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Multi-Hop Generalized Core Percolation On Complex Networks

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  • YILUN SHANG

    (Department of Computer and Information Sciences, Northumbria University, Ellison Place, Newcastle upon Tyne NE1 8ST, UK)

Abstract

Recent theoretical studies on network robustness have focused primarily on attacks by random selection and global vision, but numerous real-life networks suffer from proximity-based breakdown. Here we introduce the multi-hop generalized core percolation on complex networks, where nodes with degree less than k and their neighbors within L-hop distance are removed progressively from the network. The resulting subgraph is referred to as G(k,L)-core, extending the recently proposed Gk-core and classical core of a network. We develop analytical frameworks based upon generating function formalism and rate equation method, showing for instance continuous phase transition for G(2,1)-core and discontinuous phase transition for G(k,L)-core with any other combination of k and L. We test our theoretical results on synthetic homogeneous and heterogeneous networks, as well as on a selection of large-scale real-world networks. This unravels, e.g., a unique crossover phenomenon rooted in heterogeneous networks, which raises a caution that endeavor to promote network-level robustness could backfire when multi-hop tracing is involved.

Suggested Citation

  • Yilun Shang, 2020. "Multi-Hop Generalized Core Percolation On Complex Networks," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 23(01), pages 1-15, March.
    • Handle: RePEc:wsi:acsxxx:v:23:y:2020:i:01:n:s0219525920500010
    DOI: 10.1142/S0219525920500010
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    Cited by:

    1. Julia García Cabello & Pedro A. Castillo & Maria-del-Carmen Aguilar-Luzon & Francisco Chiclana & Enrique Herrera-Viedma, 2021. "A Methodology for Redesigning Networks by Using Markov Random Fields," Mathematics, MDPI, vol. 9(12), pages 1-13, June.

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