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Degree Distribution of the FKP Network Model
Noam Berger, Bela Bollobas, Christian Borgs, Jennifer Chayes, Oliver Riordan

Citation
Noam Berger, Bela Bollobas, Christian Borgs, Jennifer Chayes, Oliver Riordan. "Degree Distribution of the FKP Network Model". ICALP 2003 International Colloquium on Automata, Languages and Programming, 306-316, 2003.

Abstract
Power laws, in particular power-law degree distributions, have been observed in real-world networks in a very wide range of contexts, including social networks, biological networks, and artificial networks such as the physical internet or abstract world wide web. Recently, these observations have triggered much work attempting to explain the power laws in terms of new 'scale-free' random graph models. So far, perhaps the most effective mechanism for explaining power laws is the combination of growth and preferential attachment. In [A. Fabrikant, E. Koutsoupias, C.H. Papadimitriou, Heuristically optimized trade-offs: A new paradigm for power laws in the internet ICALP 2002, in: LNCS, vol. 2380, pp. 110-122], Fabrikant, Koutsoupias and Papadimitriou propose a new 'paradigm' for explaining power laws, based on trade-offs between competing objectives. They also introduce a new, simple and elegant parametrized model for the internet, and prove some kind of power-law bound on the degree sequence for a wide range of scalings of the trade-off parameter. Here we shall show that this model does not have the usual kind of power-law degree distribution observed in the real world: for the most interesting range of the parameter, neither the bulk of the nodes, nor the few highest degree nodes have degrees following a power law. We shall show that almost all nodes have degree 1, and that there is a strong bunching of degrees near the maximum.

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Citation formats  
  • HTML
    Noam Berger, Bela Bollobas, Christian Borgs, Jennifer
    Chayes, Oliver Riordan. <a
    href="http://chess.eecs.berkeley.edu/pubs/722.html"
    >Degree Distribution of the FKP Network Model</a>,
    ICALP 2003 International Colloquium on Automata, Languages
    and Programming, 306-316, 2003.
  • Plain text
    Noam Berger, Bela Bollobas, Christian Borgs, Jennifer
    Chayes, Oliver Riordan. "Degree Distribution of the FKP
    Network Model". ICALP 2003 International Colloquium on
    Automata, Languages and Programming, 306-316, 2003.
  • BibTeX
    @inproceedings{BergerBollobasBorgsChayesRiordan03_DegreeDistributionOfFKPNetworkModel,
        author = {Noam Berger and Bela Bollobas and Christian Borgs
                  and Jennifer Chayes and Oliver Riordan},
        title = {Degree Distribution of the FKP Network Model},
        booktitle = {ICALP 2003 International Colloquium on Automata,
                  Languages and Programming},
        pages = {306-316},
        year = {2003},
        abstract = {Power laws, in particular power-law degree
                  distributions, have been observed in real-world
                  networks in a very wide range of contexts,
                  including social networks, biological networks,
                  and artificial networks such as the physical
                  internet or abstract world wide web. Recently,
                  these observations have triggered much work
                  attempting to explain the power laws in terms of
                  new 'scale-free' random graph models. So far,
                  perhaps the most effective mechanism for
                  explaining power laws is the combination of growth
                  and preferential attachment. In [A. Fabrikant, E.
                  Koutsoupias, C.H. Papadimitriou, Heuristically
                  optimized trade-offs: A new paradigm for power
                  laws in the internet ICALP 2002, in: LNCS, vol.
                  2380, pp. 110-122], Fabrikant, Koutsoupias and
                  Papadimitriou propose a new 'paradigm' for
                  explaining power laws, based on trade-offs between
                  competing objectives. They also introduce a new,
                  simple and elegant parametrized model for the
                  internet, and prove some kind of power-law bound
                  on the degree sequence for a wide range of
                  scalings of the trade-off parameter. Here we shall
                  show that this model does not have the usual kind
                  of power-law degree distribution observed in the
                  real world: for the most interesting range of the
                  parameter, neither the bulk of the nodes, nor the
                  few highest degree nodes have degrees following a
                  power law. We shall show that almost all nodes
                  have degree 1, and that there is a strong bunching
                  of degrees near the maximum.},
        URL = {http://chess.eecs.berkeley.edu/pubs/722.html}
    }
    

Posted by Christopher Brooks on 4 Nov 2010.
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