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Network Robustness Analytics with Optimization

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Computational Intelligence for Network Structure Analytics

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Abstract

The community structure and the robustness are two important properties of networks for analyzing the functionality of complex systems. The community structure is crucial to understand the potential functionality of complex systems, while the robustness is indispensable to protect the functionality of complex systems from malicious attacks. When a network suffers from an unpredictable attack, its structural integrity would be damaged. It is essential to enhance community integrity of networks against multilevel targeted attacks. Coupled networks are extremely fragile because a node failure of a network would trigger a cascade of failures on the entire system. In reality, it is necessary to recover the damaged networks, and there are cascading failures in recovery processes. This chapter first introduces a greedy algorithm to enhance community integrity of networks against multilevel targeted attacks and then introduces a technique aiming at protecting several influential nodes for enhancing robustness of coupled networks under the recoveries.

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Authors and Affiliations

  1. Xidian University, Xi’an, Shaanxi, China

    Maoguo Gong & Shanfeng Wang

  2. Hong Kong Baptist University, Hong Kong, China

    Qing Cai & Lijia Ma

  3. Northwestern Polytechnical University, Xi’an, Shaanxi, China

    Yu Lei

Authors
  1. Maoguo Gong
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  2. Qing Cai
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  3. Lijia Ma
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  4. Shanfeng Wang
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  5. Yu Lei
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Correspondence to Maoguo Gong .

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Gong, M., Cai, Q., Ma, L., Wang, S., Lei, Y. (2017). Network Robustness Analytics with Optimization. In: Computational Intelligence for Network Structure Analytics. Springer, Singapore. https://doi.org/10.1007/978-981-10-4558-5_5

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  • DOI: https://doi.org/10.1007/978-981-10-4558-5_5

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  • Online ISBN: 978-981-10-4558-5

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