On the Asymptotic Connectivity of Random Networks under the Random Connection Model

dc.contributor.authorMao, Guoqiang
dc.contributor.authorAnderson, Brian
dc.coverage.spatialShanghai China
dc.date.accessioned2015-12-10T23:06:55Z
dc.date.createdApril 10-15 2011
dc.date.issued2011
dc.date.updated2016-02-24T11:02:52Z
dc.description.abstractConsider a network where all nodes are distributed on a unit square following a Poisson distribution with known density ρand a pair of nodes separated by an Euclidean distance x are directly connected with probability g(x/rρ ), where g : [0,∞ρ+b/cp)
dc.identifier.urihttp://hdl.handle.net/1885/62869
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE Inc)
dc.relation.ispartofseriesIEEE International Conference on Computer Communications (INFOCOM 2011)
dc.sourceOn the asymptotic connectivity of random networks under the random connection model
dc.subjectKeywords: Asymptotic distributions; Boundary effects; Boundedness; Connection model; connectivity; Euclidean distance; Isolated nodes; Monotonicity; Random geometric graphs; Random network; Rotational invariances; Unit disk; Unit squares; Poisson distribution connectivity; Isolated nodes; random connection model
dc.titleOn the Asymptotic Connectivity of Random Networks under the Random Connection Model
dc.typeConference paper
local.bibliographicCitation.lastpage639
local.bibliographicCitation.startpage631
local.contributor.affiliationMao, Guoqiang , University of Sydney
local.contributor.affiliationAnderson, Brian, College of Engineering and Computer Science, ANU
local.contributor.authoruidAnderson, Brian, u8104642
local.description.embargo2037-12-31
local.description.notesImported from ARIES
local.description.refereedYes
local.identifier.absfor080503 - Networking and Communications
local.identifier.absseo970109 - Expanding Knowledge in Engineering
local.identifier.ariespublicationu4334215xPUB745
local.identifier.doi10.1109/INFCOM.2011.5935242
local.identifier.scopusID2-s2.0-79960863796
local.type.statusPublished Version

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