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Control-capacity analysis and optimized construction for controlled interdependent networks

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  • Guo, Tianjiao
  • Tu, Lilan
  • Guo, Yifei
  • Hu, Jia
  • Su, Qingqing

Abstract

In order to obtain interdependent networks with stronger control-capacity, in this paper, based on Kalman’s rank theory, a widely used and improved index of control-capacity for controlled interdependent networks is firstly analyzed and proposed theoretically, and two examples are employed to show the feasibility and effectiveness of this presented index. Secondly, with this index, the influence of the intra-couplings, network scale, inter-coupling strength, inter-couplings, and controllers on the control-capacity of sixteen controlled interdependent networks with two subnets, which are any combination of BA scale-free network, WS small-world network, NW small-world network and ER random network, are analyzed and discussed, as well as their optimal structures and various parameters for best control-capacity. Finally, with this index proposed, a novel algorithm is put forward to build up interdependencies or inter-couplings to enhance the control-capacity of controlled interdependent networks. The simulations show that the algorithm designed in this paper is feasible and effective, and can achieve interdependent networks with stronger control-capacity.

Suggested Citation

  • Guo, Tianjiao & Tu, Lilan & Guo, Yifei & Hu, Jia & Su, Qingqing, 2023. "Control-capacity analysis and optimized construction for controlled interdependent networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 616(C).
  • Handle: RePEc:eee:phsmap:v:616:y:2023:i:c:s0378437123001528
    DOI: 10.1016/j.physa.2023.128597
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    References listed on IDEAS

    as
    1. Zheng, Kexian & Liu, Ying & Gong, Jie & Wang, Wei, 2022. "Robustness of circularly interdependent networks," Chaos, Solitons & Fractals, Elsevier, vol. 157(C).
    2. Liu, Jinzhuo & Meng, Haoran & Wang, Wei & Xie, Zhongwen & Yu, Qian, 2019. "Evolution of cooperation on independent networks: The influence of asymmetric information sharing updating mechanism," Applied Mathematics and Computation, Elsevier, vol. 340(C), pages 234-241.
    3. M. E. J. Newman & D. J. Watts, 1999. "Renormalization Group Analysis of the Small-World Network Model," Working Papers 99-04-029, Santa Fe Institute.
    4. Wang, Pei & Xu, Shuang, 2017. "Spectral coarse grained controllability of complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 478(C), pages 168-176.
    5. Yang-Yu Liu & Jean-Jacques Slotine & Albert-László Barabási, 2011. "Controllability of complex networks," Nature, Nature, vol. 473(7346), pages 167-173, May.
    6. Zhengzhong Yuan & Chen Zhao & Zengru Di & Wen-Xu Wang & Ying-Cheng Lai, 2013. "Exact controllability of complex networks," Nature Communications, Nature, vol. 4(1), pages 1-9, December.
    7. Yang, Yong & Tu, Lilan & Li, Kuanyang & Guo, Tianjiao, 2019. "Optimized inter-structure for enhancing the synchronizability of interdependent networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 310-318.
    8. Cai, Ning, 2017. "On quantitatively measuring controllability of complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 474(C), pages 282-292.
    9. Wang, Chengjiang & Wang, Li & Wang, Juan & Sun, Shiwen & Xia, Chengyi, 2017. "Inferring the reputation enhances the cooperation in the public goods game on interdependent lattices," Applied Mathematics and Computation, Elsevier, vol. 293(C), pages 18-29.
    10. Sergey V. Buldyrev & Roni Parshani & Gerald Paul & H. Eugene Stanley & Shlomo Havlin, 2010. "Catastrophic cascade of failures in interdependent networks," Nature, Nature, vol. 464(7291), pages 1025-1028, April.
    11. Pang, Shaopeng & Hao, Fei, 2017. "Optimizing controllability of edge dynamics in complex networks by perturbing network structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 470(C), pages 217-227.
    12. Pang, Shao-Peng & Li, Chao & Fang, Cong & Han, Guo-Zheng, 2019. "Controlling edge dynamics in multilayer networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 528(C).
    13. Lifu Wang & Yali Zhang & Jingxiao Han & Zhi Kong, 2018. "Quantitative Controllability Index of Complex Networks," Advances in Mathematical Physics, Hindawi, vol. 2018, pages 1-9, October.
    14. Wang, Xingyuan & Cao, Jianye & Li, Rui & Zhao, Tianfang, 2017. "A preferential attachment strategy for connectivity link addition strategy in improving the robustness of interdependent networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 412-422.
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    1. Fu, Xiuwen & Li, Qing & Li, Wenfeng, 2023. "Modeling and analysis of industrial IoT reliability to cascade failures: An information-service coupling perspective," Reliability Engineering and System Safety, Elsevier, vol. 239(C).

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