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Conference Paper: An online auction framework for dynamic resource provisioning in cloud computing

TitleAn online auction framework for dynamic resource provisioning in cloud computing
Authors
Issue Date2014
PublisherACM.
Citation
Proceedings of the 2014 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems, Austin, Texas, USA, 16-20 June 2014, p. 71-83 How to Cite?
AbstractAuction mechanisms have recently attracted substantial attention as an efficient approach to pricing and resource allocation in cloud computing. This work, to the authors' knowledge, represents the first online combinatorial auction designed in the cloud computing paradigm, which is general and expressive enough to both (a) optimize system efficiency across the temporal domain instead of at an isolated time point, and (b) model dynamic provisioning of heterogeneous Virtual Machine (VM) types in practice. The final result is an online auction framework that is truthful, computationally efficient, and guarantees a competitive ratio e+ 1 over e-1 3.30 in social welfare in typical scenarios. The framework consists of three main steps: (1) a tailored primal-dual algorithm that decomposes the long-term optimization into a series of independent one-shot optimization problems, with an additive loss of 1 over e-1 in competitive ratio, (2) a randomized auction sub-framework that applies primal-dual optimization for translating a centralized co-operative social welfare approximation algorithm into an auction mechanism, retaining a similar approximation ratio while adding truthfulness, and (3) a primal-dual update plus dual fitting algorithm for approximating the one-shot optimization with a ratio λ close to e. The efficacy of the online auction framework is validated through theoretical analysis and trace-driven simulation studies. We are also in the hope that the framework, as well as its three independent modules, can be instructive in auction design for other related problems.
Persistent Identifierhttp://hdl.handle.net/10722/201097
ISBN

 

DC FieldValueLanguage
dc.contributor.authorShi, Wen_US
dc.contributor.authorZhang, Len_US
dc.contributor.authorWu, Cen_US
dc.contributor.authorLi, Zen_US
dc.contributor.authorLau, FCMen_US
dc.date.accessioned2014-08-21T07:13:33Z-
dc.date.available2014-08-21T07:13:33Z-
dc.date.issued2014en_US
dc.identifier.citationProceedings of the 2014 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems, Austin, Texas, USA, 16-20 June 2014, p. 71-83en_US
dc.identifier.isbn9781450327893-
dc.identifier.urihttp://hdl.handle.net/10722/201097-
dc.description.abstractAuction mechanisms have recently attracted substantial attention as an efficient approach to pricing and resource allocation in cloud computing. This work, to the authors' knowledge, represents the first online combinatorial auction designed in the cloud computing paradigm, which is general and expressive enough to both (a) optimize system efficiency across the temporal domain instead of at an isolated time point, and (b) model dynamic provisioning of heterogeneous Virtual Machine (VM) types in practice. The final result is an online auction framework that is truthful, computationally efficient, and guarantees a competitive ratio e+ 1 over e-1 3.30 in social welfare in typical scenarios. The framework consists of three main steps: (1) a tailored primal-dual algorithm that decomposes the long-term optimization into a series of independent one-shot optimization problems, with an additive loss of 1 over e-1 in competitive ratio, (2) a randomized auction sub-framework that applies primal-dual optimization for translating a centralized co-operative social welfare approximation algorithm into an auction mechanism, retaining a similar approximation ratio while adding truthfulness, and (3) a primal-dual update plus dual fitting algorithm for approximating the one-shot optimization with a ratio λ close to e. The efficacy of the online auction framework is validated through theoretical analysis and trace-driven simulation studies. We are also in the hope that the framework, as well as its three independent modules, can be instructive in auction design for other related problems.-
dc.languageengen_US
dc.publisherACM.-
dc.relation.ispartofProceedings of the 2014 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systemsen_US
dc.titleAn online auction framework for dynamic resource provisioning in cloud computingen_US
dc.typeConference_Paperen_US
dc.identifier.emailWu, C: cwu@cs.hku.hken_US
dc.identifier.emailLau, FCM: fcmlau@cs.hku.hken_US
dc.identifier.authorityWu, C=rp01397en_US
dc.identifier.authorityLau, FCM=rp00221en_US
dc.identifier.doi10.1145/2591971.2591980-
dc.identifier.scopuseid_2-s2.0-84904343815-
dc.identifier.hkuros232126en_US
dc.identifier.spage71-
dc.identifier.epage83-
dc.publisher.placeNew York-

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