An Incentive Mechanism for Improving Energy Efficiency of Colocation Data Centers Based on Power Prediction

Ce Chi; Kaixuan Ji; Avinab Marahatta; Fa Zhang; Youshi Wang; Zhiyong Liu

doi:10.1109/ISCC50000.2020.9219590

An Incentive Mechanism for Improving Energy Efficiency of Colocation Data Centers Based on Power Prediction

Ce Chi
, Kaixuan Ji
, Avinab Marahatta
, Fa Zhang
, Youshi Wang
, Zhiyong Liu

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

1 Citation (Scopus)

Abstract

Colocation data centers (colocations, for short) are developing rapidly in recent years, resulting in a heavy burden on the power grid and the environment. Due to the special management mode of colocations, even the colocation operators wish to reduce their power demand, they have no authority to control the servers because the servers belong to and are operated by the tenants themselves. To solve the "uncoordinated relationship"issue between operators and tenants, a truthful and feasible incentive mechanism MesPP is proposed in this paper. Different from existing works, MesPP aims at maximizing the energy reduction of colocations with a limited cost budget and can be applied even there is no demand response (DR) program. Meanwhile, power prediction is integrated into MesPP to further improve the energy efficiency of colocations and fairness of the mechanism. To solve the optimization problem, we develop a (1-ϵ)-approximation algorithm. Simulations are performed and show that MesPP can achieve 12.23% more energy saving compared with existing incentive mechanisms.

Original language	English
Title of host publication	2020 IEEE Symposium on Computers and Communications, ISCC 2020
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728180861
DOIs	https://doi.org/10.1109/ISCC50000.2020.9219590
Publication status	Published - Jul 2020
Externally published	Yes
Event	2020 IEEE Symposium on Computers and Communications, ISCC 2020 - Rennes, France Duration: 7 Jul 2020 → 10 Jul 2020

Publication series

Name	Proceedings - IEEE Symposium on Computers and Communications
Volume	2020-July
ISSN (Print)	1530-1346

Conference

Conference	2020 IEEE Symposium on Computers and Communications, ISCC 2020
Country/Territory	France
City	Rennes
Period	7/07/20 → 10/07/20

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

Colocation data center
energy efficiency
mechanism design
power prediction

Access to Document

10.1109/ISCC50000.2020.9219590

Cite this

Chi, C., Ji, K., Marahatta, A., Zhang, F., Wang, Y., & Liu, Z. (2020). An Incentive Mechanism for Improving Energy Efficiency of Colocation Data Centers Based on Power Prediction. In 2020 IEEE Symposium on Computers and Communications, ISCC 2020 Article 9219590 (Proceedings - IEEE Symposium on Computers and Communications; Vol. 2020-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISCC50000.2020.9219590

@inproceedings{a79afafafca74f0d889c79cca7a915da,

title = "An Incentive Mechanism for Improving Energy Efficiency of Colocation Data Centers Based on Power Prediction",

abstract = "Colocation data centers (colocations, for short) are developing rapidly in recent years, resulting in a heavy burden on the power grid and the environment. Due to the special management mode of colocations, even the colocation operators wish to reduce their power demand, they have no authority to control the servers because the servers belong to and are operated by the tenants themselves. To solve the {"}uncoordinated relationship{"}issue between operators and tenants, a truthful and feasible incentive mechanism MesPP is proposed in this paper. Different from existing works, MesPP aims at maximizing the energy reduction of colocations with a limited cost budget and can be applied even there is no demand response (DR) program. Meanwhile, power prediction is integrated into MesPP to further improve the energy efficiency of colocations and fairness of the mechanism. To solve the optimization problem, we develop a (1-ϵ)-approximation algorithm. Simulations are performed and show that MesPP can achieve 12.23\% more energy saving compared with existing incentive mechanisms.",

keywords = "Colocation data center, energy efficiency, mechanism design, power prediction",

author = "Ce Chi and Kaixuan Ji and Avinab Marahatta and Fa Zhang and Youshi Wang and Zhiyong Liu",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 IEEE Symposium on Computers and Communications, ISCC 2020 ; Conference date: 07-07-2020 Through 10-07-2020",

year = "2020",

month = jul,

doi = "10.1109/ISCC50000.2020.9219590",

language = "English",

series = "Proceedings - IEEE Symposium on Computers and Communications",

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

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}

Chi, C, Ji, K, Marahatta, A, Zhang, F, Wang, Y & Liu, Z 2020, An Incentive Mechanism for Improving Energy Efficiency of Colocation Data Centers Based on Power Prediction. in 2020 IEEE Symposium on Computers and Communications, ISCC 2020., 9219590, Proceedings - IEEE Symposium on Computers and Communications, vol. 2020-July, Institute of Electrical and Electronics Engineers Inc., 2020 IEEE Symposium on Computers and Communications, ISCC 2020, Rennes, France, 7/07/20. https://doi.org/10.1109/ISCC50000.2020.9219590

An Incentive Mechanism for Improving Energy Efficiency of Colocation Data Centers Based on Power Prediction. / Chi, Ce; Ji, Kaixuan; Marahatta, Avinab et al.
2020 IEEE Symposium on Computers and Communications, ISCC 2020. Institute of Electrical and Electronics Engineers Inc., 2020. 9219590 (Proceedings - IEEE Symposium on Computers and Communications; Vol. 2020-July).

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

TY - GEN

T1 - An Incentive Mechanism for Improving Energy Efficiency of Colocation Data Centers Based on Power Prediction

AU - Chi, Ce

AU - Ji, Kaixuan

AU - Marahatta, Avinab

AU - Zhang, Fa

AU - Wang, Youshi

AU - Liu, Zhiyong

PY - 2020/7

Y1 - 2020/7

N2 - Colocation data centers (colocations, for short) are developing rapidly in recent years, resulting in a heavy burden on the power grid and the environment. Due to the special management mode of colocations, even the colocation operators wish to reduce their power demand, they have no authority to control the servers because the servers belong to and are operated by the tenants themselves. To solve the "uncoordinated relationship"issue between operators and tenants, a truthful and feasible incentive mechanism MesPP is proposed in this paper. Different from existing works, MesPP aims at maximizing the energy reduction of colocations with a limited cost budget and can be applied even there is no demand response (DR) program. Meanwhile, power prediction is integrated into MesPP to further improve the energy efficiency of colocations and fairness of the mechanism. To solve the optimization problem, we develop a (1-ϵ)-approximation algorithm. Simulations are performed and show that MesPP can achieve 12.23% more energy saving compared with existing incentive mechanisms.

AB - Colocation data centers (colocations, for short) are developing rapidly in recent years, resulting in a heavy burden on the power grid and the environment. Due to the special management mode of colocations, even the colocation operators wish to reduce their power demand, they have no authority to control the servers because the servers belong to and are operated by the tenants themselves. To solve the "uncoordinated relationship"issue between operators and tenants, a truthful and feasible incentive mechanism MesPP is proposed in this paper. Different from existing works, MesPP aims at maximizing the energy reduction of colocations with a limited cost budget and can be applied even there is no demand response (DR) program. Meanwhile, power prediction is integrated into MesPP to further improve the energy efficiency of colocations and fairness of the mechanism. To solve the optimization problem, we develop a (1-ϵ)-approximation algorithm. Simulations are performed and show that MesPP can achieve 12.23% more energy saving compared with existing incentive mechanisms.

KW - Colocation data center

KW - energy efficiency

KW - mechanism design

KW - power prediction

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M3 - Conference contribution

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BT - 2020 IEEE Symposium on Computers and Communications, ISCC 2020

PB - Institute of Electrical and Electronics Engineers Inc.

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ER -

Chi C, Ji K, Marahatta A, Zhang F, Wang Y, Liu Z. An Incentive Mechanism for Improving Energy Efficiency of Colocation Data Centers Based on Power Prediction. In 2020 IEEE Symposium on Computers and Communications, ISCC 2020. Institute of Electrical and Electronics Engineers Inc. 2020. 9219590. (Proceedings - IEEE Symposium on Computers and Communications). doi: 10.1109/ISCC50000.2020.9219590

An Incentive Mechanism for Improving Energy Efficiency of Colocation Data Centers Based on Power Prediction

Abstract

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UN SDGs

Keywords

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