Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/112204
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dc.contributor.authorTune, P.-
dc.contributor.authorRoughan, M.-
dc.date.issued2017-
dc.identifier.citationIEEE ACM Transactions on Networking, 2017; 25(3):1582-1592-
dc.identifier.issn1063-6692-
dc.identifier.issn1558-2566-
dc.identifier.urihttp://hdl.handle.net/2440/112204-
dc.descriptionDate of publication January 24, 2017; date of current version June 14, 2017.-
dc.description.abstractThe traffic matrix (TM) is a chief input in many network design and planning applications. In this paper, we propose a model, called the spherically additive noise model (SANM). In conjunction with iterative proportional fitting (IPF), it enables fast generation of synthetic TMs around a predicted TM. We analyze SANM and IPF’s action on the model to show theoretical guarantees on asymptotic convergence, in particular, convergence to the well-known gravity model.-
dc.description.statementofresponsibilityPaul Tune and Matthew Roughan-
dc.language.isoen-
dc.publisherIEEE-
dc.rights© 2017 IEEE-
dc.subjectInternet traffic matrix; iterative proportional fitting; sensitivity analysis; synthetic generation-
dc.titleControlled synthesis of traffic matrices-
dc.typeJournal article-
dc.identifier.doi10.1109/TNET.2016.2639066-
dc.relation.granthttp://purl.org/au-research/grants/arc/DP110103505-
pubs.publication-statusPublished-
dc.identifier.orcidRoughan, M. [0000-0002-7882-7329]-
Appears in Collections:Aurora harvest 8
Mathematical Sciences publications

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