We model airport congestion contagion as an SIS spreading process on an airport transportation network to explain airport vulnerability. The vulnerability of each airport is derived from the US Airport Network data as its congestion probability. We construct three types of airline networks to capture diverse features such as the frequency and duration of flights. The weight of each link augments its infection rate in SIS spreading process. The nodal infection probability in the meta-stable state is used as estimate the vulnerability of the corresponding airport. We illustrate that our model could reasonably capture the distribution of nodal vulnerability and rank airports in vulnerability evidently better than the random ranking, but not significantly better than using nodal network properties. Such congestion contagion model not only allows the identification of vulnerable airports but also opens the possibility to reduce global congestion via congestion reduction in few airports.

Original languageEnglish
Title of host publicationComplex Networks and Their Applications VIII
Subtitle of host publicationProceedings of the 8th International Conference on Complex Networks and Their Applications, COMPLEX NETWORKS 2019
EditorsHocine Cherifi, Sabrina Gaito, José Fernendo Mendes, Esteban Moro, Luis Mateus Rocha
Place of PublicationCham
PublisherSpringer
Pages385-398
Number of pages14
Volume1
ISBN (Electronic)978-3-030-36687-2
ISBN (Print)978-3-030-36686-5
DOIs
Publication statusPublished - 2020
Event COMPLEX NETWORKS 2019: 8th International Conference on Complex Networks and their Applications - Lisbon, Portugal
Duration: 10 Dec 201912 Dec 2019
Conference number: 8th

Publication series

NameStudies in Computational Intelligence
Volume881
ISSN (Print)1860-949X
ISSN (Electronic)1860-9503

Conference

Conference COMPLEX NETWORKS 2019
CountryPortugal
CityLisbon
Period10/12/1912/12/19

    Research areas

  • Airline transportation network, Epidemic spreading, Network vulnerability

ID: 68295668