The DOI matches its Crossref record; 30 of the 30 references it cites were found in a registry or an index.
A model of Internet topology using k-shell decomposition
Open accessAbstract
We study a map of the Internet (at the autonomous systems level), by introducing and using the method of k-shell decomposition and the methods of percolation theory and fractal geometry, to find a model for the structure of the Internet. In particular, our analysis uses information on the connectivity of the network shells to separate, in a unique (no parameters) way, the Internet into three subcomponents: (i) a nucleus that is a small (≈100 nodes), very well connected globally distributed subgraph; (ii) a fractal subcomponent that is able to connect the bulk of the Internet without congesting the nucleus, with self-similar properties and critical exponents predicted from percolation theory; and (iii) dendrite-like structures, usually isolated nodes that are connected to the rest of the network through the nucleus only. We show that our method of decomposition is robust and provides insight into the underlying structure of the Internet and its functional consequences. Our approach of decomposing the network is general and also useful when studying other complex networks.
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Cites
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Self-citationBreakdown of the Internet under Intentional Attack
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Critical phenomena in complex networks
Dorogovtsev, S. N., Goltsev, A. V., & Mendes, J. F. F. (2008) · Reviews of Modern Physics · doi:10.1103/revmodphys.80.1275 · Cited by 2,220
The dynamics of protest recruitment through an online network
González-Bailón, S., Borge-Holthoefer, J., Rivero, A., & Moreno, Y. (2011) · Scientific Reports · doi:10.1038/srep00197 · Cited by 571
Ranking spreaders by decomposing complex networks
Zeng, A., & Zhang, C.-J. (2013) · Physics Letters A · doi:10.1016/j.physleta.2013.02.039 · Cited by 448
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Jalili, M., & Perc, M. (2017) · Journal of Complex Networks · doi:10.1093/comnet/cnx019 · Cited by 248
How the brain transitions from conscious to subliminal perception
Arese Lucini, F., Del Ferraro, G., Sigman, M., & Makse, H. A. (2019) · Neuroscience · doi:10.1016/j.neuroscience.2019.03.047 · Cited by 3
Metadata
- Authors
- Carmi, S., Havlin, S., Kirkpatrick, S., Shavitt, Y., & Shir, E.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2007-07-03
- Volume
- 104
- Issue
- 27
- Pages
- 11150-11154
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2162808198
- Cited by
- 760
- References
- 30
- FWCI
- 18.53
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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