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A heuristic algorithm for enhancing the robustness of scale-free networks based on edge classification

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  • Rong, Lei
  • Liu, Jing

Abstract

The essential of existing methods for promoting network robustness is randomly exchanging the edges of networks. Without considering the network structure, the performance of these algorithms is limited. Therefore, we put forward a way for classifying the edges of networks into three types, which are valid edges, invalid edges and flexible edges. Then, a heuristic optimization algorithm, which is designed based on the edge classification (EC) against malicious attacks (MA), is proposed to improve the robustness of scale-free (RSF) network termed as EC-RSFMA. EC-RSFMA improves the robustness of scale-free networks by adjusting the number of edges of each type and changing the connection relation of the same type of edges under the constraint that the degree distribution remains to be unchanged. In the experiments, the performance of EC-RSFMA is validated on both synthetic and real-world networks. The results show that EC-RSFMA outperforms the existing algorithms.

Suggested Citation

  • Rong, Lei & Liu, Jing, 2018. "A heuristic algorithm for enhancing the robustness of scale-free networks based on edge classification," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 503-515.
    • Handle: RePEc:eee:phsmap:v:503:y:2018:i:c:p:503-515
    DOI: 10.1016/j.physa.2018.02.173
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    References listed on IDEAS

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    Cited by:

    1. Das, Sai Saranga & Raman, Karthik, 2022. "Effect of dormant spare capacity on the attack tolerance of complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 598(C).

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