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Error and attack tolerance of evolving networks with local preferential attachment

Author

Listed:
  • Sun, Shiwen
  • Liu, Zhongxin
  • Chen, Zengqiang
  • Yuan, Zhuzhi

Abstract

Networks generated by local-world evolving network model display a transition from exponential network to power-law network with respect to connectivity distribution. We investigate statistical properties of the evolving networks and the responses of these networks under random errors and intentional attacks. It has been found that local world size M has great effect on the network's heterogeneity, thus leading to transitional behaviors in network's robustness against errors and attacks. Numerical results show that networks constructed with local preferential attachment mechanism can maintain the robustness of scale-free networks under random errors and concurrently improve reliance against targeted attacks on highly connected nodes.

Suggested Citation

  • Sun, Shiwen & Liu, Zhongxin & Chen, Zengqiang & Yuan, Zhuzhi, 2007. "Error and attack tolerance of evolving networks with local preferential attachment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 373(C), pages 851-860.
    • Handle: RePEc:eee:phsmap:v:373:y:2007:i:c:p:851-860
    DOI: 10.1016/j.physa.2006.05.049
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    Citations

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    Cited by:

    1. Sun, Shiwen & Li, Ruiqi & Wang, Li & Xia, Chengyi, 2015. "Reduced synchronizability of dynamical scale-free networks with onion-like topologies," Applied Mathematics and Computation, Elsevier, vol. 252(C), pages 249-256.
    2. Ma, A. & Mondragón, R.J., 2012. "Evaluation of network robustness using a node tearing algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(24), pages 6674-6681.
    3. Hao, Yucheng & Jia, Limin & Wang, Yanhui, 2020. "Edge attack strategies in interdependent scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    4. Hu, Menglong & Wang, Juan & Kong, Lingcong & An, Kang & Bi, Tao & Guo, Baohong & Dong, Enzeng, 2015. "Incorporating the information from direct and indirect neighbors into fitness evaluation enhances the cooperation in the social dilemmas," Chaos, Solitons & Fractals, Elsevier, vol. 77(C), pages 47-52.
    5. Jalili, Mahdi, 2011. "Error and attack tolerance of small-worldness in complex networks," Journal of Informetrics, Elsevier, vol. 5(3), pages 422-430.
    6. Wang, Tao & Cheng, Heming & Wang, Xiaoxia, 2020. "A link addition method based on uniformity of node degree in interdependent power grids and communication networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
    7. Deng, ZhengHong & Xu, Jiwei & Song, Qun & Hu, Bin & Wu, Tao & Huang, Panfei, 2020. "Robustness of multi-agent formation based on natural connectivity," Applied Mathematics and Computation, Elsevier, vol. 366(C).
    8. Milena Oehlers & Benjamin Fabian, 2021. "Graph Metrics for Network Robustness—A Survey," Mathematics, MDPI, vol. 9(8), pages 1-48, April.
    9. Xing Zhou & Wei Peng & Zhen Xu & Bo Yang, 2015. "Hardness Analysis and Empirical Studies of the Relations among Robustness, Topology and Flow in Dynamic Networks," PLOS ONE, Public Library of Science, vol. 10(12), pages 1-29, December.

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