On Dissemination Thresholds in Regular and Irregular Graph Classes
We investigate the natural situation of the dissemination of information on various graph classes starting with a random set of informed vertices called active. Initially active vertices are chosen independently with probability p , and at any stage in the process, a vertex becomes active if the maj...
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Veröffentlicht in: | Algorithmica 2011-01, Vol.59 (1), p.16-34 |
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Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | We investigate the natural situation of the dissemination of information on various graph classes starting with a random set of informed vertices called active. Initially active vertices are chosen independently with probability
p
, and at any stage in the process, a vertex becomes active if the majority of its neighbours are active, and thereafter never changes its state. This process is a particular case of bootstrap percolation. We show that in any cubic graph, with high probability, the information will not spread to all vertices in the graph if
. We give families of graphs in which information spreads to all vertices with high probability for relatively small values of
p
. |
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ISSN: | 0178-4617 1432-0541 |
DOI: | 10.1007/s00453-009-9309-0 |