基于云计算的节能调度技术综述

IF 0.6 Q4 COMPUTER SCIENCE, THEORY & METHODS Multiagent and Grid Systems Pub Date : 2022-03-07 DOI:10.3233/mgs-220357
N. Kaur, S. Bansal, R. Bansal
{"title":"基于云计算的节能调度技术综述","authors":"N. Kaur, S. Bansal, R. Bansal","doi":"10.3233/mgs-220357","DOIUrl":null,"url":null,"abstract":"With ever-growing technical advances, performance of complex scientific and engineering applications has arrived at petaflops and exaflops range. However, massive power drawn from the large scale computing infrastructure has caused commensurate rise in electricity consumption, escalating data center ownership costs besides leaving carbon footprints. Judicious scheduling of complex applications with an objective to reduce overall makespan and reduced energy consumption has become one of the biggest confront in the realm of computing architectures. This paper presents a survey on energy efficient scheduling algorithms based on dynamic voltage and frequency scaling (DVFS) and dynamic power management (DPM) techniques. The parameters considered are mainly the makespan, processor energy (dynamic and static) consumption, and network energy (communication) consumption, wherever appropriate during task scheduling.","PeriodicalId":43659,"journal":{"name":"Multiagent and Grid Systems","volume":null,"pages":null},"PeriodicalIF":0.6000,"publicationDate":"2022-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Survey on energy efficient scheduling techniques on cloud computing\",\"authors\":\"N. Kaur, S. Bansal, R. Bansal\",\"doi\":\"10.3233/mgs-220357\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With ever-growing technical advances, performance of complex scientific and engineering applications has arrived at petaflops and exaflops range. However, massive power drawn from the large scale computing infrastructure has caused commensurate rise in electricity consumption, escalating data center ownership costs besides leaving carbon footprints. Judicious scheduling of complex applications with an objective to reduce overall makespan and reduced energy consumption has become one of the biggest confront in the realm of computing architectures. This paper presents a survey on energy efficient scheduling algorithms based on dynamic voltage and frequency scaling (DVFS) and dynamic power management (DPM) techniques. The parameters considered are mainly the makespan, processor energy (dynamic and static) consumption, and network energy (communication) consumption, wherever appropriate during task scheduling.\",\"PeriodicalId\":43659,\"journal\":{\"name\":\"Multiagent and Grid Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2022-03-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Multiagent and Grid Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3233/mgs-220357\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, THEORY & METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Multiagent and Grid Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/mgs-220357","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
引用次数: 0

摘要

随着技术的不断进步,复杂的科学和工程应用的性能已经达到千万亿次和百亿亿次。然而,从大规模计算基础设施中获取的大量电力导致了电力消耗的相应增加,除了留下碳足迹之外,数据中心的所有权成本也在不断上升。以减少总体完工时间和降低能耗为目标的复杂应用程序的明智调度已成为计算体系结构领域面临的最大挑战之一。本文综述了基于动态电压频率缩放(DVFS)和动态功率管理(DPM)技术的节能调度算法。考虑的参数主要是在任务调度过程中适当的makespan、处理器能量(动态和静态)消耗和网络能量(通信)消耗。
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
Survey on energy efficient scheduling techniques on cloud computing
With ever-growing technical advances, performance of complex scientific and engineering applications has arrived at petaflops and exaflops range. However, massive power drawn from the large scale computing infrastructure has caused commensurate rise in electricity consumption, escalating data center ownership costs besides leaving carbon footprints. Judicious scheduling of complex applications with an objective to reduce overall makespan and reduced energy consumption has become one of the biggest confront in the realm of computing architectures. This paper presents a survey on energy efficient scheduling algorithms based on dynamic voltage and frequency scaling (DVFS) and dynamic power management (DPM) techniques. The parameters considered are mainly the makespan, processor energy (dynamic and static) consumption, and network energy (communication) consumption, wherever appropriate during task scheduling.
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
Multiagent and Grid Systems
Multiagent and Grid Systems COMPUTER SCIENCE, THEORY & METHODS-
CiteScore
1.50
自引率
0.00%
发文量
13
期刊最新文献
Blockchain applications for Internet of Things (IoT): A review Sine tangent search algorithm enabled LeNet for cotton crop classification using satellite image Optimization enabled elastic scaling in cloud based on predicted load for resource management Geese jellyfish search optimization trained deep learning for multiclass plant disease detection using leaf images Adam Adadelta Optimization based bidirectional encoder representations from transformers model for fake news detection on social media
×
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