research-article

An online incentive mechanism for emergency demand response in geo-distributed colocation data centers

Authors:

Zongpeng LiAuthors Info & Claims

e-Energy '16: Proceedings of the Seventh International Conference on Future Energy Systems

Article No.: 3, Pages 1 - 13

https://doi.org/10.1145/2934328.2934331

Published: 21 June 2016 Publication History

Abstract

Deferring batch workload in data centers is promising for demand response to enhance the efficiency and reliability of a power grid. Yet operators of multi-tenant colocation data centers still resort to eco-unfriendly diesel generators for demand response, because tenants lack incentives to defer their workloads. This work proposes an online auction mechanism for emergency demand response (EDR) in geo-distributed colocation data centers, which incentivizes tenants to delay and shuffle their workload across multiple data centers by providing monetary rewards. The mechanism, called BatchEDR, decides the tenants' workload deferment/reduction and diesel usage in each data center upon receiving an EDR signal, for cost minimization throughout the entire EDR event, considering that only a limited amount of batch workloads can be deferred throughout EDR as well as across multiple data centers. Without future information, BatchEDR achieves a good competitive ratio compared to an omniscient offline optimal algorithm, while ensuring truthfulness and individual rationality over the auction process. Trace-driven experiments show that BatchEDR outperforms the existing mechanisms and achieves good social cost.

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Cited By

Lin LChien A(2023)Adapting Datacenter Capacity for Greener Datacenters and GridProceedings of the 14th ACM International Conference on Future Energy Systems10.1145/3575813.3595197(200-213)Online publication date: 20-Jun-2023
https://dl.acm.org/doi/10.1145/3575813.3595197
Liu XHua YLiu XYang LSun Y(2023)Design and Implementation of Smooth Renewable Power in Cloud Data CentersIEEE Transactions on Cloud Computing10.1109/TCC.2021.307697811:1(85-96)Online publication date: 1-Jan-2023
https://doi.org/10.1109/TCC.2021.3076978
Venkataswamy VGrigsby JGrimshaw AQi Y(2023)RARE: Renewable Energy Aware Resource Management in DatacentersJob Scheduling Strategies for Parallel Processing10.1007/978-3-031-22698-4_6(108-130)Online publication date: 12-Jan-2023
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Index Terms

An online incentive mechanism for emergency demand response in geo-distributed colocation data centers

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cover image ACM Other conferences

e-Energy '16: Proceedings of the Seventh International Conference on Future Energy Systems

June 2016

266 pages

ISBN:9781450343930

DOI:10.1145/2934328

Copyright © 2016 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Publication History

Published: 21 June 2016

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e-Energy'16

e-Energy'16: The Seventh International Conference on Future Energy Systems

June 21 - 24, 2016

Ontario, Waterloo, Canada

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Overall Acceptance Rate 160 of 446 submissions, 36%

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Cited By

Lin LChien A(2023)Adapting Datacenter Capacity for Greener Datacenters and GridProceedings of the 14th ACM International Conference on Future Energy Systems10.1145/3575813.3595197(200-213)Online publication date: 20-Jun-2023
https://dl.acm.org/doi/10.1145/3575813.3595197
Liu XHua YLiu XYang LSun Y(2023)Design and Implementation of Smooth Renewable Power in Cloud Data CentersIEEE Transactions on Cloud Computing10.1109/TCC.2021.307697811:1(85-96)Online publication date: 1-Jan-2023
https://doi.org/10.1109/TCC.2021.3076978
Venkataswamy VGrigsby JGrimshaw AQi Y(2023)RARE: Renewable Energy Aware Resource Management in DatacentersJob Scheduling Strategies for Parallel Processing10.1007/978-3-031-22698-4_6(108-130)Online publication date: 12-Jan-2023
https://doi.org/10.1007/978-3-031-22698-4_6
Zhang YWilson DPaschalidis ICoskun A(2022)HPC Data Center Participation in Demand Response: An Adaptive Policy With QoS AssuranceIEEE Transactions on Sustainable Computing10.1109/TSUSC.2021.30772547:1(157-171)Online publication date: 1-Jan-2022
https://doi.org/10.1109/TSUSC.2021.3077254
Chen SJiao LLiu FWang L(2022)EdgeDR: An Online Mechanism Design for Demand Response in Edge CloudsIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2021.308736033:2(343-358)Online publication date: 1-Feb-2022
https://doi.org/10.1109/TPDS.2021.3087360
Nafus DSchooler EBurch K(2021)Carbon-Responsive Computing: Changing the Nexus between Energy and ComputingEnergies10.3390/en1421691714:21(6917)Online publication date: 21-Oct-2021
https://doi.org/10.3390/en14216917
Lin LZavala VChien A(2021)Evaluating Coupling Models for Cloud Datacenters and Power GridsProceedings of the Twelfth ACM International Conference on Future Energy Systems10.1145/3447555.3464868(171-184)Online publication date: 22-Jun-2021
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Song ZZhou RZhao SQin SLui JLi Z(2020)Emergency demand response in edge computingEURASIP Journal on Wireless Communications and Networking10.1186/s13638-020-01789-z2020:1Online publication date: 10-Sep-2020
https://doi.org/10.1186/s13638-020-01789-z
Xu HJin XKong FDeng Q(2020)Two Level Colocation Demand Response with Renewable EnergyIEEE Transactions on Sustainable Computing10.1109/TSUSC.2019.29048675:1(147-159)Online publication date: 1-Jan-2020
https://doi.org/10.1109/TSUSC.2019.2904867
Islam MMahmud HRen SWang X(2020)A Carbon-Aware Incentive Mechanism for Greening Colocation Data CentersIEEE Transactions on Cloud Computing10.1109/TCC.2017.27670438:1(4-16)Online publication date: 1-Jan-2020
https://doi.org/10.1109/TCC.2017.2767043
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