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dc.contributor.authorMiao, W
dc.contributor.authorMin, G
dc.contributor.authorWu, Y
dc.contributor.authorHuang, H
dc.contributor.authorZhao, Z
dc.contributor.authorWang, H
dc.contributor.authorLuo, C
dc.date.accessioned2019-02-12T09:32:40Z
dc.date.issued2019-01-23
dc.description.abstractIEEE Network Function Virtualisation (NFV) has been considered as a promising technology for future Internet to increase network flexibility, accelerate service innovation and reduce the Capital Expenditures (CAPEX) and Operational Expenditures (OPEX) costs, through migrating network functions from dedicated network devices to commodity hardware. Recent studies reveal that although this migration of network function brings the network operation unprecedented flexibility and controllability, NFV-based architecture suffers from serious performance degradation compared with traditional service provisioning on dedicated devices. In order to achieve a comprehensive understanding of the service provisioning capability of NFV, this paper proposes a novel analytical model based on Stochastic Network Calculus (SNC) to quantitatively investigate the end-to-end performance bound of NFV networks. To capture the dynamic and on-demand NFV features, both the non-bursty traffic, e.g. Poisson process, and the bursty traffic, e.g. Markov Modulated Poisson Process (MMPP), are jointly considered in the developed model to characterise the arriving traffic. To address the challenges of resource competition and end-to-end NFV chaining, the property of convolution associativity and leftover service technologies of SNC are exploited to calculate the available resources of Virtual Network Function (VNF) nodes in the presence of multiple competing traffic, and transfer the complex NFV chain into an equivalent system for performance derivation and analysis. Both the numerical analysis and extensive simulation experiments are conducted to validate the accuracy of the proposed analytical model. Results demonstrate that the analytical performance metrics match well with those obtained from the simulation experiments and numerical analysis. In addition, the developed model is used as a practical and cost-effective tool to investigate the strategies of the service chain design and resource allocations in NFV networks.en_GB
dc.description.sponsorshipEngineering and Physical Sciences Research Council (EPSRC)en_GB
dc.identifier.citationPublished online 23 January 2019en_GB
dc.identifier.doi10.1109/JSAC.2019.2894304
dc.identifier.grantnumberEP/R030863/1en_GB
dc.identifier.urihttp://hdl.handle.net/10871/35902
dc.language.isoenen_GB
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_GB
dc.rights© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en_GB
dc.subjectNFVen_GB
dc.subjectPerformance Analysisen_GB
dc.subjectStochastic Network Calculusen_GB
dc.subjectPerformance Boundsen_GB
dc.subjectSLAen_GB
dc.subjectFuture Interneten_GB
dc.titleStochastic performance analysis of Network Function Virtualisation in future interneten_GB
dc.typeArticleen_GB
dc.date.available2019-02-12T09:32:40Z
dc.identifier.issn0733-8716
dc.descriptionThis is the author accepted manuscript. The final version is available from the publisher via the DOI in this recorden_GB
dc.identifier.journalIEEE Journal on Selected Areas in Communicationsen_GB
dc.rights.urihttp://www.rioxx.net/licenses/all-rights-reserveden_GB
dcterms.dateAccepted2019-01-01
exeter.funder::Engineering and Physical Sciences Research Council (EPSRC)en_GB
rioxxterms.versionAMen_GB
rioxxterms.licenseref.startdate2019-01-01
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2019-02-12T09:23:23Z
refterms.versionFCDAM
refterms.dateFOA2019-02-12T09:32:43Z
refterms.panelBen_GB


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