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Robustness of single and interdependent scale-free interaction networks with various parameters

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  • Wang, Shuai
  • Liu, Jing

Abstract

The robustness of scale-free networks has attracted increasing attentions recently. It has been shown that scale-free networks are tolerant to random failures but fragile under malicious attacks. However, most existing studies focus on scale-free networks with fixed exponent (around 3) and assortativity (around 0), and the relationship between robustness and these parameters has not been studied systematically. Therefore, in this paper, we study the change of robustness along with different parameters, including scaling exponent and assortativity, of scale-free networks; moreover, the robustness of interdependent networks is also studied. In the experiments, synthetic single scale-free networks with varying scaling exponents are constructed and adjusted to fix assortativity. Several measures are adopted to estimate the robustness of networks under malicious and random attacks. Then, interdependent networks with varying parameters are constructed and their robustness against malicious attacks is studied. The results show that there is a positive correlation between robustness against node attacks and the scaling exponent as well as assortativity, and the positive correlation also exists in interdependent networks.

Suggested Citation

  • Wang, Shuai & Liu, Jing, 2016. "Robustness of single and interdependent scale-free interaction networks with various parameters," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 460(C), pages 139-151.
  • Handle: RePEc:eee:phsmap:v:460:y:2016:i:c:p:139-151
    DOI: 10.1016/j.physa.2016.04.035
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    References listed on IDEAS

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    1. Vitor H. P. Louzada & Fabio Daolio & Hans J. Herrmann & Marco Tomassini, "undated". "Generating Robust and Efficient Networks Under Targeted Attacks," Working Papers ETH-RC-12-011, ETH Zurich, Chair of Systems Design.
    2. Estrada, Ernesto & Higham, Desmond J. & Hatano, Naomichi, 2009. "Communicability betweenness in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(5), pages 764-774.
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    Cited by:

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    5. Zhou, Hongli & Zhang, Xiaodong & Hu, Yang, 2020. "Robustness of open source product innovation community’s knowledge collaboration network under the dynamic environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).

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