PERMUTE:云数据中心的响应时间和能量感知虚拟机布局

Benyamin Eslami, Morteza Biabani, Mohsen Shekarisaz, N. Yazdani
{"title":"PERMUTE:云数据中心的响应时间和能量感知虚拟机布局","authors":"Benyamin Eslami, Morteza Biabani, Mohsen Shekarisaz, N. Yazdani","doi":"10.1109/CSICC52343.2021.9420565","DOIUrl":null,"url":null,"abstract":"Cloud data centers play a significant role in providing services needed by users in a quick way. Recent studies show that, traffic patterns in data centers have a special importance to be improved, since they have significant effects on various aspects such as congestion, overall energy consumption and service response time. The traffic patterns inside a cloud data center have two categories: North-South and East-West. The former one is the outside-inside and inside-outside traffic, Whereas, the latter is the traffic among Virtual Machines (VMs) within data centers. Previous studies have shown that the East-West traffic pattern is multiple times larger than the North-South one. This leads data centers to experience congestion and packet loss in the core layer of their topology. Common cause of large traffic patterns is that, VMs of service chains are scattered within the data center in different racks, so that, it causes lots of packet injection into the data center. In this paper, we propose a heuristic algorithm to place VMs of a service chain in a closer proximity of each other to improve the East-West traffic pattern by reducing response time of services and also data centers’ overall energy consumption. The simulation results compared to the state-of-the-art method demonstrate about 18% improvement in response time for users’ requests and 10% of total energy consumption reduction in the data center.","PeriodicalId":374593,"journal":{"name":"2021 26th International Computer Conference, Computer Society of Iran (CSICC)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"PERMUTE: Response Time and Energy Aware Virtual Machine Placement for Cloud Data Centers\",\"authors\":\"Benyamin Eslami, Morteza Biabani, Mohsen Shekarisaz, N. Yazdani\",\"doi\":\"10.1109/CSICC52343.2021.9420565\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Cloud data centers play a significant role in providing services needed by users in a quick way. Recent studies show that, traffic patterns in data centers have a special importance to be improved, since they have significant effects on various aspects such as congestion, overall energy consumption and service response time. The traffic patterns inside a cloud data center have two categories: North-South and East-West. The former one is the outside-inside and inside-outside traffic, Whereas, the latter is the traffic among Virtual Machines (VMs) within data centers. Previous studies have shown that the East-West traffic pattern is multiple times larger than the North-South one. This leads data centers to experience congestion and packet loss in the core layer of their topology. Common cause of large traffic patterns is that, VMs of service chains are scattered within the data center in different racks, so that, it causes lots of packet injection into the data center. In this paper, we propose a heuristic algorithm to place VMs of a service chain in a closer proximity of each other to improve the East-West traffic pattern by reducing response time of services and also data centers’ overall energy consumption. The simulation results compared to the state-of-the-art method demonstrate about 18% improvement in response time for users’ requests and 10% of total energy consumption reduction in the data center.\",\"PeriodicalId\":374593,\"journal\":{\"name\":\"2021 26th International Computer Conference, Computer Society of Iran (CSICC)\",\"volume\":\"77 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-03-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 26th International Computer Conference, Computer Society of Iran (CSICC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CSICC52343.2021.9420565\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 26th International Computer Conference, Computer Society of Iran (CSICC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSICC52343.2021.9420565","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

云数据中心在快速提供用户所需服务方面发挥着重要作用。最近的研究表明,数据中心的流量模式具有特别重要的改进意义,因为它们对拥塞、总体能耗和服务响应时间等各个方面都有重大影响。云数据中心内部的流量模式分为南北和东西两类。前者是由外到内和由内到外的流量,后者是数据中心内虚拟机之间的流量。以前的研究表明,东西交通格局比南北交通格局大好几倍。这导致数据中心在其拓扑的核心层中经历拥塞和数据包丢失。造成大流量的常见原因是,业务链的虚拟机分散在数据中心内不同的机架上,导致大量的数据包注入数据中心。在本文中,我们提出了一种启发式算法,通过减少服务响应时间和数据中心的总体能耗,将服务链上的虚拟机放置在彼此更接近的位置,以改善东西流量模式。与最先进的方法相比,仿真结果表明,用户请求的响应时间提高了18%,数据中心的总能耗降低了10%。
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
PERMUTE: Response Time and Energy Aware Virtual Machine Placement for Cloud Data Centers
Cloud data centers play a significant role in providing services needed by users in a quick way. Recent studies show that, traffic patterns in data centers have a special importance to be improved, since they have significant effects on various aspects such as congestion, overall energy consumption and service response time. The traffic patterns inside a cloud data center have two categories: North-South and East-West. The former one is the outside-inside and inside-outside traffic, Whereas, the latter is the traffic among Virtual Machines (VMs) within data centers. Previous studies have shown that the East-West traffic pattern is multiple times larger than the North-South one. This leads data centers to experience congestion and packet loss in the core layer of their topology. Common cause of large traffic patterns is that, VMs of service chains are scattered within the data center in different racks, so that, it causes lots of packet injection into the data center. In this paper, we propose a heuristic algorithm to place VMs of a service chain in a closer proximity of each other to improve the East-West traffic pattern by reducing response time of services and also data centers’ overall energy consumption. The simulation results compared to the state-of-the-art method demonstrate about 18% improvement in response time for users’ requests and 10% of total energy consumption reduction in the data center.
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
Transfer Learning for End-to-End ASR to Deal with Low-Resource Problem in Persian Language An SDN-based Firewall for Networks with Varying Security Requirements A Face-Mask Detection Approach based on YOLO Applied for a New Collected Dataset Telegram group recommendation based on users' migration Design of an IoT-based Flood Early Detection System using Machine Learning
×
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