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Traffic dynamics on two-layer complex networks with limited delivering capacity

Author

Listed:
  • Ma, Jinlong
  • Han, Weizhan
  • Guo, Qing
  • Wang, Zhenyong

Abstract

The traffic dynamics of multi-layer networks has attracted a great deal of interest since many real networks are comprised of two or more layers of subnetworks. Due to its low traffic capacity, the average delivery capacity allocation strategy is susceptible to congestion with the wildly used shortest path routing protocol on two-layer complex networks. In this paper, we introduce a delivery capacity allocation strategy into the traffic dynamics on two-layer complex networks and focus on its effect on the traffic capacity measured by the critical point Rc of phase transition from free flow to congestion. When the total nodes delivering capacity is fixed, the delivering capacity of each node in physical layer is assigned to the degree distributions of both the physical and logical layers. Simulation results show that the proposed strategy can bring much better traffic capacity than that with the average delivery capacity allocation strategy. Because of the significantly improved traffic performance, this work may be useful for optimal design of networked traffic dynamics.

Suggested Citation

  • Ma, Jinlong & Han, Weizhan & Guo, Qing & Wang, Zhenyong, 2016. "Traffic dynamics on two-layer complex networks with limited delivering capacity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 281-287.
    • Handle: RePEc:eee:phsmap:v:456:y:2016:i:c:p:281-287
    DOI: 10.1016/j.physa.2016.03.092
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    Cited by:

    1. Ke Hu & Ju Xiang & Yun-Xia Yu & Liang Tang & Qin Xiang & Jian-Ming Li & Yong-Hong Tang & Yong-Jun Chen & Yan Zhang, 2020. "Significance-based multi-scale method for network community detection and its application in disease-gene prediction," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-24, March.
    2. Ding, Rui & Ujang, Norsidah & Hamid, Hussain bin & Manan, Mohd Shahrudin Abd & Li, Rong & Wu, Jianjun, 2017. "Heuristic urban transportation network design method, a multilayer coevolution approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 71-83.
    3. Wang, Hongjue, 2019. "An universal algorithm for source location in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 620-630.
    4. Zhang, Yue & Huang, Ning & Yin, Shigang & Sun, Lina, 2017. "Phase transition in lattice networks with heavy-tailed user behaviors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 484(C), pages 367-377.
    5. Kumari, Suchi & Saroha, Abhishek & Singh, Anurag, 2020. "Efficient edge rewiring strategies for enhancement in network capacity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    6. Gao, Xingle & Peng, Minfang & Tse, Chi K., 2022. "Robustness analysis of cyber-coupled power systems with considerations of interdependence of structures, operations and dynamic behaviors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    7. Li, Qiaoru & Zhang, Zhe & Li, Kun & Chen, Liang & Wei, Zhenlin & Zhang, Jingchun, 2020. "Evolutionary dynamics of traveling behavior in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    8. Ding, Rui & Ujang, Norsidah & Hamid, Hussain bin & Manan, Mohd Shahrudin Abd & He, Yuou & Li, Rong & Wu, Jianjun, 2018. "Detecting the urban traffic network structure dynamics through the growth and analysis of multi-layer networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 800-817.
    9. Tu, Haicheng & Xia, Yongxiang & Wu, Jiajing & Zhou, Xiang, 2019. "Robustness assessment of cyber–physical systems with weak interdependency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 522(C), pages 9-17.

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