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CloudHeat: An Efficient Online Market Mechanism for Datacenter Heat Harvesting: ACM Transactions on Modeling and Performance Evaluation of Computing Systems: Vol 3, No 3

research-article

CloudHeat: An Efficient Online Market Mechanism for Datacenter Heat Harvesting

Authors:

Shaolei RenAuthors Info & Claims

ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS), Volume 3, Issue 3

Article No.: 11, Pages 1 - 31

https://doi.org/10.1145/3199675

Published: 13 June 2018 Publication History

Abstract

Datacenters are major energy consumers and dissipate an enormous amount of waste heat. Simple outdoor discharging of datacenter heat is energy-consuming and environmentally unfriendly. By harvesting datacenter waste heat and selling to the district heating system (DHS), both energy cost compensation and environment protection can be achieved. To realize such benefits in practice, an efficient market mechanism is required to incentivize the participation of datacenters. This work proposes CloudHeat, an online reverse auction mechanism for the DHS to solicit heat bids from datacenters. To minimize long-term social operational cost of the DHS and the datacenters, we apply a RFHC approach for decomposing the long-term problem into a series of one-round auctions, guaranteeing a small loss in competitive ratio. The one-round optimization is still NP-hard, and we employ a randomized auction framework to simultaneously guarantee truthfulness, polynomial running time, and an approximation ratio of 2. The performance of CloudHeat is validated through theoretical analysis and trace-driven simulation studies.

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CloudHeat: An Efficient Online Market Mechanism for Datacenter Heat Harvesting

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Published In

cover image ACM Transactions on Modeling and Performance Evaluation of Computing Systems

ACM Transactions on Modeling and Performance Evaluation of Computing Systems Volume 3, Issue 3

September 2018

138 pages

ISSN:2376-3639

EISSN:2376-3647

DOI:10.1145/3232716

Editors:
Sem Borst
Nokia Bell Labs / Eindhoven University of Technology, Netherlands
,
Carey Williamson
University of Calgary, Canada

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Copyright © 2018 ACM.

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Publication History

Published: 13 June 2018

Accepted: 01 March 2018

Revised: 01 November 2017

Received: 01 April 2017

Published in TOMPECS Volume 3, Issue 3

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https://doi.org/10.1109/CEEPE62022.2024.10586281
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