Lowering down the cost for green cloud data centers by using ESDs and energy trading

Chonglin Gu; Ke Hu; Zhenlong Li; Qiang Yuan; Hejiao Huang; Xiaohua Jia

doi:10.1109/TrustCom.2016.0235

Lowering down the cost for green cloud data centers by using ESDs and energy trading

Chonglin Gu
, Ke Hu
, Zhenlong Li
, Qiang Yuan
, Hejiao Huang^*
, Xiaohua Jia

^*Corresponding author for this work

Harbin Institute of Technology Shenzhen
Shenzhen Key Laboratory of Internet Information Collaboration

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

14 Scopus citations

Abstract

Cloud data centers contribute greatly to global warming, because most of the energy is generated by burning fossil fuels. In view of this, many cloud data centers are trying to power their data centers using renewable energy. In this paper, we propose a green scheduling architecture for the geographically distributed cloud data centers with time-varying and location-varying electricity prices. To lower down the energy cost and carbon emissions, each data center has its own wind turbines and solar panels. The generated renewable energy can be used to power data centers directly or stored into ESDs for latter use, or sold back to the power grid. However, it is hard to make decisions on the usage of each type of energy considering the dynamic incoming requests of users, fluctuating electricity prices, and intermittent energy supply in each time slot. Our problem is formulated as a mixed integer linear programming (MILP) problem: Given the arrival of incoming requests, schedule the requests, servers, and the usage of different energy sources, such that the total energy cost can be minimized while satisfying QoS requirement within certain carbon emission level. Our simulation is based on the traces from real world. Experiments show that our method can significantly lower down the energy cost for green cloud data centers by using ESDs and energy trading.

Original language	English
Title of host publication	Proceedings - 15th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, 10th IEEE International Conference on Big Data Science and Engineering and 14th IEEE International Symposium on Parallel and Distributed Processing with Applications, IEEE TrustCom/BigDataSE/ISPA 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1508-1515
Number of pages	8
ISBN (Electronic)	9781509032051
DOIs	https://doi.org/10.1109/TrustCom.2016.0235
State	Published - 2016
Externally published	Yes
Event	Joint 15th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, 10th IEEE International Conference on Big Data Science and Engineering and 14th IEEE International Symposium on Parallel and Distributed Processing with Applications, IEEE TrustCom/BigDataSE/ISPA 2016 - Tianjin, China Duration: 23 Aug 2016 → 26 Aug 2016

Publication series

Name	Proceedings - 15th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, 10th IEEE International Conference on Big Data Science and Engineering and 14th IEEE International Symposium on Parallel and Distributed Processing with Applications, IEEE TrustCom/BigDataSE/ISPA 2016

Conference

Conference	Joint 15th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, 10th IEEE International Conference on Big Data Science and Engineering and 14th IEEE International Symposium on Parallel and Distributed Processing with Applications, IEEE TrustCom/BigDataSE/ISPA 2016
Country/Territory	China
City	Tianjin
Period	23/08/16 → 26/08/16

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

Cloud
Data center
ESD
Energy trading
Green
Renewable energy

Access to Document

10.1109/TrustCom.2016.0235

Cite this

Gu, C., Hu, K., Li, Z., Yuan, Q., Huang, H., & Jia, X. (2016). Lowering down the cost for green cloud data centers by using ESDs and energy trading. In Proceedings - 15th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, 10th IEEE International Conference on Big Data Science and Engineering and 14th IEEE International Symposium on Parallel and Distributed Processing with Applications, IEEE TrustCom/BigDataSE/ISPA 2016 (pp. 1508-1515). Article 7847118 (Proceedings - 15th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, 10th IEEE International Conference on Big Data Science and Engineering and 14th IEEE International Symposium on Parallel and Distributed Processing with Applications, IEEE TrustCom/BigDataSE/ISPA 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/TrustCom.2016.0235

Gu, Chonglin ; Hu, Ke ; Li, Zhenlong et al. / Lowering down the cost for green cloud data centers by using ESDs and energy trading. Proceedings - 15th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, 10th IEEE International Conference on Big Data Science and Engineering and 14th IEEE International Symposium on Parallel and Distributed Processing with Applications, IEEE TrustCom/BigDataSE/ISPA 2016. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 1508-1515 (Proceedings - 15th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, 10th IEEE International Conference on Big Data Science and Engineering and 14th IEEE International Symposium on Parallel and Distributed Processing with Applications, IEEE TrustCom/BigDataSE/ISPA 2016).

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title = "Lowering down the cost for green cloud data centers by using ESDs and energy trading",

abstract = "Cloud data centers contribute greatly to global warming, because most of the energy is generated by burning fossil fuels. In view of this, many cloud data centers are trying to power their data centers using renewable energy. In this paper, we propose a green scheduling architecture for the geographically distributed cloud data centers with time-varying and location-varying electricity prices. To lower down the energy cost and carbon emissions, each data center has its own wind turbines and solar panels. The generated renewable energy can be used to power data centers directly or stored into ESDs for latter use, or sold back to the power grid. However, it is hard to make decisions on the usage of each type of energy considering the dynamic incoming requests of users, fluctuating electricity prices, and intermittent energy supply in each time slot. Our problem is formulated as a mixed integer linear programming (MILP) problem: Given the arrival of incoming requests, schedule the requests, servers, and the usage of different energy sources, such that the total energy cost can be minimized while satisfying QoS requirement within certain carbon emission level. Our simulation is based on the traces from real world. Experiments show that our method can significantly lower down the energy cost for green cloud data centers by using ESDs and energy trading.",

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author = "Chonglin Gu and Ke Hu and Zhenlong Li and Qiang Yuan and Hejiao Huang and Xiaohua Jia",

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

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booktitle = "Proceedings - 15th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, 10th IEEE International Conference on Big Data Science and Engineering and 14th IEEE International Symposium on Parallel and Distributed Processing with Applications, IEEE TrustCom/BigDataSE/ISPA 2016",

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Gu, C, Hu, K, Li, Z, Yuan, Q, Huang, H & Jia, X 2016, Lowering down the cost for green cloud data centers by using ESDs and energy trading. in Proceedings - 15th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, 10th IEEE International Conference on Big Data Science and Engineering and 14th IEEE International Symposium on Parallel and Distributed Processing with Applications, IEEE TrustCom/BigDataSE/ISPA 2016., 7847118, Proceedings - 15th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, 10th IEEE International Conference on Big Data Science and Engineering and 14th IEEE International Symposium on Parallel and Distributed Processing with Applications, IEEE TrustCom/BigDataSE/ISPA 2016, Institute of Electrical and Electronics Engineers Inc., pp. 1508-1515, Joint 15th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, 10th IEEE International Conference on Big Data Science and Engineering and 14th IEEE International Symposium on Parallel and Distributed Processing with Applications, IEEE TrustCom/BigDataSE/ISPA 2016, Tianjin, China, 23/08/16. https://doi.org/10.1109/TrustCom.2016.0235

Lowering down the cost for green cloud data centers by using ESDs and energy trading. / Gu, Chonglin; Hu, Ke; Li, Zhenlong et al.
Proceedings - 15th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, 10th IEEE International Conference on Big Data Science and Engineering and 14th IEEE International Symposium on Parallel and Distributed Processing with Applications, IEEE TrustCom/BigDataSE/ISPA 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 1508-1515 7847118 (Proceedings - 15th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, 10th IEEE International Conference on Big Data Science and Engineering and 14th IEEE International Symposium on Parallel and Distributed Processing with Applications, IEEE TrustCom/BigDataSE/ISPA 2016).

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

TY - GEN

T1 - Lowering down the cost for green cloud data centers by using ESDs and energy trading

AU - Gu, Chonglin

AU - Hu, Ke

AU - Li, Zhenlong

AU - Yuan, Qiang

AU - Huang, Hejiao

AU - Jia, Xiaohua

PY - 2016

Y1 - 2016

N2 - Cloud data centers contribute greatly to global warming, because most of the energy is generated by burning fossil fuels. In view of this, many cloud data centers are trying to power their data centers using renewable energy. In this paper, we propose a green scheduling architecture for the geographically distributed cloud data centers with time-varying and location-varying electricity prices. To lower down the energy cost and carbon emissions, each data center has its own wind turbines and solar panels. The generated renewable energy can be used to power data centers directly or stored into ESDs for latter use, or sold back to the power grid. However, it is hard to make decisions on the usage of each type of energy considering the dynamic incoming requests of users, fluctuating electricity prices, and intermittent energy supply in each time slot. Our problem is formulated as a mixed integer linear programming (MILP) problem: Given the arrival of incoming requests, schedule the requests, servers, and the usage of different energy sources, such that the total energy cost can be minimized while satisfying QoS requirement within certain carbon emission level. Our simulation is based on the traces from real world. Experiments show that our method can significantly lower down the energy cost for green cloud data centers by using ESDs and energy trading.

AB - Cloud data centers contribute greatly to global warming, because most of the energy is generated by burning fossil fuels. In view of this, many cloud data centers are trying to power their data centers using renewable energy. In this paper, we propose a green scheduling architecture for the geographically distributed cloud data centers with time-varying and location-varying electricity prices. To lower down the energy cost and carbon emissions, each data center has its own wind turbines and solar panels. The generated renewable energy can be used to power data centers directly or stored into ESDs for latter use, or sold back to the power grid. However, it is hard to make decisions on the usage of each type of energy considering the dynamic incoming requests of users, fluctuating electricity prices, and intermittent energy supply in each time slot. Our problem is formulated as a mixed integer linear programming (MILP) problem: Given the arrival of incoming requests, schedule the requests, servers, and the usage of different energy sources, such that the total energy cost can be minimized while satisfying QoS requirement within certain carbon emission level. Our simulation is based on the traces from real world. Experiments show that our method can significantly lower down the energy cost for green cloud data centers by using ESDs and energy trading.

KW - Cloud

KW - Data center

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KW - Energy trading

KW - Green

KW - Renewable energy

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M3 - 会议稿件

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PB - Institute of Electrical and Electronics Engineers Inc.

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Gu C, Hu K, Li Z, Yuan Q, Huang H, Jia X. Lowering down the cost for green cloud data centers by using ESDs and energy trading. In Proceedings - 15th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, 10th IEEE International Conference on Big Data Science and Engineering and 14th IEEE International Symposium on Parallel and Distributed Processing with Applications, IEEE TrustCom/BigDataSE/ISPA 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 1508-1515. 7847118. (Proceedings - 15th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, 10th IEEE International Conference on Big Data Science and Engineering and 14th IEEE International Symposium on Parallel and Distributed Processing with Applications, IEEE TrustCom/BigDataSE/ISPA 2016). doi: 10.1109/TrustCom.2016.0235

Lowering down the cost for green cloud data centers by using ESDs and energy trading

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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