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Efficient Virtual Network Embedding Via Exploring Periodic Resource Demands

Xu, Zichuan (Edward); Liang, Weifa; Xia, Qiufen

Description

Cloud computing built on virtualization technologies promises provisioning elastic computing and communication resources to enterprise users. To share cloud resources efficiently, embedding virtual networks of different users to a distributed cloud consisting of multiple data centers (a substrate network) poses great challenges. Motivated by the fact that most enterprise virtual networks usually operate on long-term basics and have the characteristics of periodic resource demands, in this paper...[Show more]

dc.contributor.authorXu, Zichuan (Edward)
dc.contributor.authorLiang, Weifa
dc.contributor.authorXia, Qiufen
dc.coverage.spatialEdmonton Canada
dc.date.accessioned2015-12-10T23:23:55Z
dc.date.createdSeptember 8-11 2014
dc.identifier.urihttp://hdl.handle.net/1885/67019
dc.description.abstractCloud computing built on virtualization technologies promises provisioning elastic computing and communication resources to enterprise users. To share cloud resources efficiently, embedding virtual networks of different users to a distributed cloud consisting of multiple data centers (a substrate network) poses great challenges. Motivated by the fact that most enterprise virtual networks usually operate on long-term basics and have the characteristics of periodic resource demands, in this paper we study the virtual network embedding problem by embedding as many virtual networks as possible to a substrate network such that the revenue of the service provider of the substrate network is maximized, while meeting various Service Level Agreements (SLAs) between enterprise users and the cloud service provider. For this problem, we propose an efficient embedding algorithm by exploring periodic resource demands of virtual networks, and employing a novel embedding metric that models the workloads on both substrate nodes and communication links if the periodic resource demands of virtual networks are given; otherwise, we propose a prediction model to predict the periodic resource demands of these virtual networks based on their historic resource demands. We also evaluate the performance of the proposed algorithms by experimental simulation. Experimental results demonstrate that the proposed algorithms outperform existing algorithms, improving the revenue from 10% to 31%.
dc.publisherIEEE Computer Society
dc.relation.ispartofseries39th Annual IEEE Conference on Local Computer Networks, LCN 2014
dc.sourceEfficient Virtual Network Embedding Via Exploring Periodic Resource Demands
dc.titleEfficient Virtual Network Embedding Via Exploring Periodic Resource Demands
dc.typeConference paper
local.description.notesImported from ARIES
local.description.refereedYes
dc.date.issued2014
local.identifier.absfor080503 - Networking and Communications
local.identifier.ariespublicationu4334215xPUB1383
local.type.statusPublished Version
local.contributor.affiliationXu, Zichuan (Edward), College of Engineering and Computer Science, ANU
local.contributor.affiliationLiang, Weifa, College of Engineering and Computer Science, ANU
local.contributor.affiliationXia, Qiufen, College of Engineering and Computer Science, ANU
local.description.embargo2037-12-31
local.bibliographicCitation.startpage90
local.bibliographicCitation.lastpage98
local.identifier.doi10.1109/LCN.2014.6925760
local.identifier.absseo970108 - Expanding Knowledge in the Information and Computing Sciences
dc.date.updated2015-12-10T10:42:34Z
local.identifier.scopusID2-s2.0-84908354354
CollectionsANU Research Publications

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