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Efficiency of complex networks under failures and attacks: A percolation approach

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  • Zhou, Yaoming
  • Wang, Junwei

Abstract

Network efficiency, defined as the average of the reciprocal of the shortest path lengths between each node pair in a network, indicates how efficiently the network propagates information. The change of efficiency caused by failures or attacks can be used to assess the robustness or resilience of networks. However, due to the uncertainties of failures or attacks, the lengths of the shortest paths and in turn efficiency in a disrupted network cannot be easily calculated. The normal practice in the literature is to estimate the efficiency in different scenarios by simulation. In this paper, we propose an analytical way to assess the efficiency of complex networks under failures and attacks using percolation theory. We find that the efficiency of an affected network is exactly the product of global connectivity and local connectivity, where global connectivity refers to the size of the giant component, and local connectivity represents the average number of neighbors with different distances. This approach not only provides a more efficient and systematic way to analyze efficiency, but also reveals the relation between efficiency and connectivity. We discuss the application of our approach to scale-free networks and random graphs.

Suggested Citation

  • Zhou, Yaoming & Wang, Junwei, 2018. "Efficiency of complex networks under failures and attacks: A percolation approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 658-664.
    • Handle: RePEc:eee:phsmap:v:512:y:2018:i:c:p:658-664
    DOI: 10.1016/j.physa.2018.08.093
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    References listed on IDEAS

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    1. Yaoming Zhou & Jiuh‐Biing Sheu & Junwei Wang, 2017. "Robustness Assessment of Urban Road Network with Consideration of Multiple Hazard Events," Risk Analysis, John Wiley & Sons, vol. 37(8), pages 1477-1494, August.
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    8. Crucitti, Paolo & Latora, Vito & Marchiori, Massimo & Rapisarda, Andrea, 2003. "Efficiency of scale-free networks: error and attack tolerance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 320(C), pages 622-642.
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    Cited by:

    1. Li, Siping & Zhou, Yaoming & Kundu, Tanmoy & Zhang, Fangni, 2021. "Impact of entry restriction policies on international air transport connectivity during COVID-19 pandemic," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    2. Li, Siping & Zhou, Yaoming & Kundu, Tanmoy & Sheu, Jiuh-Biing, 2021. "Spatiotemporal variation of the worldwide air transportation network induced by COVID-19 pandemic in 2020," Transport Policy, Elsevier, vol. 111(C), pages 168-184.
    3. Perez, Yuri & Pereira, Fabio Henrique, 2021. "Simulation of traffic light disruptions in street networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 582(C).

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