Multi-objective Virtual Machine Placement for Load Balancing

The virtual machine placement is closely related to the efficient and balanced utilization of physical resources. In this paper, the influence of two scenarios about resource utilization on load balancing is analyzed. A multi-objective ant colony optimization algorithm is proposed to solve the virtu...

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Main Authors: Fang Feng, Qu Bin-Bin
Format: Article
Language:English
Published: EDP Sciences 2017-01-01
Series:ITM Web of Conferences
Online Access:https://doi.org/10.1051/itmconf/20171101011
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author Fang Feng
Qu Bin-Bin
author_facet Fang Feng
Qu Bin-Bin
author_sort Fang Feng
collection DOAJ
description The virtual machine placement is closely related to the efficient and balanced utilization of physical resources. In this paper, the influence of two scenarios about resource utilization on load balancing is analyzed. A multi-objective ant colony optimization algorithm is proposed to solve the virtual machine placement problem, which balances the load among physical machines and the internal load of physical machine simultaneously. The proposed algorithm is compared with two single objective ant colony optimization algorithms, first fit algorithm and greedy algorithm under some instances. The results show that the proposed algorithm can search and find solutions that exhibit good balance among objectives while others cannot. This demonstrates the proposed algorithm can balance the load in the process of mapping virtual machines to physical machines.
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spelling doaj.art-d680ec7511e245c291ecd1911faad1bc2022-12-21T16:54:00ZengEDP SciencesITM Web of Conferences2271-20972017-01-01110101110.1051/itmconf/20171101011itmconf_ist2017_01011Multi-objective Virtual Machine Placement for Load BalancingFang Feng0Qu Bin-Bin1School of Computer Science & Technology, Huazhong University Of Science And TechnologySchool of Computer Science & Technology, Huazhong University Of Science And TechnologyThe virtual machine placement is closely related to the efficient and balanced utilization of physical resources. In this paper, the influence of two scenarios about resource utilization on load balancing is analyzed. A multi-objective ant colony optimization algorithm is proposed to solve the virtual machine placement problem, which balances the load among physical machines and the internal load of physical machine simultaneously. The proposed algorithm is compared with two single objective ant colony optimization algorithms, first fit algorithm and greedy algorithm under some instances. The results show that the proposed algorithm can search and find solutions that exhibit good balance among objectives while others cannot. This demonstrates the proposed algorithm can balance the load in the process of mapping virtual machines to physical machines.https://doi.org/10.1051/itmconf/20171101011
spellingShingle Fang Feng
Qu Bin-Bin
Multi-objective Virtual Machine Placement for Load Balancing
ITM Web of Conferences
title Multi-objective Virtual Machine Placement for Load Balancing
title_full Multi-objective Virtual Machine Placement for Load Balancing
title_fullStr Multi-objective Virtual Machine Placement for Load Balancing
title_full_unstemmed Multi-objective Virtual Machine Placement for Load Balancing
title_short Multi-objective Virtual Machine Placement for Load Balancing
title_sort multi objective virtual machine placement for load balancing
url https://doi.org/10.1051/itmconf/20171101011
work_keys_str_mv AT fangfeng multiobjectivevirtualmachineplacementforloadbalancing
AT qubinbin multiobjectivevirtualmachineplacementforloadbalancing