Carbon-aware Load Balancing for Geo-distributed Cloud Services

Zhi Zhou; Fangming Liu; Yong Xu; Ruolan Zou; Hong Xu; John C.S. Lui; Hai Jin

doi:10.1109/MASCOTS.2013.31

Carbon-aware Load Balancing for Geo-distributed Cloud Services

Zhi Zhou, Fangming Liu^*, Yong Xu, Ruolan Zou, Hong Xu, John C.S. Lui, Hai Jin

^*Corresponding author for this work

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

98 Citations (Scopus)

Abstract

Recently, datacenter carbon emission has become an emerging concern for the cloud service providers. Previous works are limited on cutting down the power consumption ofthe datacenters to defuse such a concern. In this paper, we show how the spatial and temporal variabilities of the electricity carbon footprint can be fully exploited to further green the cloud running on top of geographically distributed datacenters. We jointly consider the electricity cost, service level agreement (SLA) requirement, and emission reduction budget. To navigate such a three-way tradeoff, we take advantage of Lyapunov optimization techniques to design and analyze a carbon-aware control framework, which makes online decisions on geographical load balancing, capacity right-sizing, and server speed scaling. Results from rigorous mathematical analyses and real-world trace-driven empirical evaluation demonstrate its effectiveness in both minimizing electricity cost and reducing carbon emission.

Original language	English
Title of host publication	Proceedings - 2013 IEEE 21st International Symposium on Modeling, Analysis & Simulation of Computer and Telecommunication, MASCOTS 2013
Pages	232-241
DOIs	https://doi.org/10.1109/MASCOTS.2013.31
Publication status	Published - Aug 2013
Externally published	Yes
Event	2013 IEEE 21st International Symposium on Modeling, Analysis & Simulation of Computer and Telecommunication Systems (MASCOTS 2013) - San Francisco, United States Duration: 14 Aug 2013 → 16 Aug 2013

Publication series

Name
ISSN (Print)	1526-7539

Conference

Conference	2013 IEEE 21st International Symposium on Modeling, Analysis & Simulation of Computer and Telecommunication Systems (MASCOTS 2013)
Place	United States
City	San Francisco
Period	14/08/13 → 16/08/13

UN SDGs

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

SDG 12 Responsible Consumption and Production
SDG 13 Climate Action

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@inproceedings{5fc1d19b65174ff08706cd9071c73551,

title = "Carbon-aware Load Balancing for Geo-distributed Cloud Services",

abstract = "Recently, datacenter carbon emission has become an emerging concern for the cloud service providers. Previous works are limited on cutting down the power consumption ofthe datacenters to defuse such a concern. In this paper, we show how the spatial and temporal variabilities of the electricity carbon footprint can be fully exploited to further green the cloud running on top of geographically distributed datacenters. We jointly consider the electricity cost, service level agreement (SLA) requirement, and emission reduction budget. To navigate such a three-way tradeoff, we take advantage of Lyapunov optimization techniques to design and analyze a carbon-aware control framework, which makes online decisions on geographical load balancing, capacity right-sizing, and server speed scaling. Results from rigorous mathematical analyses and real-world trace-driven empirical evaluation demonstrate its effectiveness in both minimizing electricity cost and reducing carbon emission.",

author = "Zhi Zhou and Fangming Liu and Yong Xu and Ruolan Zou and Hong Xu and Lui, {John C.S.} and Hai Jin",

year = "2013",

month = aug,

doi = "10.1109/MASCOTS.2013.31",

language = "English",

isbn = "9780769551029",

pages = "232--241",

booktitle = "Proceedings - 2013 IEEE 21st International Symposium on Modeling, Analysis & Simulation of Computer and Telecommunication, MASCOTS 2013",

note = "2013 IEEE 21st International Symposium on Modeling, Analysis & Simulation of Computer and Telecommunication Systems (MASCOTS 2013) ; Conference date: 14-08-2013 Through 16-08-2013",

}

Zhou, Z, Liu, F, Xu, Y, Zou, R, Xu, H, Lui, JCS & Jin, H 2013, Carbon-aware Load Balancing for Geo-distributed Cloud Services. in Proceedings - 2013 IEEE 21st International Symposium on Modeling, Analysis & Simulation of Computer and Telecommunication, MASCOTS 2013., 6730766, pp. 232-241, 2013 IEEE 21st International Symposium on Modeling, Analysis & Simulation of Computer and Telecommunication Systems (MASCOTS 2013), San Francisco, California, United States, 14/08/13. https://doi.org/10.1109/MASCOTS.2013.31

Carbon-aware Load Balancing for Geo-distributed Cloud Services. / Zhou, Zhi; Liu, Fangming; Xu, Yong et al.
Proceedings - 2013 IEEE 21st International Symposium on Modeling, Analysis & Simulation of Computer and Telecommunication, MASCOTS 2013. 2013. p. 232-241 6730766.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Carbon-aware Load Balancing for Geo-distributed Cloud Services

AU - Zhou, Zhi

AU - Liu, Fangming

AU - Xu, Yong

AU - Zou, Ruolan

AU - Xu, Hong

AU - Lui, John C.S.

AU - Jin, Hai

PY - 2013/8

Y1 - 2013/8

N2 - Recently, datacenter carbon emission has become an emerging concern for the cloud service providers. Previous works are limited on cutting down the power consumption ofthe datacenters to defuse such a concern. In this paper, we show how the spatial and temporal variabilities of the electricity carbon footprint can be fully exploited to further green the cloud running on top of geographically distributed datacenters. We jointly consider the electricity cost, service level agreement (SLA) requirement, and emission reduction budget. To navigate such a three-way tradeoff, we take advantage of Lyapunov optimization techniques to design and analyze a carbon-aware control framework, which makes online decisions on geographical load balancing, capacity right-sizing, and server speed scaling. Results from rigorous mathematical analyses and real-world trace-driven empirical evaluation demonstrate its effectiveness in both minimizing electricity cost and reducing carbon emission.

AB - Recently, datacenter carbon emission has become an emerging concern for the cloud service providers. Previous works are limited on cutting down the power consumption ofthe datacenters to defuse such a concern. In this paper, we show how the spatial and temporal variabilities of the electricity carbon footprint can be fully exploited to further green the cloud running on top of geographically distributed datacenters. We jointly consider the electricity cost, service level agreement (SLA) requirement, and emission reduction budget. To navigate such a three-way tradeoff, we take advantage of Lyapunov optimization techniques to design and analyze a carbon-aware control framework, which makes online decisions on geographical load balancing, capacity right-sizing, and server speed scaling. Results from rigorous mathematical analyses and real-world trace-driven empirical evaluation demonstrate its effectiveness in both minimizing electricity cost and reducing carbon emission.

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DO - 10.1109/MASCOTS.2013.31

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SN - 9780769551029

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EP - 241

BT - Proceedings - 2013 IEEE 21st International Symposium on Modeling, Analysis & Simulation of Computer and Telecommunication, MASCOTS 2013

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Y2 - 14 August 2013 through 16 August 2013

ER -

Carbon-aware Load Balancing for Geo-distributed Cloud Services

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