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The Resilience Of Complex Network: An Approach For Relevant Nodes Extraction

Author

Listed:
  • ALDO RAMIREZ-ARELLANO

    (Unidad Profesional Interdisciplinaria de Ingeniería y Ciencias Sociales, y Administrativas, Instituto Politécnico Nacional, Ciudad de México 0840, México)

  • JUAN BORY-REYES

    (SEPI-ESIME-Zacatenco, Instituto Politécnico Nacional, Ciudad de México 07738, México)

Abstract

In this paper, a new algorithm to select the relevant nodes — those that maintain the cohesion of the network — of the complex network is presented. The experiments on most of the real complex networks show that the proposed approach outperforms centrality measures as node degree, PageRank algorithm and betweenness centrality. The rationale of the algorithm for extracting relevant nodes is to discover the self-similarity of the network. As seen in the algorithm, throughout the extraction sequence of relevant nodes, differences are advised with node degree, PageRank algorithm and betweenness centrality. Finally, empirical evidence is considered to show that complex network robustness is a nonlinear function of the small-worldness measure.

Suggested Citation

  • Aldo Ramirez-Arellano & Juan Bory-Reyes, 2021. "The Resilience Of Complex Network: An Approach For Relevant Nodes Extraction," FRACTALS (fractals), World Scientific Publishing Co. Pte. Ltd., vol. 29(01), pages 1-14, February.
    • Handle: RePEc:wsi:fracta:v:29:y:2021:i:01:n:s0218348x21500092
    DOI: 10.1142/S0218348X21500092
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