一种云数据中心资源均衡利用的虚拟机布局算法

N. Hieu, M. D. Francesco, Antti Ylä-Jääski
{"title":"一种云数据中心资源均衡利用的虚拟机布局算法","authors":"N. Hieu, M. D. Francesco, Antti Ylä-Jääski","doi":"10.1109/CLOUD.2014.70","DOIUrl":null,"url":null,"abstract":"Virtual machine (VM) placement is the process of selecting the most suitable server in large cloud data centers to deploy newly-created VMs. Several approaches have been proposed to find a solution to this problem. However, most of the existing solutions only consider a limited number of resource types, thus resulting in unbalanced load or in the unnecessary activation of physical servers. In this article, we propose an algorithm, called Max-BRU, that maximizes the resource utilization and balances the usage of resources across multiple dimensions. Our algorithm is based on multiple resource-constraint metrics that help to find the most suitable server for deploying VMs in large cloud data centers. The proposed Max-BRU algorithm is evaluated by simulations based on synthetic datasets. Experimental results show two major improvements over the existing approaches for VM placement. First, Max-BRU increases the resource utilization by minimizing the amount of physical servers used. Second, Max-BRU effectively balances the utilization of multiple types of resources.","PeriodicalId":288542,"journal":{"name":"2014 IEEE 7th International Conference on Cloud Computing","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"44","resultStr":"{\"title\":\"A virtual machine placement algorithm for balanced resource utilization in cloud data centers\",\"authors\":\"N. Hieu, M. D. Francesco, Antti Ylä-Jääski\",\"doi\":\"10.1109/CLOUD.2014.70\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Virtual machine (VM) placement is the process of selecting the most suitable server in large cloud data centers to deploy newly-created VMs. Several approaches have been proposed to find a solution to this problem. However, most of the existing solutions only consider a limited number of resource types, thus resulting in unbalanced load or in the unnecessary activation of physical servers. In this article, we propose an algorithm, called Max-BRU, that maximizes the resource utilization and balances the usage of resources across multiple dimensions. Our algorithm is based on multiple resource-constraint metrics that help to find the most suitable server for deploying VMs in large cloud data centers. The proposed Max-BRU algorithm is evaluated by simulations based on synthetic datasets. Experimental results show two major improvements over the existing approaches for VM placement. First, Max-BRU increases the resource utilization by minimizing the amount of physical servers used. Second, Max-BRU effectively balances the utilization of multiple types of resources.\",\"PeriodicalId\":288542,\"journal\":{\"name\":\"2014 IEEE 7th International Conference on Cloud Computing\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-06-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"44\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE 7th International Conference on Cloud Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CLOUD.2014.70\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE 7th International Conference on Cloud Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CLOUD.2014.70","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 44

摘要

虚拟机布局是在大型云数据中心中选择最合适的服务器来部署新创建的虚拟机的过程。已经提出了几种方法来解决这个问题。但是,大多数现有解决方案只考虑有限数量的资源类型,从而导致负载不平衡或不必要地激活物理服务器。在本文中,我们提出了一种称为Max-BRU的算法,该算法最大限度地提高资源利用率,并在多个维度上平衡资源的使用。我们的算法基于多个资源约束指标,这些指标有助于找到最适合在大型云数据中心部署vm的服务器。通过基于合成数据集的仿真对所提出的Max-BRU算法进行了评价。实验结果表明,与现有的虚拟机放置方法相比,该方法有两大改进。首先,Max-BRU通过最小化使用的物理服务器数量来提高资源利用率。其次,Max-BRU有效地平衡了多种资源的利用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
A virtual machine placement algorithm for balanced resource utilization in cloud data centers
Virtual machine (VM) placement is the process of selecting the most suitable server in large cloud data centers to deploy newly-created VMs. Several approaches have been proposed to find a solution to this problem. However, most of the existing solutions only consider a limited number of resource types, thus resulting in unbalanced load or in the unnecessary activation of physical servers. In this article, we propose an algorithm, called Max-BRU, that maximizes the resource utilization and balances the usage of resources across multiple dimensions. Our algorithm is based on multiple resource-constraint metrics that help to find the most suitable server for deploying VMs in large cloud data centers. The proposed Max-BRU algorithm is evaluated by simulations based on synthetic datasets. Experimental results show two major improvements over the existing approaches for VM placement. First, Max-BRU increases the resource utilization by minimizing the amount of physical servers used. Second, Max-BRU effectively balances the utilization of multiple types of resources.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
User-Friendly Visualization of Cloud Quality Energy and Performance-Aware Task Scheduling in a Mobile Cloud Computing Environment MediaPaaS: A Cloud-Based Media Processing Platform for Elastic Live Broadcasting AppCloak: Rapid Migration of Legacy Applications into Cloud Introducing SSDs to the Hadoop MapReduce Framework
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1