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Air traffic management technical support system provides communication, navigation and surveillance service for air traffic management system and air traffic controller. The failures of some facilities may lead to large delay, even affect air transportation safety. In order to improve the ability of air traffic management technical support system to respond to emergencies, a network model of air traffic management technical support system is presented. The network model of air traffic management technical support system is established according to the effective coverage of communication, navigation and surveillance facilities, the position of air traffic management technical support system and air route network. Flexibility, robustness and efficiency are used to measure the network. The measure index of air traffic management technical support system network includes degree, degree distribution, strength, clustering coefficient, network performance, betweenness centrality, average shortest path and diameter. For Beijing, Shanghai, Guangzhou, Kunming, Shenyang and Lanzhou flight information regions, the air traffic management technical support networks are built by using the data of air traffic support facilities, air route, air traffic flow, etc. The average degrees, degree distributions, degree-degree correlations, clustering coefficients, average shortest paths and diameters of these netwoks are comparatively analyzed. The results show that the degrees of most nodes are between two and four. The network has a power law distribution, which is the same as that of air transportation network. The degree-degree correlation of air traffic management technical support system network is not assortative nor disassortative mixing, which has random network characteristics. The clustering coefficients of several air traffic management technical support system networks are between 0.25 and 0.39. The clustering value is lower than that of air transportation network. The shortest paths of air traffic management technical support system networks are between 3.16 and 5.05. The average shortest paths of these networks are all 3.4, which exhibits small world characteristics. Network attack based on degrees of priority and random is conducted to several flight information regions of air traffic management technical support network, showing the network is vulnerable. The network performance decreases quickly after degree priority attack. Some key nodes play an important role in the network. The network survivability can be improved after targeted immunized key nodes. The network performance can be improved by using more satellites based air traffic management technical support system. These rules provide theoretical support for improving and expanding air traffic management technical support system, and have practical significance for reducing the influence of emergency on air traffic management system support ability and ensuring the continuous safety of air traffic.
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Keywords:
- complex network /
- air traffic management /
- technology support /
- network properties
[1] Wang J J, Yu X H, McGrath B, Zhong J X 2015 Proceedings, IECON 2014-40th Annual Conference of the IEEE Industrial Electronics Society Dallas, TX, United states October 30-November 1, 2014 p3543
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[5] Cheung D P, Gunes M H 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining Istanbul, Turkey August 26-29, 2012 p699
[6] Mehta V, Patel F, Glina Y, Schmidt M, Miller B, Bliss N 2012 Conference on Intelligent Data Understanding Boulder, CO, United States October 24-26, 2012 p124
[7] Xu Z W, Harriss R 2008 Geo. Journal 73 87
[8] Bagler G 2008 Physica A 387 2972
[9] Guida M, Maria F 2007 Chaos, Solitons Fractals 31 527
[10] Pien K C, Han K, Shang W L, Majumdar A, Ochieng W 2015 Transportmetrica A: Transport Sci. 11 772
[11] Zhang J, Cao X B, Du W B, Cai K Q 2010 Physica A 389 3922
[12] Cai K Q, Zhang J, Du W B, Cao X B 2012 Chin. Phys. B 21 028903
[13] Wang H Y, Wen R Y 2012 24th Chinese Control and Decision Conference Taiyuan, China, May 23-25, 2012 p2400
[14] Wang H Y, Wen R Y, Zhao Y F 2015 Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 229 2497
[15] Zeng X Z, Tang X X, Jiang K S 2011 Journal of Transportation Systems Engineering and Information Technology 11 175 (in Chinese) [曾小舟, 唐笑笑, 江可申 2011 交通运输系统工程与信息 11 175]
[16] Zeng X Z, Tang X X, Jiang K S 2012 System Simulation Technology 8 111 (in Chinese) [曾小舟, 唐笑笑, 江可申 2012 系统仿真技术 8 111]
[17] Zeng X Z, Jiang K S, Cheng K 2010 Systems Engineering 28 39 (in Chinese) [曾小舟, 江可申, 程凯 2010 系统工程 28 39]
[18] Wang J E, Mo H H, Jin F J 2009 Acta Geographica Sinica 64 899 (in Chinese) [王姣娥, 莫辉辉, 金凤君 2009 地理学报 64 899]
[19] Paleari S, Redondi R, Malighetti P 2009 Transportation Research Part E: Logistics and Transportation Review 46 198
[20] Suo D, Wen F 2009 2nd International Symposium on Information Science and Engineering Shanghai, China December 26-28, 2009 p114
[21] Shang L Y, Tan Q M 2014 Proceedings of the IEEE International Conference on Software Engineering and Service Sciences Beijing, China June 27-29, 2014 p897
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[1] Wang J J, Yu X H, McGrath B, Zhong J X 2015 Proceedings, IECON 2014-40th Annual Conference of the IEEE Industrial Electronics Society Dallas, TX, United states October 30-November 1, 2014 p3543
[2] Shimizu Y, Yamazaki F, Yasuda S, Towhata I, Suzuki T, Isoyama R, Ishida E, Suetomi I, Koganemaru K, Nakayama W 2006 J. Geotech. Geoenviron. Eng. 132 237
[3] Zhou X, Yang F, Zhang F M, Zhou W P, Zou W 2013 Acta Phys. Sin. 62 150201 (in Chinese) [周漩, 杨帆, 张凤鸣, 周卫平, 邹伟 2013 物理学报 62 150201]
[4] Zheng X, Chen J P, Shao J L, Bie L D 2012 Acta Phys. Sin. 61 190510 (in Chinese) [郑啸, 陈建平, 邵佳丽, 别立东 2012 物理学报 61 190510]
[5] Cheung D P, Gunes M H 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining Istanbul, Turkey August 26-29, 2012 p699
[6] Mehta V, Patel F, Glina Y, Schmidt M, Miller B, Bliss N 2012 Conference on Intelligent Data Understanding Boulder, CO, United States October 24-26, 2012 p124
[7] Xu Z W, Harriss R 2008 Geo. Journal 73 87
[8] Bagler G 2008 Physica A 387 2972
[9] Guida M, Maria F 2007 Chaos, Solitons Fractals 31 527
[10] Pien K C, Han K, Shang W L, Majumdar A, Ochieng W 2015 Transportmetrica A: Transport Sci. 11 772
[11] Zhang J, Cao X B, Du W B, Cai K Q 2010 Physica A 389 3922
[12] Cai K Q, Zhang J, Du W B, Cao X B 2012 Chin. Phys. B 21 028903
[13] Wang H Y, Wen R Y 2012 24th Chinese Control and Decision Conference Taiyuan, China, May 23-25, 2012 p2400
[14] Wang H Y, Wen R Y, Zhao Y F 2015 Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 229 2497
[15] Zeng X Z, Tang X X, Jiang K S 2011 Journal of Transportation Systems Engineering and Information Technology 11 175 (in Chinese) [曾小舟, 唐笑笑, 江可申 2011 交通运输系统工程与信息 11 175]
[16] Zeng X Z, Tang X X, Jiang K S 2012 System Simulation Technology 8 111 (in Chinese) [曾小舟, 唐笑笑, 江可申 2012 系统仿真技术 8 111]
[17] Zeng X Z, Jiang K S, Cheng K 2010 Systems Engineering 28 39 (in Chinese) [曾小舟, 江可申, 程凯 2010 系统工程 28 39]
[18] Wang J E, Mo H H, Jin F J 2009 Acta Geographica Sinica 64 899 (in Chinese) [王姣娥, 莫辉辉, 金凤君 2009 地理学报 64 899]
[19] Paleari S, Redondi R, Malighetti P 2009 Transportation Research Part E: Logistics and Transportation Review 46 198
[20] Suo D, Wen F 2009 2nd International Symposium on Information Science and Engineering Shanghai, China December 26-28, 2009 p114
[21] Shang L Y, Tan Q M 2014 Proceedings of the IEEE International Conference on Software Engineering and Service Sciences Beijing, China June 27-29, 2014 p897
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