under Uncertainty
title_short Two-Phase Virtual Machine Placement Algorithms for Cloud Computing: An Experimental Evaluation under Uncertainty
title_full Two-Phase Virtual Machine Placement Algorithms for Cloud Computing: An Experimental Evaluation under Uncertainty
title_fullStr Two-Phase Virtual Machine Placement Algorithms for Cloud Computing: An Experimental Evaluation under Uncertainty
title_full_unstemmed Two-Phase Virtual Machine Placement Algorithms for Cloud Computing: An Experimental Evaluation under Uncertainty
title_sort two-phase virtual machine placement algorithms for cloud computing: an experimental evaluation under uncertainty
publishDate 2017
url http://sedici.unlp.edu.ar/handle/10915/65519
work_keys_str_mv AT chamasnabil twophasevirtualmachineplacementalgorithmsforcloudcomputinganexperimentalevaluationunderuncertainty
AT lopezpiresfabio twophasevirtualmachineplacementalgorithmsforcloudcomputinganexperimentalevaluationunderuncertainty
AT baranbenjamin twophasevirtualmachineplacementalgorithmsforcloudcomputinganexperimentalevaluationunderuncertainty
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