Approach of glowworm swarm optimization based virtual machine placement

In a cloud data center, one of the most important problems is using novel virtual machine placement strategy to promote the physical resource utilization.An approach of glowworm swarm optimization based virtual machine placement for cloud data centers called GSO-VMP was proposed.In the virtual place...

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Main Authors: Shengchao XU, Maohua XIONG, Tianqi ZHOU
Format: Article
Language:zho
Published: Beijing Xintong Media Co., Ltd 2022-03-01
Series:Dianxin kexue
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Online Access:http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2022060/
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author Shengchao XU
Maohua XIONG
Tianqi ZHOU
author_facet Shengchao XU
Maohua XIONG
Tianqi ZHOU
author_sort Shengchao XU
collection DOAJ
description In a cloud data center, one of the most important problems is using novel virtual machine placement strategy to promote the physical resource utilization.An approach of glowworm swarm optimization based virtual machine placement for cloud data centers called GSO-VMP was proposed.In the virtual placement, GSO algorithm was used to find a near-optimal solution.Each physical host had a luciferin value which represented the available CPU utilization.Whenever a VM was placed to a physical host, luciferin value of this physical host was updated.GSO-VMP algorithm could search the more available physical host within local range and thus the virtual migration numbers had been decreased and low energy consumption had been obtained.GSO-VMP had been evaluated using CloudSim with real-world workload data.The experimental results show that GSO-VMP has good performance in resource wastage and energy consumption.
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publisher Beijing Xintong Media Co., Ltd
record_format Article
series Dianxin kexue
spelling doaj-art-798c54fc7a3c4de5ad9e3bdfdaae25972025-08-20T02:46:59ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012022-03-013817218259810020Approach of glowworm swarm optimization based virtual machine placementShengchao XUMaohua XIONGTianqi ZHOUIn a cloud data center, one of the most important problems is using novel virtual machine placement strategy to promote the physical resource utilization.An approach of glowworm swarm optimization based virtual machine placement for cloud data centers called GSO-VMP was proposed.In the virtual placement, GSO algorithm was used to find a near-optimal solution.Each physical host had a luciferin value which represented the available CPU utilization.Whenever a VM was placed to a physical host, luciferin value of this physical host was updated.GSO-VMP algorithm could search the more available physical host within local range and thus the virtual migration numbers had been decreased and low energy consumption had been obtained.GSO-VMP had been evaluated using CloudSim with real-world workload data.The experimental results show that GSO-VMP has good performance in resource wastage and energy consumption.http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2022060/intelligent computingglowworm swarm optimizationvirtual machine placementcloud data centerlow energy consumption
spellingShingle Shengchao XU
Maohua XIONG
Tianqi ZHOU
Approach of glowworm swarm optimization based virtual machine placement
Dianxin kexue
intelligent computing
glowworm swarm optimization
virtual machine placement
cloud data center
low energy consumption
title Approach of glowworm swarm optimization based virtual machine placement
title_full Approach of glowworm swarm optimization based virtual machine placement
title_fullStr Approach of glowworm swarm optimization based virtual machine placement
title_full_unstemmed Approach of glowworm swarm optimization based virtual machine placement
title_short Approach of glowworm swarm optimization based virtual machine placement
title_sort approach of glowworm swarm optimization based virtual machine placement
topic intelligent computing
glowworm swarm optimization
virtual machine placement
cloud data center
low energy consumption
url http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2022060/
work_keys_str_mv AT shengchaoxu approachofglowwormswarmoptimizationbasedvirtualmachineplacement
AT maohuaxiong approachofglowwormswarmoptimizationbasedvirtualmachineplacement
AT tianqizhou approachofglowwormswarmoptimizationbasedvirtualmachineplacement