On the efficiency of data representation on the modeling and characterization of complex networks

Carlos Antônio Ruggiero, Odemir Martinez Bruno, Gonzalo Travieso and Luciano da Fontoura Costa

Physica A: Statistical Mechanics and its Applications, 2011, vol. 390, issue 11, 2172-2180

Abstract: Specific choices about how to represent complex networks can have a substantial impact on the execution time required for the respective construction and analysis of those structures. In this work we report a comparison of the effects of representing complex networks statically by adjacency matrices or dynamically by adjacency lists. Three theoretical models of complex networks are considered: two types of Erdős–Rényi as well as the Barabási–Albert model. We investigated the effect of the different representations with respect to the construction and measurement of several topological properties (i.e. degree, clustering coefficient, shortest path length, and betweenness centrality). We found that different forms of representation generally have a substantial effect on the execution time, with the sparse representation frequently resulting in remarkably superior performance.

Keywords: Complex networks; Representation; Computational efficiency (search for similar items in EconPapers)
Date: 2011
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:390:y:2011:i:11:p:2172-2180

DOI: 10.1016/j.physa.2011.02.011

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