Escope: An Energy Efficiency Simulator for Internet Data Centers

Author:

Liu Jun1,Yan Longchuan1,Yan Chengxu2,Qiu Yeliang2,Jiang Congfeng2ORCID,Li Yang1,Li Yan1,Cérin Christophe3

Affiliation:

1. State Grid Co., Ltd., Information Communication Branch, Beijing 100761, China

2. School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, China

3. IUT de Villetaneuse, Département d’Informatique, University of Paris 13, Sorbonne Paris Cité, LIPN/CNRS UMR 7030, F-93430 Villetaneuse, France

Abstract

Contemporary megawatt-scale data centers have emerged to meet the increasing demand for online cloud services and big data analytics. However, in such large-scale data centers, servers of different generations are installed gradually year by year, making the data center heterogeneous in computing capability and energy efficiency. Furthermore, due to different processor architectures, complex and diverse load dynamic changing, business coupling, and other reasons, operators pay great attention to processor hardware power consumption and server aggregation energy efficiency. Therefore, the simulation and analysis of the energy efficiency characteristics of data center servers under different processor architectures can help operators understand the energy efficiency characteristics of data centers and make the optimal task scheduling strategy. This is very beneficial for improving the energy efficiency of the production system and the entire data center. The Escope simulator designed in this study can simulate the online quantity (placement strategy) of different types of servers in the data center and the optimal operating range of the servers. The purpose of this is to analyze the energy efficiency characteristics of all servers in the data center and provide data center operators with the energy efficiency and energy proportionality characteristics of different servers, improve server utilization, and perform reasonable scheduling. Through the simulation experiment of Escope, it can be proved that running the server at the highest energy efficiency point or running the server under full load cannot improve the energy efficiency of the entire data center. The simulation algorithm provided by Escope can select the optimal set of servers and their corresponding utilization. Escope can set up a variety of simulation strategies, and data center operators can simulate data center energy efficiency according to their own needs. Escope can also calculate the power cost savings of introducing new servers in the data center, which provides an essential reference for operators to purchase servers and design data centers.

Funder

Natural Science Foundation of China

Science and Technology Project of State Grid Corporation of China

Publisher

MDPI AG

Subject

Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous),Building and Construction

Reference41 articles.

1. Cook, G. (2011). How Dirty Is Your Data: A Look at the Energy Choices that Power Cloud Computing, Greenpeace.

2. Pettey, C. (2007). Gartner Estimates ICT Industry Accounts for 2 Percent of Global CO2 Emissions, Gartner Symposium/ITxpo. Available online: http://www.gartner.com/us/symposiumwest.

3. Jyothi, S.A., Curino, C., and Menache, I. (2016, January 2–4). Morpheus: Towards Automated SLOs for Enterprise Clusters. Proceedings of the USENIX OSDI 2016, Savannah, GA, USA.

4. Rajan, K., Kakadia, D., and Curino, C. (2016, January 5–7). PerfOrator: Eloquent performance models for Resource Optimization. Proceedings of the Seventh ACM Symposium on Cloud Computing, Santa Clara, CA, USA.

5. Xu, G., and Xu, C.Z. (2017, January 24–27). Prometheus: Online estimation of optimal memory demands for workers in in-memory distributed computation. Proceedings of the 2017 Symposium on Cloud Computing, Santa Clara, CA, USA.

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3