The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Le placement de machines virtuelles (VMP) joue un rôle important pour garantir un approvisionnement efficace en ressources des machines physiques (PM) et l'efficacité énergétique dans les centres de données d'infrastructure en tant que service (IaaS). Une consolidation efficace des serveurs assistée par la migration de machines virtuelles (VM) peut favoriser le niveau d'utilisation des serveurs et faire passer les PM inactifs en mode veille pour économiser de l'énergie. Le compromis entre énergie et performances est difficile, car la consolidation peut entraîner une dégradation des performances, voire des violations des accords de niveau de service (SLA). Un nouveau modèle de ressource de capacité disponible résiduelle (RAC) est proposé pour résoudre le problème de sélection et d'allocation de VM du point de vue du fournisseur de services cloud (CSP). De plus, une nouvelle politique heuristique de sélection de VM pour la consolidation de serveurs, nommée Ressource disponible de racine carrée réduite (MISR) est proposé. Parallèlement, une politique d'allocation de VM efficace, nommée Sélection équilibrée (BS) basé sur RAC est proposé. La validation de l'efficacité de la combinaison BS-MISR est réalisée sur CloudSim avec des charges de travail réelles du projet CoMon. Les résultats de l'évaluation des expériences montrent que la combinaison proposée BS-MISR peut réduire considérablement la consommation d'énergie, avec une moyenne de 36.35 % par rapport à la politique combinée de régression locale et de temps de migration minimum (LR-MMT). De plus, le BS-MISR garantit un niveau de SLA raisonnable par rapport aux benchmarks.
Yaohui CHANG
East China University of Science and Technology,Shihezi University
Chunhua GU
East China University of Science and Technology
Fei LUO
East China University of Science and Technology
Guisheng FAN
East China University of Science and Technology
Wenhao FU
East China University of Science and Technology
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Yaohui CHANG, Chunhua GU, Fei LUO, Guisheng FAN, Wenhao FU, "Energy Efficient Resource Selection and Allocation Strategy for Virtual Machine Consolidation in Cloud Datacenters" in IEICE TRANSACTIONS on Information,
vol. E101-D, no. 7, pp. 1816-1827, July 2018, doi: 10.1587/transinf.2017EDP7321.
Abstract: Virtual Machine Placement (VMP) plays an important role in ensuring efficient resource provisioning of physical machines (PMs) and energy efficiency in Infrastructure as a Service (IaaS) data centers. Efficient server consolidation assisted by virtual machine (VM) migration can promote the utilization level of the servers and switch the idle PMs to sleep mode to save energy. The trade-off between energy and performance is difficult, because consolidation may cause performance degradation, even service level agreement (SLA) violations. A novel residual available capacity (RAC) resource model is proposed to resolve the VM selection and allocation problem from the cloud service provider (CSP) perspective. Furthermore, a novel heuristic VM selection policy for server consolidation, named Minimized Square Root available Resource (MISR) is proposed. Meanwhile, an efficient VM allocation policy, named Balanced Selection (BS) based on RAC is proposed. The effectiveness validation of the BS-MISR combination is conducted on CloudSim with real workloads from the CoMon project. Evaluation results of experiments show that the proposed combinationBS-MISR can significantly reduce the energy consumption, with an average of 36.35% compared to the Local Regression and Minimum Migration Time (LR-MMT) combination policy. Moreover, the BS-MISR ensures a reasonable level of SLAs compared to the benchmarks.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2017EDP7321/_p
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@ARTICLE{e101-d_7_1816,
author={Yaohui CHANG, Chunhua GU, Fei LUO, Guisheng FAN, Wenhao FU, },
journal={IEICE TRANSACTIONS on Information},
title={Energy Efficient Resource Selection and Allocation Strategy for Virtual Machine Consolidation in Cloud Datacenters},
year={2018},
volume={E101-D},
number={7},
pages={1816-1827},
abstract={Virtual Machine Placement (VMP) plays an important role in ensuring efficient resource provisioning of physical machines (PMs) and energy efficiency in Infrastructure as a Service (IaaS) data centers. Efficient server consolidation assisted by virtual machine (VM) migration can promote the utilization level of the servers and switch the idle PMs to sleep mode to save energy. The trade-off between energy and performance is difficult, because consolidation may cause performance degradation, even service level agreement (SLA) violations. A novel residual available capacity (RAC) resource model is proposed to resolve the VM selection and allocation problem from the cloud service provider (CSP) perspective. Furthermore, a novel heuristic VM selection policy for server consolidation, named Minimized Square Root available Resource (MISR) is proposed. Meanwhile, an efficient VM allocation policy, named Balanced Selection (BS) based on RAC is proposed. The effectiveness validation of the BS-MISR combination is conducted on CloudSim with real workloads from the CoMon project. Evaluation results of experiments show that the proposed combinationBS-MISR can significantly reduce the energy consumption, with an average of 36.35% compared to the Local Regression and Minimum Migration Time (LR-MMT) combination policy. Moreover, the BS-MISR ensures a reasonable level of SLAs compared to the benchmarks.},
keywords={},
doi={10.1587/transinf.2017EDP7321},
ISSN={1745-1361},
month={July},}
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TY - JOUR
TI - Energy Efficient Resource Selection and Allocation Strategy for Virtual Machine Consolidation in Cloud Datacenters
T2 - IEICE TRANSACTIONS on Information
SP - 1816
EP - 1827
AU - Yaohui CHANG
AU - Chunhua GU
AU - Fei LUO
AU - Guisheng FAN
AU - Wenhao FU
PY - 2018
DO - 10.1587/transinf.2017EDP7321
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E101-D
IS - 7
JA - IEICE TRANSACTIONS on Information
Y1 - July 2018
AB - Virtual Machine Placement (VMP) plays an important role in ensuring efficient resource provisioning of physical machines (PMs) and energy efficiency in Infrastructure as a Service (IaaS) data centers. Efficient server consolidation assisted by virtual machine (VM) migration can promote the utilization level of the servers and switch the idle PMs to sleep mode to save energy. The trade-off between energy and performance is difficult, because consolidation may cause performance degradation, even service level agreement (SLA) violations. A novel residual available capacity (RAC) resource model is proposed to resolve the VM selection and allocation problem from the cloud service provider (CSP) perspective. Furthermore, a novel heuristic VM selection policy for server consolidation, named Minimized Square Root available Resource (MISR) is proposed. Meanwhile, an efficient VM allocation policy, named Balanced Selection (BS) based on RAC is proposed. The effectiveness validation of the BS-MISR combination is conducted on CloudSim with real workloads from the CoMon project. Evaluation results of experiments show that the proposed combinationBS-MISR can significantly reduce the energy consumption, with an average of 36.35% compared to the Local Regression and Minimum Migration Time (LR-MMT) combination policy. Moreover, the BS-MISR ensures a reasonable level of SLAs compared to the benchmarks.
ER -