Joint power optimization through VM placement and flow scheduling in data centers

Dawei Li, Jie Wu, Zhiyong Liu, Fa Zhang
{"title":"Joint power optimization through VM placement and flow scheduling in data centers","authors":"Dawei Li, Jie Wu, Zhiyong Liu, Fa Zhang","doi":"10.1109/PCCC.2014.7017088","DOIUrl":null,"url":null,"abstract":"Two important components that consume the majority of IT power in data centers are the servers and the Data Center Network (DCN). Existing works fail to fully utilize power management techniques on the servers and in the DCN at the same time. In this paper, we jointly consider VM placement on servers with scalable frequencies and flow scheduling in the DCN, to minimize the overall system's power consumption. Due to the convex relation between a server's power consumption and its operating frequency, we prove that, given the number of servers to be used, computation workloads should be allocated to severs in a balanced way, to minimize the power consumption on servers. To reduce the power consumption of the DCN, we further consider the flow requirements among the VMs during VM allocation and assignment. Also, after VM placement, flow consolidation is conducted to reduce the number of active switches and ports. We notice that, choosing the minimum number of servers to accommodate the VMs may result in high power consumption on servers, due to servers' increased operating frequencies. Choosing the optimal number of servers purely based on servers' power consumption leads to reduced power consumption on servers, but may increase power consumption of the DCN. We propose to choose the optimal number of servers to be used, based on the overall system's power consumption. Simulations show that, our joint power optimization method helps to reduce the overall power consumption significantly, and outperforms various existing state-of-the-art methods in terms of reducing the overall system's power consumption.","PeriodicalId":105442,"journal":{"name":"2014 IEEE 33rd International Performance Computing and Communications Conference (IPCCC)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE 33rd International Performance Computing and Communications Conference (IPCCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PCCC.2014.7017088","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10

Abstract

Two important components that consume the majority of IT power in data centers are the servers and the Data Center Network (DCN). Existing works fail to fully utilize power management techniques on the servers and in the DCN at the same time. In this paper, we jointly consider VM placement on servers with scalable frequencies and flow scheduling in the DCN, to minimize the overall system's power consumption. Due to the convex relation between a server's power consumption and its operating frequency, we prove that, given the number of servers to be used, computation workloads should be allocated to severs in a balanced way, to minimize the power consumption on servers. To reduce the power consumption of the DCN, we further consider the flow requirements among the VMs during VM allocation and assignment. Also, after VM placement, flow consolidation is conducted to reduce the number of active switches and ports. We notice that, choosing the minimum number of servers to accommodate the VMs may result in high power consumption on servers, due to servers' increased operating frequencies. Choosing the optimal number of servers purely based on servers' power consumption leads to reduced power consumption on servers, but may increase power consumption of the DCN. We propose to choose the optimal number of servers to be used, based on the overall system's power consumption. Simulations show that, our joint power optimization method helps to reduce the overall power consumption significantly, and outperforms various existing state-of-the-art methods in terms of reducing the overall system's power consumption.
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
通过数据中心中的虚拟机放置和流调度进行联合功率优化
在数据中心中消耗大部分IT电力的两个重要组件是服务器和数据中心网络(DCN)。现有的工作不能同时在服务器和DCN上充分利用电源管理技术。在本文中,我们共同考虑了虚拟机在DCN中具有可扩展频率和流调度的服务器上的放置,以最小化整个系统的功耗。由于服务器的功耗与其工作频率之间存在凸关系,我们证明了在给定服务器数量的情况下,计算工作负载应该均衡地分配给服务器,以最大限度地减少服务器的功耗。为了降低DCN的功耗,我们在分配和分配虚拟机时进一步考虑了虚拟机之间的流量需求。此外,在虚拟机放置后,进行流量整合,以减少活动交换机和端口的数量。我们注意到,选择最小数量的服务器来容纳虚拟机可能会导致服务器上的高功耗,因为服务器的工作频率增加了。单纯根据服务器的功耗选择最优的服务器数量,可以降低服务器的功耗,但可能会增加DCN的功耗。我们建议根据整个系统的功耗来选择要使用的最优服务器数量。仿真表明,我们的联合功耗优化方法有助于显著降低整体功耗,并且在降低整体系统功耗方面优于现有的各种最先进的方法。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Performance and energy evaluation of RESTful web services in Raspberry Pi Proximity-driven social interactions and their impact on the throughput scaling of wireless networks POLA: A privacy-preserving protocol for location-based real-time advertising Replica placement in content delivery networks with stochastic demands and M/M/1 servers Combinatorial JPT based on orthogonal beamforming for two-cell cooperation
×
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