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Conference Paper: SmartDPSS: cost-minimizing multi-source power supply for datacenters with arbitrary demand
Title | SmartDPSS: cost-minimizing multi-source power supply for datacenters with arbitrary demand |
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Authors | |
Issue Date | 2013 |
Publisher | IEEE 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? |
Abstract | To 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 Identifier | http://hdl.handle.net/10722/186485 |
ISBN | |
ISSN | 2023 SCImago Journal Rankings: 0.986 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Deng, W | en_US |
dc.contributor.author | Liu, F | en_US |
dc.contributor.author | Jin, H | en_US |
dc.contributor.author | Wu, C | en_US |
dc.date.accessioned | 2013-08-20T12:11:10Z | - |
dc.date.available | 2013-08-20T12:11:10Z | - |
dc.date.issued | 2013 | en_US |
dc.identifier.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 | en_US |
dc.identifier.isbn | 978-076955000-8 | - |
dc.identifier.issn | 1063-6927 | - |
dc.identifier.uri | http://hdl.handle.net/10722/186485 | - |
dc.description.abstract | To 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.language | eng | en_US |
dc.publisher | IEEE Computer Society. | - |
dc.relation.ispartof | International Conference on Distributed Computing Systems Proceedings | en_US |
dc.title | SmartDPSS: cost-minimizing multi-source power supply for datacenters with arbitrary demand | en_US |
dc.type | Conference_Paper | en_US |
dc.identifier.email | Wu, C: cwu@cs.hku.hk | en_US |
dc.identifier.authority | Wu, C=rp01397 | en_US |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/ICDCS.2013.59 | - |
dc.identifier.scopus | eid_2-s2.0-84893260137 | - |
dc.identifier.hkuros | 217649 | en_US |
dc.identifier.spage | 420 | - |
dc.identifier.epage | 429 | - |
dc.identifier.isi | WOS:000333267200042 | - |
dc.publisher.place | United States | - |
dc.customcontrol.immutable | sml 140307 | - |
dc.identifier.issnl | 1063-6927 | - |