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Conference Paper: SmartDPSS: cost-minimizing multi-source power supply for datacenters with arbitrary demand

TitleSmartDPSS: cost-minimizing multi-source power supply for datacenters with arbitrary demand
Authors
Issue Date2013
PublisherIEEE Computer Society.
Citation
The 33rd IEEE International Conference on Distributed Computing Systems (ICDCS 2013), Philadelphia, PA., 8-11 July 2013. In International Conference on Distributed Computing Systems Proceedings, 2013, p. 420-429 How to Cite?
AbstractTo tackle soaring power costs, significant carbon emission and unexpected power outage, Cloud Service Providers (CSPs) typically equip their Datacenters with a Power Supply System (DPSS) nurtured by multiple sources: (1) smart grid with time-varying electricity prices, (2) uninterrupted power supply (UPS), and (3) renewable energy with intermittent and uncertain supply. It remains a significant challenge how to operate among multiple power supply sources in a complementary manner, to deliver reliable energy to datacenter users with arbitrary demand over time, while minimizing a CSP's operation cost over the long run. This paper proposes an efficient, online control algorithm for DPSS, SmartDPSS, based on the two-timescale Lyapunov optimization techniques. Without requiring a priori knowledge of system statistics, SmartDPSS allows CSPs to make online decisions on how much power demand, including delay-sensitive demand and delay-tolerant demand, to serve at each time, the amount of power to purchase from the long-term-ahead and realtime grid markets, and charging and discharging of UPS over time, in order to fully leverage the available renewable energy and time-varying prices from the grid markets, for minimum operational cost. We thoroughly analyze the performance of our online control algorithm with rigorous theoretical analysis. We also demonstrate its optimality in terms of operational cost, demand service delay, datacenter availability, system robustness and scalability, using extensive simulations based on one-month worth of traces from live power systems. © 2013 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/186485
ISBN
ISSN
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorDeng, Wen_US
dc.contributor.authorLiu, Fen_US
dc.contributor.authorJin, Hen_US
dc.contributor.authorWu, Cen_US
dc.date.accessioned2013-08-20T12:11:10Z-
dc.date.available2013-08-20T12:11:10Z-
dc.date.issued2013en_US
dc.identifier.citationThe 33rd IEEE International Conference on Distributed Computing Systems (ICDCS 2013), Philadelphia, PA., 8-11 July 2013. In International Conference on Distributed Computing Systems Proceedings, 2013, p. 420-429en_US
dc.identifier.isbn978-076955000-8-
dc.identifier.issn1063-6927-
dc.identifier.urihttp://hdl.handle.net/10722/186485-
dc.description.abstractTo tackle soaring power costs, significant carbon emission and unexpected power outage, Cloud Service Providers (CSPs) typically equip their Datacenters with a Power Supply System (DPSS) nurtured by multiple sources: (1) smart grid with time-varying electricity prices, (2) uninterrupted power supply (UPS), and (3) renewable energy with intermittent and uncertain supply. It remains a significant challenge how to operate among multiple power supply sources in a complementary manner, to deliver reliable energy to datacenter users with arbitrary demand over time, while minimizing a CSP's operation cost over the long run. This paper proposes an efficient, online control algorithm for DPSS, SmartDPSS, based on the two-timescale Lyapunov optimization techniques. Without requiring a priori knowledge of system statistics, SmartDPSS allows CSPs to make online decisions on how much power demand, including delay-sensitive demand and delay-tolerant demand, to serve at each time, the amount of power to purchase from the long-term-ahead and realtime grid markets, and charging and discharging of UPS over time, in order to fully leverage the available renewable energy and time-varying prices from the grid markets, for minimum operational cost. We thoroughly analyze the performance of our online control algorithm with rigorous theoretical analysis. We also demonstrate its optimality in terms of operational cost, demand service delay, datacenter availability, system robustness and scalability, using extensive simulations based on one-month worth of traces from live power systems. © 2013 IEEE.-
dc.languageengen_US
dc.publisherIEEE Computer Society.-
dc.relation.ispartofInternational Conference on Distributed Computing Systems Proceedingsen_US
dc.rightsInternational Conference on Distributed Computing Systems Proceedings. Copyright © IEEE Computer Society.-
dc.rights©2013 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.titleSmartDPSS: cost-minimizing multi-source power supply for datacenters with arbitrary demanden_US
dc.typeConference_Paperen_US
dc.identifier.emailWu, C: cwu@cs.hku.hken_US
dc.identifier.authorityWu, C=rp01397en_US
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/ICDCS.2013.59-
dc.identifier.scopuseid_2-s2.0-84893260137-
dc.identifier.hkuros217649en_US
dc.identifier.spage420-
dc.identifier.epage429-
dc.identifier.isiWOS:000333267200042-
dc.publisher.placeUnited States-
dc.customcontrol.immutablesml 140307-

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