Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
10.1145/3022227.3022273acmconferencesArticle/Chapter ViewAbstractPublication PagesicuimcConference Proceedingsconference-collections
research-article

Topology and survivability analysis for flight flow networks: case studies of three China airline companies

Published: 05 January 2017 Publication History

Abstract

In this paper we study the survivability feature of airline networks. To measure survivability, we comprehensively consider the network structure measures such as degree distribution, average path length, clustering coefficient, and density; the centrality metrics such as degree centrality and betweenness centrality; as well as the connectivity measures such as maximum connected subgraph size and overall efficiency. Taking three listed China airline companies as examples, namely Air China, China Southern Airlines, and China Eastern Airlines, we provide mass number of simulations to test the survivability of the three companies under random attacks and malicious attacks. The results depict the scale-free features of such networks without small-world characteristics, while the attack simulations reflect the survivability of airline networks clearly. To the best of our knowledge, we are the first to provide case studies for airline networks of individual airline companies in China, which has both theoretical and practical significance in related areas.

References

[1]
R. Albert, H. Jeong, and A.-L. Barabasi. Error and attack tolerance of complex networks. Nature, 406:378--382, 2000.
[2]
G. Bagler. Analysis of the airport network of India as a complex weighted network. Physica A: Statistical Mechanics and its Applications, 387:2972--2980, 2008.
[3]
A.-L. Barabasi. Scale-free networks: A decade and beyond. Science, 325:412--413, 2009.
[4]
A.-L. Barabasi. Linked: The new science of networks. Perseus Books Groups, CambridgečňMassachusetts, 2014.
[5]
A.-L. Barabasi. and R. Albert. Emergence of scaling in random networks. Science, 286:509--512, 1999.
[6]
A. Barrat, R. Pastor-Satorras, and A. Vespignani. The architecture of complex weighted networks. Proceedings of the National Academy of Sciences, 101:3747--3752, 2004.
[7]
A. Cento. The Airline Industry. Physica-Verlag, HD, Heidelberg, 2009.
[8]
China Civil Aviation Development Planning Division. 2012--2013 flight plan, Oct. 27 2013.
[9]
L. Freeman. A set of measuring centrality based on betweenness. Sociometry, 40:35--41, 1977.
[10]
L. Freeman. Centrality in social networks: conceptual clarification. Social Networks, 1(3):215--239, 1979.
[11]
M. Guida and F. Maria. Topology of the Italian airport network: a scale-free small-world network with a fractal structure? Chaos, Solitons Fractals, 31:527--536, 2007.
[12]
R. Guimera and L. Amaral. Modeling the world-wide airport network. European Physical Journal B, 38:381--385, 2004.
[13]
R. Guimera, S. Mossa, and L. Turtsehi, A. and Amaral. The worldwide air transportation network: anomalous centrality, community structure, and cities' global roles. Proceedings of the National Academy of Sciences, 102(22):7794--7799, 2005.
[14]
D. Han, J. Qian, and J. Liu. Network topology and correlation features affiliated with european airline companies. Physica A: Statistical Mechanics and its Applications, 388(1):71--81, 2009.
[15]
S. Havlin and R. Cohen. Complex Networks: Structure, Robustness and Function. Cambridge University Press, Cambridge, United Kingdom, 2010.
[16]
W. Li and X. Cai. Statistical analysis of airport network of China. Physical Review E, 69(4):1--6, 2004.
[17]
H. Liu, X. Zhang, and T. Zhou. Structure and external factors of Chinese city airline network. Physics Procedia, 3(5):1781--1789, 2010.
[18]
O. Lordan, J. Sallan, and P. Simo. Study of the topology and robustness of airline route networks from the complex network approach: a survey and research agenda. Journal of Transport Geography, 37:112--120, 2014.
[19]
Z. Neal. The devil is in the details: Differences in air traffic networks by scale, species, and season. Social Networks, 38:63--73, 2014.
[20]
M. E. J. Newman. The structure and function of complex networks. SIAM Review, 45(2):167--256, 2003.
[21]
A. Reggiani, P. Nijkamp, and A. Cento. Connectivity and concentration in airline networks: a complexity analysis of Lufthansas network. European Journal of Information Systems, 19(4):449--461, 2010.
[22]
A. Reggiani, S. Signoretti, P. Nijkamp, and A. Cento. Network measures in civil air transport: a case study of Lufthansa. In A. Naimzada, S. Stefani, and A. Torriero, editors, Networks, Topology and Dynamics: Theory and Applications to Economics and Social Systems, pages 257--282. Springer, Berlin Heidelberg, 2009.
[23]
J. Wang, H. Moa, F. Wang, and F. Jin. Exploring the network structure and nodal centrality of China's air transport network: A complex network approach. Journal of Transport Geography, 19:712--721, 2011.
[24]
D. Watts and S. Strogatz. Collective dynamics of 'small-world' networks. Nature, 393:440--442, 1998.
[25]
Z. Xu and R. Harriss. Exploring the structure of the U.S. intercity passenger airtransportation network: a weighted complex network approach. GeoJournal, 73:87--102, 2008.
[26]
M. Zanin and F. Lillo. Modelling the air transport with complex networks: a short review. European Physical Journal-Special Topics, 215(1):5--21, 2013.

Index Terms

  1. Topology and survivability analysis for flight flow networks: case studies of three China airline companies

        Recommendations

        Comments

        Information & Contributors

        Information

        Published In

        cover image ACM Conferences
        IMCOM '17: Proceedings of the 11th International Conference on Ubiquitous Information Management and Communication
        January 2017
        746 pages
        ISBN:9781450348881
        DOI:10.1145/3022227
        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

        Sponsors

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        Published: 05 January 2017

        Permissions

        Request permissions for this article.

        Check for updates

        Author Tags

        1. air transportation
        2. complex network
        3. survivability

        Qualifiers

        • Research-article

        Funding Sources

        Conference

        IMCOM '17
        Sponsor:

        Acceptance Rates

        IMCOM '17 Paper Acceptance Rate 113 of 366 submissions, 31%;
        Overall Acceptance Rate 213 of 621 submissions, 34%

        Contributors

        Other Metrics

        Bibliometrics & Citations

        Bibliometrics

        Article Metrics

        • 0
          Total Citations
        • 104
          Total Downloads
        • Downloads (Last 12 months)2
        • Downloads (Last 6 weeks)0
        Reflects downloads up to 31 Jan 2025

        Other Metrics

        Citations

        View Options

        Login options

        View options

        PDF

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader

        Figures

        Tables

        Media

        Share

        Share

        Share this Publication link

        Share on social media