Betweenness centrality in dense random geometric networks

Alexander P Kartun-Giles, Orestis Georgiou, Carl P Dettmann

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

11 Citations (Scopus)
261 Downloads (Pure)


Random geometric networks are mathematical structures consisting of a set of nodes placed randomly within a bounded set V ⊆ ℝd mutually coupled with a probability dependent on their Euclidean separation, and are the classic model used within the expanding field of ad hoc wireless networks. In order to rank the importance of the network's communicating nodes, we consider the well established `betweenness' centrality measure (quantifying how often a node is on a shortest path of links between any pair of nodes), providing an analytic treatment of betweenness within a random graph model by deriving a closed form expression for the expected betweenness of a node placed within a dense random geometric network formed inside a disk of radius R. We confirm this with numerical simulations, and discuss the importance of the formula for mitigating the `boundary effect' connectivity phenomenon, for cluster head node election protocol design and for detecting the location of a network's 'vulnerability backbone'.
Original languageEnglish
Title of host publicationICC 2015 - 2015 IEEE International Conference on Communications
Subtitle of host publicationProceedings of a meeting held 8-12 June 2015, London, United Kingdom
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages6
ISBN (Electronic)9781467364324
ISBN (Print)9781467364300
Publication statusPublished - Sep 2015
EventIEEE International Conference on Communications, ICC 2015 - London, United Kingdom
Duration: 8 Jun 201512 Jun 2015

Publication series

NameIEEE International Conference on Communications
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
ISSN (Print)1550-3607


ConferenceIEEE International Conference on Communications, ICC 2015
CountryUnited Kingdom

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