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Sustaining the Internet with hyperbolic mapping

Author

Listed:
  • Marián Boguñá

    (Departament de Física Fonamental, Universitat de Barcelona, Martí i Franquès 1)

  • Fragkiskos Papadopoulos

    (University of Cyprus, Kallipoleos 75)

  • Dmitri Krioukov

    (Cooperative Association for Internet Data Analysis, University of California, San Diego)

Abstract

The Internet infrastructure is severely stressed. Rapidly growing overheads associated with the primary function of the Internet—routing information packets between any two computers in the world—cause concerns among Internet experts that the existing Internet routing architecture may not sustain even another decade. In this paper, we present a method to map the Internet to a hyperbolic space. Guided by a constructed map, which we release with this paper, Internet routing exhibits scaling properties that are theoretically close to the best possible, thus resolving serious scaling limitations that the Internet faces today. Besides this immediate practical viability, our network mapping method can provide a different perspective on the community structure in complex networks.

Suggested Citation

  • Marián Boguñá & Fragkiskos Papadopoulos & Dmitri Krioukov, 2010. "Sustaining the Internet with hyperbolic mapping," Nature Communications, Nature, vol. 1(1), pages 1-8, December.
    • Handle: RePEc:nat:natcom:v:1:y:2010:i:1:d:10.1038_ncomms1063
    DOI: 10.1038/ncomms1063
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    Citations

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    Cited by:

    1. Maksim Kitsak & Ahmed Elmokashfi & Shlomo Havlin & Dmitri Krioukov, 2015. "Long-Range Correlations and Memory in the Dynamics of Internet Interdomain Routing," PLOS ONE, Public Library of Science, vol. 10(11), pages 1-12, November.
    2. Robert Jankowski & Antoine Allard & Marián Boguñá & M. Ángeles Serrano, 2023. "The D-Mercator method for the multidimensional hyperbolic embedding of real networks," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    3. Huang, Wei & Chen, Shengyong & Wang, Wanliang, 2014. "Navigation in spatial networks: A survey," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 393(C), pages 132-154.
    4. Maksim Kitsak & Alexander Ganin & Ahmed Elmokashfi & Hongzhu Cui & Daniel A. Eisenberg & David L. Alderson & Dmitry Korkin & Igor Linkov, 2023. "Finding shortest and nearly shortest path nodes in large substantially incomplete networks by hyperbolic mapping," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    5. Ma, Lili & Jiang, Xin & Wu, Kaiyuan & Zhang, Zhanli & Tang, Shaoting & Zheng, Zhiming, 2012. "Surveying network community structure in the hidden metric space," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(1), pages 371-378.
    6. Meliksah Turker & Haluk O. Bingol, 2023. "Multi-layer network approach in modeling epidemics in an urban town," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 96(2), pages 1-13, February.
    7. Kelly B. Yancey & Matthew P. Yancey, 0. "Bipartite communities via spectral partitioning," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-34.
    8. Wang, Zuxi & Li, Qingguang & Xiong, Wei & Jin, Fengdong & Wu, Yao, 2016. "Fast community detection based on sector edge aggregation metric model in hyperbolic space," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 452(C), pages 178-191.
    9. Charles Murphy & Vincent Thibeault & Antoine Allard & Patrick Desrosiers, 2024. "Duality between predictability and reconstructability in complex systems," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    10. Antoine Allard & M Ángeles Serrano, 2020. "Navigable maps of structural brain networks across species," PLOS Computational Biology, Public Library of Science, vol. 16(2), pages 1-20, February.
    11. Coupier, David & Flammant, Lucas & Tran, Viet Chi, 2024. "Hyperbolic radial spanning tree," Stochastic Processes and their Applications, Elsevier, vol. 172(C).
    12. Ma, Lili, 2019. "Studying node centrality based on the hidden hyperbolic metric space of complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 426-434.
    13. Wang, Zuxi & Wu, Yao & Li, Qingguang & Jin, Fengdong & Xiong, Wei, 2016. "Link prediction based on hyperbolic mapping with community structure for complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 609-623.
    14. Kelly B. Yancey & Matthew P. Yancey, 2022. "Bipartite communities via spectral partitioning," Journal of Combinatorial Optimization, Springer, vol. 44(3), pages 1995-2028, October.
    15. Komjáthy, Júlia & Lodewijks, Bas, 2020. "Explosion in weighted hyperbolic random graphs and geometric inhomogeneous random graphs," Stochastic Processes and their Applications, Elsevier, vol. 130(3), pages 1309-1367.
    16. Wang, Zuxi & Li, Qingguang & Jin, Fengdong & Xiong, Wei & Wu, Yao, 2016. "Hyperbolic mapping of complex networks based on community information," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 455(C), pages 104-119.

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