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Conference Paper: Profit-maximizing virtual machine trading in a federation of selfish clouds
Title | Profit-maximizing virtual machine trading in a federation of selfish clouds |
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Authors | |
Keywords | Auction mechanisms Dynamic algorithm Dynamic resource trading Electricity prices Long-term profits Rigorous analysis Temporal availability Virtual machines |
Issue Date | 2013 |
Publisher | IEEE Computer Society. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000359 |
Citation | The 32nd IEEE Conference on Computer Communications (IEEE INFOCOM 2013), Turin, Italy, 14-19 April 2013. In IEEE Infocom Proceedings, 2013, p. 25-29 How to Cite? |
Abstract | The emerging federated cloud paradigm advocates sharing of resources among cloud providers, to exploit temporal availability of resources and diversity of operational costs for job serving. While extensive studies exist on enabling interoperability across different cloud platforms, a fundamental question on cloud economics remains unanswered: When and how should a cloud trade VMs with others, such that its net profit is maximized over the long run? In order to answer this question by the federation, a number of important, correlated decisions, including job scheduling, server provisioning and resource pricing, need to be dynamically made, with long-term profit optimality being a goal. In this work, we design efficient algorithms for inter-cloud resource trading and scheduling in a federation of geo-distributed clouds. For VM trading among clouds, we apply a double auction-based mechanism that is strategyproof, individual rational, and ex-post budget balanced. Coupling with the auction mechanism is an efficient, dynamic resource trading and scheduling algorithm, which carefully decides the true valuations of VMs in the auction, optimally schedules stochastic job arrivals with different SLAs onto the VMs, and judiciously turns on and off servers based on the current electricity prices. Through rigorous analysis, we show that each individual cloud, by carrying out our dynamic algorithm, can achieve a time-averaged profit arbitrarily close to the offline optimum. © 2013 IEEE. |
Description | Mini-Conference - IEEE INFOCOM 2013 |
Persistent Identifier | http://hdl.handle.net/10722/186479 |
ISBN | |
ISSN | 2023 SCImago Journal Rankings: 2.865 |
DC Field | Value | Language |
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dc.contributor.author | Li, H | en_US |
dc.contributor.author | Wu, C | en_US |
dc.contributor.author | Li, Z | en_US |
dc.contributor.author | Lau, FCM | en_US |
dc.date.accessioned | 2013-08-20T12:11:09Z | - |
dc.date.available | 2013-08-20T12:11:09Z | - |
dc.date.issued | 2013 | en_US |
dc.identifier.citation | The 32nd IEEE Conference on Computer Communications (IEEE INFOCOM 2013), Turin, Italy, 14-19 April 2013. In IEEE Infocom Proceedings, 2013, p. 25-29 | en_US |
dc.identifier.isbn | 978-1-4673-5946-7 | - |
dc.identifier.issn | 0743-166X | - |
dc.identifier.uri | http://hdl.handle.net/10722/186479 | - |
dc.description | Mini-Conference - IEEE INFOCOM 2013 | - |
dc.description.abstract | The emerging federated cloud paradigm advocates sharing of resources among cloud providers, to exploit temporal availability of resources and diversity of operational costs for job serving. While extensive studies exist on enabling interoperability across different cloud platforms, a fundamental question on cloud economics remains unanswered: When and how should a cloud trade VMs with others, such that its net profit is maximized over the long run? In order to answer this question by the federation, a number of important, correlated decisions, including job scheduling, server provisioning and resource pricing, need to be dynamically made, with long-term profit optimality being a goal. In this work, we design efficient algorithms for inter-cloud resource trading and scheduling in a federation of geo-distributed clouds. For VM trading among clouds, we apply a double auction-based mechanism that is strategyproof, individual rational, and ex-post budget balanced. Coupling with the auction mechanism is an efficient, dynamic resource trading and scheduling algorithm, which carefully decides the true valuations of VMs in the auction, optimally schedules stochastic job arrivals with different SLAs onto the VMs, and judiciously turns on and off servers based on the current electricity prices. Through rigorous analysis, we show that each individual cloud, by carrying out our dynamic algorithm, can achieve a time-averaged profit arbitrarily close to the offline optimum. © 2013 IEEE. | - |
dc.language | eng | en_US |
dc.publisher | IEEE Computer Society. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000359 | - |
dc.relation.ispartof | IEEE Infocom Proceedings | en_US |
dc.subject | Auction mechanisms | - |
dc.subject | Dynamic algorithm | - |
dc.subject | Dynamic resource trading | - |
dc.subject | Electricity prices | - |
dc.subject | Long-term profits | - |
dc.subject | Rigorous analysis | - |
dc.subject | Temporal availability | - |
dc.subject | Virtual machines | - |
dc.title | Profit-maximizing virtual machine trading in a federation of selfish clouds | en_US |
dc.type | Conference_Paper | en_US |
dc.identifier.email | Wu, C: cwu@cs.hku.hk | en_US |
dc.identifier.email | Lau, FCM: fcmlau@cs.hku.hk | en_US |
dc.identifier.authority | Wu, C=rp01397 | en_US |
dc.identifier.authority | Lau, FCM=rp00221 | en_US |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/INFCOM.2013.6566728 | - |
dc.identifier.scopus | eid_2-s2.0-84883112358 | - |
dc.identifier.hkuros | 217643 | en_US |
dc.identifier.spage | 25 | - |
dc.identifier.epage | 29 | - |
dc.publisher.place | United States | - |
dc.customcontrol.immutable | sml 140822 | - |
dc.identifier.issnl | 0743-166X | - |