Cloud Data Centre Energy Utilization Estimation: Simulation and Modelling With iDR

R. Rajput, Dinesh Goyal, Anjali Pant, G. Sharma, Varsha Arya, M. Rafsanjani
{"title":"Cloud Data Centre Energy Utilization Estimation: Simulation and Modelling With iDR","authors":"R. Rajput, Dinesh Goyal, Anjali Pant, G. Sharma, Varsha Arya, M. Rafsanjani","doi":"10.4018/ijcac.311035","DOIUrl":null,"url":null,"abstract":"Due to the growth of the internet and internet-based software applications, cloud data center demand has increased. Cloud data centers have thousands of servers that are 24×7 working for users; it is the strong witness of enormous energy consumption for the operation of the cloud data center. However, server utilization is not remaining the same all the time, so, from an economic feasibility point of view, energy management is an essential activity for cloud resource management. Some well-known energy management techniques for cloud data centers generally used are dynamic voltage and frequency scaling (DVFS), dynamic power management (DPM), and task scheduling-based techniques. The present work is based on an analytical approach to integrating resource provisioning with sophisticated task scheduling; the authors estimate energy utilization by cloud data centers using iDR cloud simulator. The work is intended to optimize power consumption in the cloud data center.","PeriodicalId":442336,"journal":{"name":"Int. J. Cloud Appl. Comput.","volume":"75 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Cloud Appl. Comput.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/ijcac.311035","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Due to the growth of the internet and internet-based software applications, cloud data center demand has increased. Cloud data centers have thousands of servers that are 24×7 working for users; it is the strong witness of enormous energy consumption for the operation of the cloud data center. However, server utilization is not remaining the same all the time, so, from an economic feasibility point of view, energy management is an essential activity for cloud resource management. Some well-known energy management techniques for cloud data centers generally used are dynamic voltage and frequency scaling (DVFS), dynamic power management (DPM), and task scheduling-based techniques. The present work is based on an analytical approach to integrating resource provisioning with sophisticated task scheduling; the authors estimate energy utilization by cloud data centers using iDR cloud simulator. The work is intended to optimize power consumption in the cloud data center.
云数据中心能源利用估算:iDR模拟与建模
由于互联网和基于互联网的软件应用的增长,云数据中心的需求不断增加。云数据中心有成千上万台服务器24×7为用户服务;这是云数据中心运行能耗巨大的有力见证。然而,服务器利用率并不是一直保持不变的,因此,从经济可行性的角度来看,能源管理是云资源管理的一项基本活动。云数据中心通常使用的一些著名的能源管理技术是动态电压和频率缩放(DVFS)、动态电源管理(DPM)和基于任务调度的技术。目前的工作是基于一种分析方法,将资源供应与复杂的任务调度相结合;作者使用iDR云模拟器估算了云数据中心的能源利用率。这项工作旨在优化云数据中心的功耗。
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