休眠- dc:数据中心电源管理系统

Mathieu Bacou, Grégoire Todeschi, A. Tchana, D. Hagimont, Baptiste Lepers, W. Zwaenepoel
{"title":"休眠- dc:数据中心电源管理系统","authors":"Mathieu Bacou, Grégoire Todeschi, A. Tchana, D. Hagimont, Baptiste Lepers, W. Zwaenepoel","doi":"10.1109/IPDPS.2019.00091","DOIUrl":null,"url":null,"abstract":"In a modern data center (DC), the large majority of costs arise from the energy consumption. The most popular technique used to mitigate this issue in a virtualized DC is the virtual machine (VM) consolidation. Although the latter may increase server utilization by about 5-10%, it is difficult to actually notice server loads greater than 50%. By analyzing the traces from our cloud provider partner, confirmed by previous research work, we have identified that some VMs have sporadic periods of data computation followed by large intervals of idleness. These VMs often hinder the consolidation system to further increase the energy efficiency of the DC. In this paper we propose a novel DC power management system called Drowsy-DC, which is able to identify the aforementioned VMs that have similar periods of idleness. Further, these VMs are colocated on the same server so that their idle periods are exploited to put the server to a low power mode (suspend to RAM) until some data computation is required. By introducing a negligible overhead, our system is able to improve any VM consolidation system (up to 81% for OpenStack Neat).","PeriodicalId":403406,"journal":{"name":"2019 IEEE International Parallel and Distributed Processing Symposium (IPDPS)","volume":"132 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Drowsy-DC: Data Center Power Management System\",\"authors\":\"Mathieu Bacou, Grégoire Todeschi, A. Tchana, D. Hagimont, Baptiste Lepers, W. Zwaenepoel\",\"doi\":\"10.1109/IPDPS.2019.00091\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In a modern data center (DC), the large majority of costs arise from the energy consumption. The most popular technique used to mitigate this issue in a virtualized DC is the virtual machine (VM) consolidation. Although the latter may increase server utilization by about 5-10%, it is difficult to actually notice server loads greater than 50%. By analyzing the traces from our cloud provider partner, confirmed by previous research work, we have identified that some VMs have sporadic periods of data computation followed by large intervals of idleness. These VMs often hinder the consolidation system to further increase the energy efficiency of the DC. In this paper we propose a novel DC power management system called Drowsy-DC, which is able to identify the aforementioned VMs that have similar periods of idleness. Further, these VMs are colocated on the same server so that their idle periods are exploited to put the server to a low power mode (suspend to RAM) until some data computation is required. By introducing a negligible overhead, our system is able to improve any VM consolidation system (up to 81% for OpenStack Neat).\",\"PeriodicalId\":403406,\"journal\":{\"name\":\"2019 IEEE International Parallel and Distributed Processing Symposium (IPDPS)\",\"volume\":\"132 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE International Parallel and Distributed Processing Symposium (IPDPS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IPDPS.2019.00091\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE International Parallel and Distributed Processing Symposium (IPDPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IPDPS.2019.00091","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

在现代数据中心(DC)中,大部分成本来自能源消耗。在虚拟化数据中心中缓解此问题的最常用技术是虚拟机(VM)整合。尽管后者可能会使服务器利用率提高5-10%,但实际上很难注意到服务器负载超过50%。通过分析我们的云提供商合作伙伴提供的痕迹,并通过之前的研究工作确认,我们已经确定一些虚拟机具有零星的数据计算周期,然后是大间隔的空闲。这些虚拟机经常阻碍整合系统进一步提高数据中心的能效。在本文中,我们提出了一种新的直流电源管理系统,称为Drowsy-DC,它能够识别上述具有相似空闲时间的虚拟机。此外,这些虚拟机位于同一台服务器上,以便利用它们的空闲时间将服务器置于低功耗模式(挂起到RAM),直到需要进行一些数据计算。通过引入一个可以忽略不计的开销,我们的系统能够改进任何VM整合系统(OpenStack Neat高达81%)。
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
Drowsy-DC: Data Center Power Management System
In a modern data center (DC), the large majority of costs arise from the energy consumption. The most popular technique used to mitigate this issue in a virtualized DC is the virtual machine (VM) consolidation. Although the latter may increase server utilization by about 5-10%, it is difficult to actually notice server loads greater than 50%. By analyzing the traces from our cloud provider partner, confirmed by previous research work, we have identified that some VMs have sporadic periods of data computation followed by large intervals of idleness. These VMs often hinder the consolidation system to further increase the energy efficiency of the DC. In this paper we propose a novel DC power management system called Drowsy-DC, which is able to identify the aforementioned VMs that have similar periods of idleness. Further, these VMs are colocated on the same server so that their idle periods are exploited to put the server to a low power mode (suspend to RAM) until some data computation is required. By introducing a negligible overhead, our system is able to improve any VM consolidation system (up to 81% for OpenStack Neat).
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
Distributed Weighted All Pairs Shortest Paths Through Pipelining SAFIRE: Scalable and Accurate Fault Injection for Parallel Multithreaded Applications Architecting Racetrack Memory Preshift through Pattern-Based Prediction Mechanisms Z-Dedup:A Case for Deduplicating Compressed Contents in Cloud Dual Pattern Compression Using Data-Preprocessing for Large-Scale GPU Architectures
×
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