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Air Traffic Sector Network: Motif Identification and Resilience Evaluation Based on Subgraphs

Author

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  • Zongbei Shi

    (College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
    National Key Laboratory of Air Traffic Flow Management, Nanjing University of Aeronautics and Astronautics, No. 29 General Avenue, Nanjing 211106, China)

  • Honghai Zhang

    (College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
    National Key Laboratory of Air Traffic Flow Management, Nanjing University of Aeronautics and Astronautics, No. 29 General Avenue, Nanjing 211106, China)

  • Yike Li

    (College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
    National Key Laboratory of Air Traffic Flow Management, Nanjing University of Aeronautics and Astronautics, No. 29 General Avenue, Nanjing 211106, China)

  • Jinlun Zhou

    (College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
    National Key Laboratory of Air Traffic Flow Management, Nanjing University of Aeronautics and Astronautics, No. 29 General Avenue, Nanjing 211106, China)

Abstract

Air traffic control systems play a critical role in ensuring the sustainable and resilient flow of air traffic. The air traffic sector serves as a fundamental topological unit and is responsible for overseeing and maintaining the system’s sustainable operation. Examining the structural characteristics of the air traffic sector network is a useful approach to gaining an intuitive understanding of the system’s sustainability and resilience. In this paper, an air traffic sector network (ATSN) was established in mainland China using the complex network theory, and its motif characteristics were analyzed from a microscopic perspective. Additionally, subgraph resilience was defined in order to describe the network topology by analyzing changes in subgraph motif concentration and subgraph residual concentration. Our empirical findings indicated that motifs exhibit high connectivity, while anti-motifs are found in subgraph structures with low connectivity. The motif concentration of subgraphs can efficiently reflect the distribution of heterogeneous subgraph structures within a network. During the process of resilience evaluation, the subgraph motif concentration remains relatively stable but is sensitive to the transition state of the network from disturbance to recovery. The resilience of the system at the macroscopic scale is aligned with the resilience of each heterogeneous subgraph structure to some extent. Topological indicators have a more significant impact on the resilience of the ATSN than air traffic flow characteristics. This study has the outcome of uncovering the preference for connection among nodes and the rationality of sector structure delineation in ATSNs. Additionally, this research addresses the fundamental mechanism behind the network disturbance recovery process, and identifies the connection between network macro- and microstructure in the resilience process.

Suggested Citation

  • Zongbei Shi & Honghai Zhang & Yike Li & Jinlun Zhou, 2023. "Air Traffic Sector Network: Motif Identification and Resilience Evaluation Based on Subgraphs," Sustainability, MDPI, vol. 15(18), pages 1-19, September.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:18:p:13423-:d:1235168
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    References listed on IDEAS

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