Adaptive Routing Approaches of Controlling Traffic Congestion in Internet

  • Zonghua Liu
  • Ming Tang
  • Pak Ming Hui
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 5)


Different routing strategies may result in different behaviors of traffic in internet. We review the routing strategies developed recently in the field of physics and show that the traffic can be significantly improved by the adaptive routing approaches. Comparing with the shortest path approach, the adaptive routing approaches can reduce the over-loading of hub nodes and thus increase the capacity of network. Especially, for the realistic situation with fluctuated traffic, the local self-adjusting traffic awareness protocol can efficiently reduce the traffic congestion. These results provide new insight in sustaining the normal function of Internet.


traffic in internet routing strategies self-adjusting traffic congestion shortest path 


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  1. 1.
    Huberman, B.A., Lukose, R.M.: Social Dilemmas and Internet Congestion. Science 277, 535 (1997)CrossRefGoogle Scholar
  2. 2.
    Guimerá, R., Díaz-Guilera, A., Vega-Redondo, F., Cabrales, A., Arenas, A.: Optimal Network Topologies for Local Search with Congestion. Phys. Rev. Lett. 89, 248701 (2002)CrossRefGoogle Scholar
  3. 3.
    Arenas, A., Danon, L., Díaz-Guilera, A., Guimerá, R.: Local Search with Congestion in Complex Communication Networks. In: Bubak, M., van Albada, G.D., Sloot, P.M.A., Dongarra, J. (eds.) ICCS 2004. LNCS, vol. 3038, pp. 1078–1085. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  4. 4.
    Arenas, A., Cabrales, A., Díz-Guilera, A., Guimerá, R., Vega-Redondo, F.: Search and congestion in complex networks. In: XVIII Sitges conference on statistical mechanics. Lecture notes in physics, statistical mechanics of complex networks, vol. 625, p. 175 (2003)Google Scholar
  5. 5.
    Moreno, Y., Pastor-Satorras, R., Vazquez, A., Vespignani, A.: Critical load and congestion instabilities in scale-free networks. Europhys. Lett. 62, 292 (2003)CrossRefGoogle Scholar
  6. 6.
    Echenique, P., Gomez-Gardenes, J., Moreno, Y.: Improved routing strategies for Internet traffic delivery. Phys. Rev. E 70, 056105 (2004)CrossRefGoogle Scholar
  7. 7.
    Echenique, P., Gomez-Gardenes, J., Moreno, Y.: Dynamics of jamming transitions in complex networks. Europhys. Lett. 71, 325 (2005)CrossRefGoogle Scholar
  8. 8.
    Chen, Z., Wang, X.: Effects of network structure and routing strategy on network capacity. Phys. Rev. E 73, 036107 (2006)CrossRefGoogle Scholar
  9. 9.
    Wang, W., Wang, B., Yin, C., Xie, Y., Zhou, T.: Traffic dynamics based on local routing protocol on a scale-free network. Phys. Rev. E 73, 026111 (2006)CrossRefGoogle Scholar
  10. 10.
    Yan, G., Zhou, T., Hu, B., Fu, Z., Wang, B.: Efficient routing on complex networks. Phys. Rev. E 73, 046108 (2006)CrossRefGoogle Scholar
  11. 11.
    Mukherjee, S., Gupte, N.: Gradient mechanism in a communication network. Phys. Rev. E 77, 036121 (2008)MathSciNetCrossRefGoogle Scholar
  12. 12.
    Zhao, L., Lai, Y.-C., Park, K., Ye, N.: Onset of traffic congestion in complex networks. Phys. Rev. E 71, 026125 (2005)CrossRefGoogle Scholar
  13. 13.
    Liu, Z., Ma, W., Zhang, H., Sun, Y., Hui, P.M.: An efficient approach of controlling traffic congestion in scale-free networks. Physica A 370, 843 (2006)CrossRefGoogle Scholar
  14. 14.
    Zhang, H., Liu, Z., Tang, M., Hui, P.M.: An adaptive routing strategy for packet delivery in complex networks. Physics Letters A 364, 177 (2007)CrossRefzbMATHGoogle Scholar
  15. 15.
    Zhu, X., Liu, Z., Tang, M.: Detrended fluctuation analysis of traffic data. Chin. Phys. Lett. 24, 2142 (2007)CrossRefGoogle Scholar
  16. 16.
    Tang, M., Liu, Z., Liang, X., Hui, P.M.: A self-adjusting routing approach of controlling congestion in Internet (unpublished)Google Scholar
  17. 17.
    Albert, R., Barabási, A.-L.: Statistical mechanics of complex networks. Rev. Mod. Phys. 74, 47 (2002)MathSciNetCrossRefzbMATHGoogle Scholar
  18. 18.
    Li, H., Manesca, M.: Polymorphic-Torus Network. IEEE Trans. Comput. 38, 1345 (1989)CrossRefGoogle Scholar
  19. 19.
    Leland, E.W., Taqqu, M.S., Willinger, W., Wilson, D.V.: On the self-similar nature of Ethernet traffic. ACM/SIGCOMM Comput. Commun. Rev. 23, 183 (1993)CrossRefGoogle Scholar
  20. 20.
    Taqqu, M.S., Willinger, W., Sherman, R.: Proof of a fundamental result in self-similar traffic modeling. ACM/SIGCOMM Comput. Commun. Rev. 27, 5 (1997)CrossRefGoogle Scholar
  21. 21.
    Crovella, A.E., Bestavros, A.: Self-Similarity in World Wide Web Traffic: Evidence and Possible Causes. IEEE Trans. Networking 5, 835 (1997)CrossRefGoogle Scholar
  22. 22.
    Faloutsos, M., Faloutsos, P., Faloutsos, C.: On power-law relationships of the Internet topology. Comput. Commun. Rev. 29, 251 (1999)CrossRefzbMATHGoogle Scholar
  23. 23.
    Ohira, T., Sawatari, R.: Phase transition in a computer network traffic model. Phys. Rev. E 58, 193 (1998)CrossRefGoogle Scholar
  24. 24.
    Fukś, H., Lawniczak, A.T.: Performance of data networks with random links. Math. Comp. Sim. 51, 101 (1999)MathSciNetCrossRefGoogle Scholar
  25. 25.
    Solá, R.V., Valverde, S.: Information transfer and phase transitions in a model of internet traffic. Physica A 289, 595 (2001)CrossRefzbMATHGoogle Scholar
  26. 26.
    Arenas, A., Díaz-Guilera, A., Guimerá, R.: Communication in Networks with Hierarchical Branching. Phys. Rev. Lett. 86, 3196 (2001)CrossRefzbMATHGoogle Scholar
  27. 27.
    Guimerá, R., Arenas, A., Díaz-Guilera, A.: Communication and optimal hierarchical networks. Physica A 299, 247 (2001)CrossRefzbMATHGoogle Scholar
  28. 28.
    Guimerá, R., Arenas, A., Díaz-Guilera, A., Giralt, F.: Dynamical properties of model communication networks. Phys. Rev. E 66, 026704 (2002)CrossRefGoogle Scholar
  29. 29.
    Woolf, M., Arrowsmith, D.K., Mondragón-C, R.J., Pitts, J.M.: Optimization and phase transitions in a chaotic model of data traffic. Phys. Rev. E 66, 046106 (2002)CrossRefGoogle Scholar
  30. 30.
    Valverde, S., Solé, R.V.: Self-organized critical traffic in parallel computer networks. Physica A 312, 636 (2002)CrossRefzbMATHGoogle Scholar
  31. 31.
    Pastor-Satorras, R., Vázquez, A., Vespignani, A.: Dynamical and Correlation Properties of the Internet. Phys. Rev. Lett. 87, 258701 (2001)CrossRefGoogle Scholar
  32. 32.
    Vázquez, A., Pastor-Satorras, R., Vespignani, A.: Large-scale topological and dynamical properties of the Internet. Phys. Rev. E 65, 066130 (2002)CrossRefGoogle Scholar
  33. 33.
    Barabási, A.-L., Albert, R.: Emergence of Scaling in Random Networks. Science 286, 509 (1999)MathSciNetCrossRefzbMATHGoogle Scholar
  34. 34.
    Barabási, A.-L., Albert, R., Jeong, H.: Mean-field theory for scale-free random networks. Physica A 272, 173 (1999)CrossRefGoogle Scholar
  35. 35.
    Meloni, S., Gomez-Gardenes, J., Latora, V., Moreno, Y.: Scaling Breakdown in Flow Fluctuations on Complex Networks. Phys. Rev. Lett. 100, 208701 (2008)CrossRefGoogle Scholar

Copyright information

© ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering 2009

Authors and Affiliations

  • Zonghua Liu
    • 1
  • Ming Tang
    • 1
  • Pak Ming Hui
    • 2
  1. 1.Institute of theoretical physics and Department of PhysicsEast China Normal UniversityShanghaiP.R. China
  2. 2.Department of PhysicsThe Chinese University of Hong KongHong KongChina

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