Open AccessSpatial embedding and the structure of complex networks
Author(s) -
Bullock S.,
Barnett L.,
Di Paolo E. A.
Publication year - 2010
Publication title -
complexity
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.447
H-Index - 61
eISSN - 1099-0526
pISSN - 1076-2787
DOI - 10.1002/cplx.20338
Subject(s) - embedding , computer science , metric (unit) , space (punctuation) , metric space , topology (electrical circuits) , distribution (mathematics) , spatial network , theoretical computer science , mathematics , artificial intelligence , discrete mathematics , combinatorics , mathematical analysis , operations management , economics , operating system
We review and discuss the structural consequences of embedding a random network within a metric space such that nodes distributed in this space tend to be connected to those nearby. We find that where the spatial distribution of nodes is maximally symmetrical some of the structural properties of the resulting networks are similar to those of random nonspatial networks. However, where the distribution of nodes is inhomogeneous in some way, this ceases to be the case, with consequences for the distribution of neighborhood sizes within the network, the correlation between the number of neighbors of connected nodes, and the way in which the largest connected component of the network grows as the density of edges is increased. We present an overview of these findings in an attempt to convey the ramifications of spatial embedding to those studying real‐world complex systems. © 2010 Wiley Periodicals, Inc. Complexity 16: 20–28, 2010
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