Research Article
Understanding the spread of epidemics in highly partitioned mobile networks
@INPROCEEDINGS{10.1145/1315843.1315846, author={Iacopo Carreras and Daniele Miorandi and Geoffrey S. Canright and Kenth Engo-Monsen}, title={Understanding the spread of epidemics in highly partitioned mobile networks}, proceedings={1st International ICST Conference on Bio Inspired Models of Network, Information and Computing Systems}, publisher={ACM}, proceedings_a={BIONETICS}, year={2006}, month={12}, keywords={epidemics spreading wireless mobile networks eigenvector centrality clustering topography}, doi={10.1145/1315843.1315846} }- Iacopo Carreras
Daniele Miorandi
Geoffrey S. Canright
Kenth Engo-Monsen
Year: 2006
Understanding the spread of epidemics in highly partitioned mobile networks
BIONETICS
ACM
DOI: 10.1145/1315843.1315846
Abstract
In this paper we introduce a model for analyzing the spread of epidemics in a disconnected mobile network. The work is based on an extension, to a dynamic setting, of the eigenvector centrality principle introduced by two of the authors for the case of static networks. The extension builds on a new definition of connectivity matrix for a highly partitioned mobile system, where the connectivity between a pair of nodes is defined as the number of contacts taking place over a finite time window. The connectivity matrix is then used to evaluate the eigenvector centrality of the various nodes. Numerical results from real-world traces are presented and discussed.
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