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Fellow Travelers Phenomenon Present in Real-World Networks

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Complex Networks & Their Applications X (COMPLEX NETWORKS 2021)

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Abstract

We investigate a metric parameter “Leanness” of graphs which is a formalization of a well-known Fellow Travelers Property present in some metric spaces. Given a graph \(G=(V,E)\), the leanness of G is the smallest \(\lambda \) such that, for every pair of vertices \(x,y\in V\), all shortest (xy)-paths stay within distance \(\lambda \) from each other. We show that this parameter is bounded for many structured graph classes and is small for many real-world networks. We present efficient algorithms to compute or estimate this parameter and evaluate the performance of our algorithms on a number of real-world networks.

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Notes

  1. 1.

    This is known (see, e.g., [6]) also under the name \(\lambda \)-thin interval, but to differentiate graph thinness parameter based on the thinness of geodesic triangles from the graph thinness based on thinness of intervals, we use here the word lean.

References

  1. Abu-Ata, M., Dragan, F.F.: Metric tree-like structures in real-world networks: an empirical study. Networks 67(1), 49–68 (2016)

    Article  MathSciNet  Google Scholar 

  2. Adcock, A.B., Sullivan, B.D., Mahoney, M.W.: Tree-like structure in large social and information networks. In: 13th ICDM 2013, pp. 1–10. IEEE (2013)

    Google Scholar 

  3. Borassi, M., Coudert, D., Crescenzi, P., Marino, A.: On computing the hyperbolicity of real-world graphs. In: Bansal, N., Finocchi, I. (eds.) ESA 2015. LNCS, vol. 9294, pp. 215–226. Springer, Heidelberg (2015). https://doi.org/10.1007/978-3-662-48350-3_19

    Chapter  Google Scholar 

  4. Bridson, M., Haefliger, A.: Metric Spaces of Non-Positive Curvature. Grundlehren der mathematischen Wissenschaften, vol. 319. Springer, Heidelberg (1999). https://doi.org/10.1007/978-3-662-12494-9

    Book  MATH  Google Scholar 

  5. Center for Applied Internet Data Analysis (CAIDA). CAIDA AS Relationships Dataset (2017). http://www.caida.org/data/active/as-relationships/

  6. Chalopin, J., Chepoi, V., Dragan, F.F., Ducoffe, G., Mohammed, A., Vaxès, Y.: Fast approximation and exact computation of negative curvature parameters of graphs. Discret. Comput. Geom. 65(3), 856–892 (2021)

    Article  MathSciNet  MATH  Google Scholar 

  7. Chalopin, J., Chepoi, V., Papasoglu, P., Pecatte, T.: Cop and robber game and hyperbolicity. SIAM J. Discret. Math. 28(4), 1987–2007 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  8. Chepoi, V., Dragan, F., Estellon, B., Habib, M., Vaxès, Y.: Diameters, centers, and approximating trees of \(\delta \)-hyperbolic geodesic spaces and graphs. In: Proceedings of the 24th Annual Symposium on Computational Geometry, pp. 59–68. ACM (2008)

    Google Scholar 

  9. Chepoi, V., Dragan, F.F., Estellon, B., Habib, M., Vaxès, Y., Xiang, Y.: Additive spanners and distance and routing labeling schemes for hyperbolic graphs. Algorithmica 62(3–4), 713–732 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  10. Chepoi, V., Dragan, F.F., Vaxes, Y.: Core congestion is inherent in hyperbolic networks. In: Proceedings of the Twenty-Eighth Annual ACM-SIAM Symposium on Discrete Algorithms, pp. 2264–2279. SIAM (2017)

    Google Scholar 

  11. Chepoi, V., Estellon, B.: Packing and covering \(\delta \)-hyperbolic spaces by balls. In: Charikar, M., Jansen, K., Reingold, O., Rolim, J.D.P. (eds.) APPROX/RANDOM -2007. LNCS, vol. 4627, pp. 59–73. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-74208-1_5

    Chapter  MATH  Google Scholar 

  12. Cohen, N., Coudert, D., Lancin, A.: On computing the Gromov hyperbolicity. J. Exp. Algorithmics (JEA) 20, 1–6 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  13. Corneil, D.G., Dragan, F.F., Köhler, E.: On the power of BFS to determine a graph’s diameter. Networks 42(4), 209–222 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  14. Coudert, D.: Gromov hyperbolicity of graphs: C source code (2014). http://www-sop.inria.fr/members/David.Coudert/code/hyperbolicity.shtml

  15. Dragan, F.F., Guarnera, H.M.: Obstructions to a small hyperbolicity in Helly graphs. Discret. Math. 342(2), 326–338 (2019)

    Article  MathSciNet  MATH  Google Scholar 

  16. Dragan, F.F., Mohammed, A.: Slimness of graphs. Discret. Math. Theor. Comput. Sci. 21(3) (2019)

    Google Scholar 

  17. Duan, R.: Approximation algorithms for the Gromov hyperbolicity of discrete metric spaces. In: LATIN, pp. 285–293 (2014)

    Google Scholar 

  18. Edwards, K., Kennedy, S., Saniee, I.: Fast approximation algorithms for p-centers in large \(\delta \)-hyperbolic graphs. In: Bonato, A., Graham, F.C., Prałat, P. (eds.) WAW 2016. LNCS, vol. 10088, pp. 60–73. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-49787-7_6

    Chapter  MATH  Google Scholar 

  19. Fournier, H., Ismail, A., Vigneron, A.: Computing the Gromov hyperbolicity of a discrete metric space. eprint arXiv:1210.3323 (2012)

  20. Ghys, E., de la Harpe, P. (eds.): Sur les groupes hyperboliques d’après M. Gromov. Progress in Mathematics, vol. 83 (1990)

    Google Scholar 

  21. Gromov, M.: Hyperbolic groups: essays in group theory. MSRI 8, 75–263 (1987)

    Google Scholar 

  22. Jon Kleinberg. Jon Kleinberg’s web page. http://www.cs.cornell.edu/courses/cs685/2002fa/

  23. Jonckheere, E.A., Lou, M., Bonahon, F., Baryshnikov, Y.: Euclidean versus hyperbolic congestion in idealized versus experimental networks. Internet Math. 7(1), 1–27 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  24. Kennedy, W.S., Saniee, I., Narayan, O.: On the hyperbolicity of large-scale networks and its estimation. In: 2016 IEEE International Conference on Big Data (Big Data), pp. 3344–3351. IEEE (2016)

    Google Scholar 

  25. Krauthgamer, R., Lee, J.R.: Algorithms on negatively curved spaces. In: 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS 2006), pp. 119–132. IEEE (2006)

    Google Scholar 

  26. Kunegis, J.: Konect: the Koblenz network collection. In: WWW 2013 Companion, pp. 1343–1350. Association for Computing Machinery, New York (2013)

    Google Scholar 

  27. Narayan, O., Saniee, I.: Large-scale curvature of networks. Phys. Rev. E 84(6), 066108 (2011)

    Article  Google Scholar 

  28. Shavitt, Y., Shir, E.: DIMES: let the internet measure itself. ACM SIGCOMM Comput. Commun. Rev. 35(5), 71–74 (2005)

    Article  Google Scholar 

  29. Shavitt, Y., Tankel, T.: Hyperbolic embedding of internet graph for distance estimation and overlay construction. IEEE/ACM Trans. Netw. 16(1), 25–36 (2008)

    Article  Google Scholar 

  30. Stanford Large Network Dataset Collection (SNAP). Stanford large network dataset. http://snap.stanford.edu/data/index.html

  31. Vladimir Batagelj. Pajek datasets. http://vlado.fmf.uni-lj.si/pub/networks/data/

  32. Wu, Y., Zhang, C.: Hyperbolicity and chordality of a graph. Electr. J. Comb. 18(1), Paper #P43 (2011)

    Google Scholar 

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Correspondence to Abdulhakeem O. Mohammed .

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Mohammed, A.O., Dragan, F.F., Guarnera, H.M. (2022). Fellow Travelers Phenomenon Present in Real-World Networks. In: Benito, R.M., Cherifi, C., Cherifi, H., Moro, E., Rocha, L.M., Sales-Pardo, M. (eds) Complex Networks & Their Applications X. COMPLEX NETWORKS 2021. Studies in Computational Intelligence, vol 1072. Springer, Cham. https://doi.org/10.1007/978-3-030-93409-5_17

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  • DOI: https://doi.org/10.1007/978-3-030-93409-5_17

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