Prevent VM Migration in Virtualized Clusters via Deadline Driven Placement Policy

M. Tsai, J. Chou, Jye Chen
{"title":"Prevent VM Migration in Virtualized Clusters via Deadline Driven Placement Policy","authors":"M. Tsai, J. Chou, Jye Chen","doi":"10.1109/CloudCom.2013.85","DOIUrl":null,"url":null,"abstract":"VM consolidation has been shown as a promising technique for saving energy costs of a data center. It relies on VM migration to move user applications or jobs onto fewer numbers of physical servers during off peak hour. However, VM migration is a costly operation that could cause several concerns, such as performance degradation and system instability. Most existing works were proposed to minimize the migration cost for dynamic consolidation which migrates VM at the runtime when SLA violation or resource under-utilization is detected. In contrast, this paper aims to proactively prevent VM migration for semi-static VM consolidation by proposing a deadline driven VM placement strategy based on the awareness of the server turn-off time and job execution time. We evaluate our approach using a real HPC cluster trace as well as a set of synthetic generated workloads. The results show our approach can significantly reduce the number of migrations by 70% on the real trace. We also demonstrate that our approach can be resilient to different workload patterns by achieving consistent improvement around 50% over all the synthetic workloads.","PeriodicalId":198053,"journal":{"name":"2013 IEEE 5th International Conference on Cloud Computing Technology and Science","volume":"75 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE 5th International Conference on Cloud Computing Technology and Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CloudCom.2013.85","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6

Abstract

VM consolidation has been shown as a promising technique for saving energy costs of a data center. It relies on VM migration to move user applications or jobs onto fewer numbers of physical servers during off peak hour. However, VM migration is a costly operation that could cause several concerns, such as performance degradation and system instability. Most existing works were proposed to minimize the migration cost for dynamic consolidation which migrates VM at the runtime when SLA violation or resource under-utilization is detected. In contrast, this paper aims to proactively prevent VM migration for semi-static VM consolidation by proposing a deadline driven VM placement strategy based on the awareness of the server turn-off time and job execution time. We evaluate our approach using a real HPC cluster trace as well as a set of synthetic generated workloads. The results show our approach can significantly reduce the number of migrations by 70% on the real trace. We also demonstrate that our approach can be resilient to different workload patterns by achieving consistent improvement around 50% over all the synthetic workloads.
通过“截止日期驱动放置策略”防止虚拟化集群中的虚拟机迁移
虚拟机整合已被证明是一种很有前途的技术,可以节省数据中心的能源成本。它依赖于VM迁移,在非高峰时段将用户应用程序或作业迁移到数量较少的物理服务器上。但是,虚拟机迁移是一项代价高昂的操作,可能会引起一些问题,例如性能下降和系统不稳定。大多数现有的工作都是为了最小化动态整合的迁移成本,当检测到SLA违反或资源利用率不足时,动态整合会在运行时迁移VM。相比之下,本文提出了一种基于服务器关闭时间和作业执行时间的截止日期驱动的虚拟机放置策略,旨在主动防止半静态虚拟机整合中的虚拟机迁移。我们使用真实的HPC集群跟踪以及一组合成生成的工作负载来评估我们的方法。结果表明,我们的方法可以将实际跟踪的迁移次数显著减少70%。我们还演示了我们的方法可以适应不同的工作负载模式,在所有合成工作负载上实现大约50%的一致改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信