A box-covering algorithm for fractal scaling in scale-free networks

J. S. Kim, K. I. Goh, B. Kahng, D. Kim

Research output: Contribution to journalArticlepeer-review

82 Citations (Scopus)


A random sequential box-covering algorithm recently introduced to measure the fractal dimension in scale-free (SF) networks is investigated. The algorithm contains Monte Carlo sequential steps of choosing the position of the center of each box; thereby, vertices in preassigned boxes can divide subsequent boxes into more than one piece, but divided boxes are counted once. We find that such box-split allowance in the algorithm is a crucial ingredient necessary to obtain the fractal scaling for fractal networks; however, it is inessential for regular lattice and conventional fractal objects embedded in the Euclidean space. Next, the algorithm is viewed from the cluster-growing perspective that boxes are allowed to overlap; thereby, vertices can belong to more than one box. The number of distinct boxes a vertex belongs to is, then, distributed in a heterogeneous manner for SF fractal networks, while it is of Poisson-type for the conventional fractal objects.

Original languageEnglish
Article number026116
Issue number2
Publication statusPublished - 2007

Bibliographical note

Funding Information:
This work was supported by KRF Grant No. R14-2002-059-010000-0 of the ABRL program funded by the Korean government (MOEHRD). Notre Dame’s Center for Complex Networks kindly acknowledges the support of the National Science Foundation under Grant No. ITR DMR-0426737.

ASJC Scopus subject areas

  • Statistical and Nonlinear Physics
  • Mathematical Physics
  • General Physics and Astronomy
  • Applied Mathematics


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