UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Fingerprint for Network Topologies

Guo, YC; Chen, CJ; Zhou, S; (2009) Fingerprint for Network Topologies. In: Zhou, J, (ed.) Complex Sciences First International Conference, Complex 2009, Shanghai, China, February 23-25, 2009, Revised Papers, Part 2. (pp. 1666 - 1677). Springer: Berlin / Heidelberg, Germany. Green open access

[thumbnail of 87501.pdf]
Preview
PDF
87501.pdf
Available under License : See the attached licence file.

Download (513kB)

Abstract

A network’s topology information can be given as an adjacency matrix. The bitmap of sorted adjacency matrix (BOSAM) is a network visualisation tool which can emphasise different network structures by just looking at reordered adjacent matrixes. A BOSAM picture resembles the shape of a flower and is characterised by a series of ‘leaves’. Here we show and mathematically prove that for most networks, there is a self-similar relation between the envelope of the BOSAM leaves. This self-similar property allows us to use a single envelope to predict all other envelopes and therefore reconstruct the outline of a network’s BOSAM picture. We analogise the BOSAM envelope to human’s fingerprint as they share a number of common features, e.g. both are simple, easy to obtain, and strongly characteristic encoding essential information for identification.

Type: Proceedings paper
Title: Fingerprint for Network Topologies
ISBN-13: 9783642024689
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/978-3-642-02469-6_45
Publisher version: http://dx.doi.org/10.1007/978-3-642-02469-6_45
Language: English
Additional information: The original publication is available at www.springerlink.com
Keywords: BOSAM, complex network, visualisation
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/87501
Downloads since deposit
265Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item