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The power of choice in growing trees

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  • R. M. D'Souza
  • P. L. Krapivsky
  • C. Moore

Abstract

The “power of choice” has been shown to radically alter the behavior of a number of randomized algorithms. Here we explore the effects of choice on models of random tree growth. In our models each new node has k randomly chosen contacts, where k > 1 is a constant. It then attaches to whichever one of these contacts is most desirable in some sense, such as its distance from the root or its degree. Even when the new node has just two choices, i.e., when k=2, the resulting tree can be very different from a random graph or tree. For instance, if the new node attaches to the contact which is closest to the root of the tree, the distribution of depths changes from Poisson to a traveling wave solution. If the new node attaches to the contact with the smallest degree, the degree distribution is closer to uniform than in a random graph, so that with high probability there are no nodes in the tree with degree greater than O(log log N). Finally, if the new node attaches to the contact with the largest degree, we find that the degree distribution is a power law with exponent -1 up to degrees roughly equal to k, with an exponential cutoff beyond that; thus, in this case, we need k ≫ 1 to see a power law over a wide range of degrees. Copyright EDP Sciences/Società Italiana di Fisica/Springer-Verlag 2007

Suggested Citation

  • R. M. D'Souza & P. L. Krapivsky & C. Moore, 2007. "The power of choice in growing trees," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 59(4), pages 535-543, October.
  • Handle: RePEc:spr:eurphb:v:59:y:2007:i:4:p:535-543
    DOI: 10.1140/epjb/e2007-00310-5
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    Cited by:

    1. Hosam Mahmoud, 2022. "Profile of Random Exponential Recursive Trees," Methodology and Computing in Applied Probability, Springer, vol. 24(1), pages 259-275, March.
    2. Hosam M. Mahmoud, 2014. "The Degree Profile in Some Classes of Random Graphs that Generalize Recursive Trees," Methodology and Computing in Applied Probability, Springer, vol. 16(3), pages 527-538, September.

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