IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v105y2017icp169-175.html
   My bibliography  Save this article

Vital layer nodes of multiplex networks for immunization and attack

Author

Listed:
  • Zhao, Dawei
  • Wang, Lianhai
  • Xu, Shujiang
  • Liu, Guangqi
  • Han, Xiaohui
  • Li, Shudong

Abstract

When dealing with the optimal prevention of epidemics or destruction of network structures, one important question that can be asked is the location of vital nodes which need to be immunized or removed first. In the last decade, the vital nodes identification has attracted increasing attentions. However, the majority of the existing achievements are limited to single networks, how to identify the vital nodes of multiplex networks need further exploration. The nodes of multiplex networks can be divided into two categories: multiplex node (MN) and layer node (LN). In this paper, we focus on identifying the vital LNs of multiplex networks for immunization or attack. We extend several indexes or algorithms from single networks to multiplex networks, including high degree, high betweeness and their variations based on adaptive strategies, and the collective influence, explosive immunization and simulated annealing, to identify the vital LNs. By performing them on different kinds of multiplex networks, we find the explosive immunization is always the best for the identification of vital LNs. Particularly, the performances of the proposed indexes and algorithms could be improved considerably when the greedy reinserting strategy is considered except the explosive immunization, which however still performs the best. Our work offers a deeper understanding for the vital nodes identification in multiplex network and provides novel insights for further studies of the immunization and attack on multiplex networks.

Suggested Citation

  • Zhao, Dawei & Wang, Lianhai & Xu, Shujiang & Liu, Guangqi & Han, Xiaohui & Li, Shudong, 2017. "Vital layer nodes of multiplex networks for immunization and attack," Chaos, Solitons & Fractals, Elsevier, vol. 105(C), pages 169-175.
  • Handle: RePEc:eee:chsofr:v:105:y:2017:i:c:p:169-175
    DOI: 10.1016/j.chaos.2017.10.021
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S096007791730437X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.chaos.2017.10.021?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Zhao, Dawei & Wang, Lianhai & Xu, Lijuan & Wang, Zhen, 2015. "Finding another yourself in multiplex networks," Applied Mathematics and Computation, Elsevier, vol. 266(C), pages 599-604.
    2. Dawei Zhao & Lianhai Wang & Shudong Li & Zhen Wang & Lin Wang & Bo Gao, 2014. "Immunization of Epidemics in Multiplex Networks," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-5, November.
    3. Li, Xianghua & Wang, Zhen & Gao, Chao & Shi, Lei, 2017. "Reasoning human emotional responses from large-scale social and public media," Applied Mathematics and Computation, Elsevier, vol. 310(C), pages 182-193.
    4. Chao Gao & Zhen Wang & Xianghua Li & Zili Zhang & Wei Zeng, 2016. "PR-Index: Using the h-Index and PageRank for Determining True Impact," PLOS ONE, Public Library of Science, vol. 11(9), pages 1-13, September.
    5. Gao, Bo & Deng, Zhenghong & Zhao, Dawei, 2016. "Competing spreading processes and immunization in multiplex networks," Chaos, Solitons & Fractals, Elsevier, vol. 93(C), pages 175-181.
    6. Saeed Osat & Ali Faqeeh & Filippo Radicchi, 2017. "Optimal percolation on multiplex networks," Nature Communications, Nature, vol. 8(1), pages 1-7, December.
    7. Flaviano Morone & HernĂ¡n A. Makse, 2015. "Influence maximization in complex networks through optimal percolation," Nature, Nature, vol. 524(7563), pages 65-68, August.
    8. C.M. Schneider & T. Mihaljev & H.J. Herrmann, "undated". "Inverse targeting - an effective immunization strategy," Working Papers ETH-RC-12-009, ETH Zurich, Chair of Systems Design.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Quan Ye & Guanghui Yan & Wenwen Chang & Hao Luo, 2023. "Vital node identification based on cycle structure in a multiplex network," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 96(2), pages 1-16, February.
    2. Zhao, Jianyu & Yu, Lean & Xi, Xi & Li, Shengliang, 2023. "Knowledge percolation threshold and optimization strategies of the combinatorial network for complex innovation in the digital economy," Omega, Elsevier, vol. 120(C).
    3. Zan, Yongli, 2018. "DSIR double-rumors spreading model in complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 110(C), pages 191-202.
    4. Li, Shudong & Jiang, Laiyuan & Wu, Xiaobo & Han, Weihong & Zhao, Dawei & Wang, Zhen, 2021. "A weighted network community detection algorithm based on deep learning," Applied Mathematics and Computation, Elsevier, vol. 401(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zheng, Mingwen & Wang, Zeming & Li, Lixiang & Peng, Haipeng & Xiao, Jinghua & Yang, Yixian & Zhang, Yanping & Feng, Cuicui, 2018. "Finite-time generalized projective lag synchronization criteria for neutral-type neural networks with delay," Chaos, Solitons & Fractals, Elsevier, vol. 107(C), pages 195-203.
    2. Li, Xianghua & Guo, Jingyi & Gao, Chao & Zhang, Leyan & Zhang, Zili, 2018. "A hybrid strategy for network immunization," Chaos, Solitons & Fractals, Elsevier, vol. 106(C), pages 214-219.
    3. Su, Zhen & Liu, Fanzhen & Gao, Chao & Gao, Shupeng & Li, Xianghua, 2018. "Inferring infection rate based on observations in complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 107(C), pages 170-176.
    4. Baba, Isa Abdullahi & Kaymakamzade, Bilgen & Hincal, Evren, 2018. "Two-strain epidemic model with two vaccinations," Chaos, Solitons & Fractals, Elsevier, vol. 106(C), pages 342-348.
    5. Li, Hui-Jia & Bu, Zhan & Li, Yulong & Zhang, Zhongyuan & Chu, Yanchang & Li, Guijun & Cao, Jie, 2018. "Evolving the attribute flow for dynamical clustering in signed networks," Chaos, Solitons & Fractals, Elsevier, vol. 110(C), pages 20-27.
    6. Parsamanesh, Mahmood & Erfanian, Majid, 2018. "Global dynamics of an epidemic model with standard incidence rate and vaccination strategy," Chaos, Solitons & Fractals, Elsevier, vol. 117(C), pages 192-199.
    7. Shen, Dongqin & Cao, Shanshan, 2018. "An efficient immunization strategy based on transmission limit in weighted complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 114(C), pages 1-7.
    8. Li, Xianghua & Guo, Jingyi & Gao, Chao & Su, Zhen & Bao, Deng & Zhang, Zili, 2018. "Network-based transportation system analysis: A case study in a mountain city," Chaos, Solitons & Fractals, Elsevier, vol. 107(C), pages 256-265.
    9. Li, Shudong & Zhao, Dawei & Wu, Xiaobo & Tian, Zhihong & Li, Aiping & Wang, Zhen, 2020. "Functional immunization of networks based on message passing," Applied Mathematics and Computation, Elsevier, vol. 366(C).
    10. Wu, Qingchu & Fu, Xinchu, 2016. "Immunization and epidemic threshold of an SIS model in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 576-581.
    11. Zan, Yongli, 2018. "DSIR double-rumors spreading model in complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 110(C), pages 191-202.
    12. Fan, Dongming & Sun, Bo & Dui, Hongyan & Zhong, Jilong & Wang, Ziyao & Ren, Yi & Wang, Zili, 2022. "A modified connectivity link addition strategy to improve the resilience of multiplex networks against attacks," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    13. Xia, Ling-Ling & Song, Yu-Rong & Li, Chan-Chan & Jiang, Guo-Ping, 2018. "Improved targeted immunization strategies based on two rounds of selection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 540-547.
    14. Gao, Bo & Liu, Xuan & Lan, Zhongzhou & Fu, Rongrong, 2018. "A novel method for reconstructing period with single input in NFSR," Chaos, Solitons & Fractals, Elsevier, vol. 109(C), pages 36-40.
    15. Zhang, Jun & Hu, Bin & Huang, Yi Jie & Deng, Zheng Hong & Wu, Tao, 2020. "The evolution of cooperation affected by aspiration-driven updating rule in multi-games with voluntary participation," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    16. Chen, Dandan & Zheng, Muhua & Zhao, Ming & Zhang, Yu, 2018. "A dynamic vaccination strategy to suppress the recurrent epidemic outbreaks," Chaos, Solitons & Fractals, Elsevier, vol. 113(C), pages 108-114.
    17. Zhu, Hongmiao & Jin, Zhen & Yan, Xin, 2023. "A dynamics model of coupling transmission for multiple different knowledge in multiplex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 629(C).
    18. Zhang, Yaming & Su, Yanyuan & Weigang, Li & Liu, Haiou, 2019. "Interacting model of rumor propagation and behavior spreading in multiplex networks," Chaos, Solitons & Fractals, Elsevier, vol. 121(C), pages 168-177.
    19. Fink, Christian G. & Fullin, Kelly & Gutierrez, Guillermo & Omodt, Nathan & Zinnecker, Sydney & Sprint, Gina & McCulloch, Sean, 2023. "A centrality measure for quantifying spread on weighted, directed networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 626(C).
    20. Zhu, Yu-Xiao & Cao, Yan-Yan & Chen, Ting & Qiu, Xiao-Yan & Wang, Wei & Hou, Rui, 2018. "Crossover phenomena in growth pattern of social contagions with restricted contact," Chaos, Solitons & Fractals, Elsevier, vol. 114(C), pages 408-414.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:chsofr:v:105:y:2017:i:c:p:169-175. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.