Joint Energy Optimization on the Server and Network Sides for Geo-Distributed Datacenters

Yang Qin; Wuji Han; Yuanyuan Yang; Weihong Yang; Bing Liu

doi:10.1109/ICC.2019.8761333

Joint Energy Optimization on the Server and Network Sides for Geo-Distributed Datacenters

Yang Qin^*
, Wuji Han
, Yuanyuan Yang
, Weihong Yang
, Bing Liu

^*Corresponding author for this work

Harbin Institute of Technology Shenzhen
Stony Brook University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

With the rapid development of cloud computing, many cloud service providers have been deploying more and more datacenters to provide better reliability and quality of service. The energy optimization problem has become an emerging concern. The current researches focus on how to either reduce the energy consumption of servers or reduce the consumption of inter-datacenters data transmission. However, energy optimization of joint inter-datacenter and servers has not been explored. In this paper, we first introduced the background to the energy consumption problem of geographically distributed datacenters. Then, based on the Service Level Agreement (SLA), this paper proposes an online control framework to minimize the energy consummation cost. The online control framework can dynamically make decisions by adjusting geographically load balancing, capacity right-sizing, server speed scaling, and flow programming. Finally, the simulation verifies the effectiveness of the proposed framework in cost saving.

Original language	English
Title of host publication	2019 IEEE International Conference on Communications, ICC 2019 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781538680889
DOIs	https://doi.org/10.1109/ICC.2019.8761333
State	Published - May 2019
Externally published	Yes
Event	2019 IEEE International Conference on Communications, ICC 2019 - Shanghai, China Duration: 20 May 2019 → 24 May 2019

Publication series

Name	IEEE International Conference on Communications
Volume	2019-May
ISSN (Print)	1550-3607

Conference

Conference	2019 IEEE International Conference on Communications, ICC 2019
Country/Territory	China
City	Shanghai
Period	20/05/19 → 24/05/19

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

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10.1109/ICC.2019.8761333

Cite this

Qin, Y., Han, W., Yang, Y., Yang, W., & Liu, B. (2019). Joint Energy Optimization on the Server and Network Sides for Geo-Distributed Datacenters. In 2019 IEEE International Conference on Communications, ICC 2019 - Proceedings Article 8761333 (IEEE International Conference on Communications; Vol. 2019-May). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICC.2019.8761333

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title = "Joint Energy Optimization on the Server and Network Sides for Geo-Distributed Datacenters",

abstract = "With the rapid development of cloud computing, many cloud service providers have been deploying more and more datacenters to provide better reliability and quality of service. The energy optimization problem has become an emerging concern. The current researches focus on how to either reduce the energy consumption of servers or reduce the consumption of inter-datacenters data transmission. However, energy optimization of joint inter-datacenter and servers has not been explored. In this paper, we first introduced the background to the energy consumption problem of geographically distributed datacenters. Then, based on the Service Level Agreement (SLA), this paper proposes an online control framework to minimize the energy consummation cost. The online control framework can dynamically make decisions by adjusting geographically load balancing, capacity right-sizing, server speed scaling, and flow programming. Finally, the simulation verifies the effectiveness of the proposed framework in cost saving.",

author = "Yang Qin and Wuji Han and Yuanyuan Yang and Weihong Yang and Bing Liu",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE International Conference on Communications, ICC 2019 ; Conference date: 20-05-2019 Through 24-05-2019",

year = "2019",

month = may,

doi = "10.1109/ICC.2019.8761333",

language = "英语",

series = "IEEE International Conference on Communications",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2019 IEEE International Conference on Communications, ICC 2019 - Proceedings",

address = "美国",

}

Qin, Y, Han, W, Yang, Y, Yang, W & Liu, B 2019, Joint Energy Optimization on the Server and Network Sides for Geo-Distributed Datacenters. in 2019 IEEE International Conference on Communications, ICC 2019 - Proceedings., 8761333, IEEE International Conference on Communications, vol. 2019-May, Institute of Electrical and Electronics Engineers Inc., 2019 IEEE International Conference on Communications, ICC 2019, Shanghai, China, 20/05/19. https://doi.org/10.1109/ICC.2019.8761333

Joint Energy Optimization on the Server and Network Sides for Geo-Distributed Datacenters. / Qin, Yang; Han, Wuji; Yang, Yuanyuan et al.
2019 IEEE International Conference on Communications, ICC 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. 8761333 (IEEE International Conference on Communications; Vol. 2019-May).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Joint Energy Optimization on the Server and Network Sides for Geo-Distributed Datacenters

AU - Qin, Yang

AU - Han, Wuji

AU - Yang, Yuanyuan

AU - Yang, Weihong

AU - Liu, Bing

PY - 2019/5

Y1 - 2019/5

N2 - With the rapid development of cloud computing, many cloud service providers have been deploying more and more datacenters to provide better reliability and quality of service. The energy optimization problem has become an emerging concern. The current researches focus on how to either reduce the energy consumption of servers or reduce the consumption of inter-datacenters data transmission. However, energy optimization of joint inter-datacenter and servers has not been explored. In this paper, we first introduced the background to the energy consumption problem of geographically distributed datacenters. Then, based on the Service Level Agreement (SLA), this paper proposes an online control framework to minimize the energy consummation cost. The online control framework can dynamically make decisions by adjusting geographically load balancing, capacity right-sizing, server speed scaling, and flow programming. Finally, the simulation verifies the effectiveness of the proposed framework in cost saving.

AB - With the rapid development of cloud computing, many cloud service providers have been deploying more and more datacenters to provide better reliability and quality of service. The energy optimization problem has become an emerging concern. The current researches focus on how to either reduce the energy consumption of servers or reduce the consumption of inter-datacenters data transmission. However, energy optimization of joint inter-datacenter and servers has not been explored. In this paper, we first introduced the background to the energy consumption problem of geographically distributed datacenters. Then, based on the Service Level Agreement (SLA), this paper proposes an online control framework to minimize the energy consummation cost. The online control framework can dynamically make decisions by adjusting geographically load balancing, capacity right-sizing, server speed scaling, and flow programming. Finally, the simulation verifies the effectiveness of the proposed framework in cost saving.

UR - https://www.scopus.com/pages/publications/85070217664

U2 - 10.1109/ICC.2019.8761333

DO - 10.1109/ICC.2019.8761333

M3 - 会议稿件

AN - SCOPUS:85070217664

T3 - IEEE International Conference on Communications

BT - 2019 IEEE International Conference on Communications, ICC 2019 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2019 IEEE International Conference on Communications, ICC 2019

Y2 - 20 May 2019 through 24 May 2019

ER -

Joint Energy Optimization on the Server and Network Sides for Geo-Distributed Datacenters

Abstract

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