Distance-sum heterogeneity in graphs and complex networks

Ernesto Estrada, EUSEBIO VARGAS ESTRADA

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

The heterogeneity of the sum of all distances from one node to the rest of nodes in a graph (distance-sum or status of the node) is analyzed. We start here by analyzing the cumulative statistical distributions of the distance-sum of nodes in random and real-world networks. From this analysis we conclude that statistical distributions do not reveal the distance-sum heterogeneity in networks. Thus, we motivate an index of distance-sum heterogeneity based on a hypothetical consensus model in which the nodes of the network try to reach an agreement on their distance-sum values. This index is expressed as a quadratic form of the combinatorial Laplacian matrix of the network. The distance-sum heterogeneity index (G) gives a natural interpretation of the Balaban index for any kind of graph/network. We conjecture here that among graphs with a given number of nodes (G) is maximized for a graph with a structure resembling the agave plant. We also found the graphs that maximize (G) for a given number of nodes and links. Using this index and a normalized version of it we studied random graphs as well as 57 real-world networks. Our findings indicate that the distance-sum heterogeneity index reveals important structural characteristics of networks which can be important for understanding the functional and dynamical processes in complex systems.

Original languageEnglish
Pages (from-to)10393-10405
Number of pages13
JournalApplied Mathematics and Computation
Volume218
Issue number21
DOIs
StatePublished - 1 Jul 2012

Keywords

  • Balaban index
  • Complex networks
  • Distance distributions
  • Distance-sum
  • Graph distances

Fingerprint Dive into the research topics of 'Distance-sum heterogeneity in graphs and complex networks'. Together they form a unique fingerprint.

Cite this