Towards a Greener Cloud Infrastructure Management using Optimized Placement Policies

Cloud infrastructures are designed to simultaneously service many, diverse applications that consist of collections of Virtual Machines (VMs). The placement policy used to map applications onto physical servers has important effects in terms of application performance and resource efficiency. We pro...

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Detalles Bibliográficos
Autores: Pascual Saiz, José Antonio, Lorido Botrán, Tania, Miguel Alonso, José, Lozano Alonso, José Antonio
Tipo de recurso: artículo
Fecha de publicación:2014
País:España
Institución:Universidad del País Vasco
Repositorio:Addi. Archivo Digital para la Docencia y la Investigación
OAI Identifier:oai:addi.ehu.eus:10810/71568
Acceso en línea:http://hdl.handle.net/10810/71568
Access Level:acceso abierto
Palabra clave:cloud computing
VM placement
multi-objective optimization
energy consumption
tree-network data center topology
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spelling Towards a Greener Cloud Infrastructure Management using Optimized Placement PoliciesPascual Saiz, José AntonioLorido Botrán, TaniaMiguel Alonso, JoséLozano Alonso, José Antoniocloud computingVM placementmulti-objective optimizationenergy consumptiontree-network data center topologyCloud infrastructures are designed to simultaneously service many, diverse applications that consist of collections of Virtual Machines (VMs). The placement policy used to map applications onto physical servers has important effects in terms of application performance and resource efficiency. We propose enhancing placement policies with network-aware optimizations, trying to simultaneously improve application performance, resource efficiency and power efficiency. The per-application placement decision is formulated as a bi-objective optimization problem (minimizing communication cost and the number of physical servers on which an application runs) whose solution is searched using evolutionary techniques. We have tested three multi-objective optimization algorithms with problem-specific crossover and mutation operators. Simulation-based experiments demonstrate how, in comparison with classic placement techniques, a low-cost optimization results in improved assignments of resources, making applications run faster and reducing the energy consumed by the data center. This is beneficial for both cloud clients and cloud providers.This work has been partially supported by the Saiotek and Research Groups 2013-2018 (IT-609-13) programs (Basque Government), TIN2010-14931 and COM-BIOMED network in computational biomedicine (Carlos III Health Institute). Dr. Pascual is supported by a postdoctoral grant of the UPV/EHU. Mrs Lorido-Botran is supported by a doctoral grant from the Basque Government. Prof. Miguel-Alonso is a member of the HiPEAC European Network of Excellence.Jose Antonio Pascual, Tania Lorido-Botran, José Miguel-Alonso, José Antonio Lozano: Towards a Greener Cloud Infrastructure Management using Optimized Placement Policies. J. Grid Comput. 13(3): 375-389 (2015)202520252014info:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10810/71568reponame:Addi. Archivo Digital para la Docencia y la Investigacióninstname:Universidad del País VascoIngléshttps://doi.org/10.1007/s10723-014-9312-9info:eu-repo/semantics/openAccess© 2014, Springer Science Business Media Dordrechtoai:addi.ehu.eus:10810/715682026-06-18T09:23:17Z
dc.title.none.fl_str_mv Towards a Greener Cloud Infrastructure Management using Optimized Placement Policies
title Towards a Greener Cloud Infrastructure Management using Optimized Placement Policies
spellingShingle Towards a Greener Cloud Infrastructure Management using Optimized Placement Policies
Pascual Saiz, José Antonio
cloud computing
VM placement
multi-objective optimization
energy consumption
tree-network data center topology
title_short Towards a Greener Cloud Infrastructure Management using Optimized Placement Policies
title_full Towards a Greener Cloud Infrastructure Management using Optimized Placement Policies
title_fullStr Towards a Greener Cloud Infrastructure Management using Optimized Placement Policies
title_full_unstemmed Towards a Greener Cloud Infrastructure Management using Optimized Placement Policies
title_sort Towards a Greener Cloud Infrastructure Management using Optimized Placement Policies
dc.creator.none.fl_str_mv Pascual Saiz, José Antonio
Lorido Botrán, Tania
Miguel Alonso, José
Lozano Alonso, José Antonio
author Pascual Saiz, José Antonio
author_facet Pascual Saiz, José Antonio
Lorido Botrán, Tania
Miguel Alonso, José
Lozano Alonso, José Antonio
author_role author
author2 Lorido Botrán, Tania
Miguel Alonso, José
Lozano Alonso, José Antonio
author2_role author
author
author
dc.subject.none.fl_str_mv cloud computing
VM placement
multi-objective optimization
energy consumption
tree-network data center topology
topic cloud computing
VM placement
multi-objective optimization
energy consumption
tree-network data center topology
description Cloud infrastructures are designed to simultaneously service many, diverse applications that consist of collections of Virtual Machines (VMs). The placement policy used to map applications onto physical servers has important effects in terms of application performance and resource efficiency. We propose enhancing placement policies with network-aware optimizations, trying to simultaneously improve application performance, resource efficiency and power efficiency. The per-application placement decision is formulated as a bi-objective optimization problem (minimizing communication cost and the number of physical servers on which an application runs) whose solution is searched using evolutionary techniques. We have tested three multi-objective optimization algorithms with problem-specific crossover and mutation operators. Simulation-based experiments demonstrate how, in comparison with classic placement techniques, a low-cost optimization results in improved assignments of resources, making applications run faster and reducing the energy consumed by the data center. This is beneficial for both cloud clients and cloud providers.
publishDate 2014
dc.date.none.fl_str_mv 2014
2025
2025
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10810/71568
url http://hdl.handle.net/10810/71568
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv https://doi.org/10.1007/s10723-014-9312-9
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
© 2014, Springer Science Business Media Dordrecht
eu_rights_str_mv openAccess
rights_invalid_str_mv © 2014, Springer Science Business Media Dordrecht
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Jose Antonio Pascual, Tania Lorido-Botran, José Miguel-Alonso, José Antonio Lozano: Towards a Greener Cloud Infrastructure Management using Optimized Placement Policies. J. Grid Comput. 13(3): 375-389 (2015)
publisher.none.fl_str_mv Jose Antonio Pascual, Tania Lorido-Botran, José Miguel-Alonso, José Antonio Lozano: Towards a Greener Cloud Infrastructure Management using Optimized Placement Policies. J. Grid Comput. 13(3): 375-389 (2015)
dc.source.none.fl_str_mv reponame:Addi. Archivo Digital para la Docencia y la Investigación
instname:Universidad del País Vasco
instname_str Universidad del País Vasco
reponame_str Addi. Archivo Digital para la Docencia y la Investigación
collection Addi. Archivo Digital para la Docencia y la Investigación
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,811543

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