Network Planning and Adaptive Routing for Multimedia Traffic

  • Priscila Solís Barreto
  • Paulo H. P. de Carvalho
  • Rafael Dias Oliveira
  • Maximiliano Prestes Ceppo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5297)


This work presents a methodology for network traffic engineering based on a hybrid traffic model and an adaptive routing algorithm. The hybrid traffic model pursuits the calculation of more accurate Qos metrics and effective bandwidth for multimedia traffic in order to optimize the sizing of network elements at a minimal cost. During network operation, the links weighted values are modified to compute shortest path routing algorithms in an adaptive manner to comply with the traffic effective bandwidth and QoS requirements. The network routing methodology was evaluated in a network topology that aggregates different traffic types, Poisson and self-similar. The results show that the proposed methodology achieves the QoS requirements and promotes a more efficient traffic balancing within the network.


Traffic characterization adaptive routing QoS metrics optimization 


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  1. 1.
    Rosen, E., Viswanathan, A., Callon, R.: Request for Comments: 3031. Janeiro (2001)Google Scholar
  2. 2.
    Evans, J., Filsfils, C.: Deploying IP and MPLS QoS for multiservice networks. Morgan Kaufmann, San Francisco (2007)Google Scholar
  3. 3.
    Leland, W.E., Taquu, M.S., Willenger, W., Wilson, D.V.: On the self- similar nature of ethernet traffic (extended version). IEEE/ACM Trans. on Networking 2(1), 1–15 (1994)CrossRefGoogle Scholar
  4. 4.
    Park, K., Willinger, W.: Self-Similar Network Traffic and Performance Evaluation. John Wiley and sons, Chichester (2000)CrossRefGoogle Scholar
  5. 5.
    Sahinoglu, Z., Tekinay, S.: On multimedia networks: self-similar traffic and network performance. IEEE Communications 37(1), 48–52 (1999)CrossRefGoogle Scholar
  6. 6.
    Yusheng, JI.: Multi-Scale Internet Traffic Analysis Using Piecewise Self-Similar Processes. IEICE Transactions in Communications E89-B, 2125–2133 (2006)Google Scholar
  7. 7.
    Crovella, M.E., Bestavros, A.: Self-Similarity in World Wide Web Traffic: Evidence and Possible Causes. IEEE/ACM Transactions on Networking 5, 835–846 (1997)CrossRefGoogle Scholar
  8. 8.
    Rodrigues, L., e Guardieiro, P.R.: A Spatial and Temporal Analysis of Internet Aggregate Traffic at the Flow Level. In: Global Telecommunications Conference, vol. 2, pp. 685–691 (2004)Google Scholar
  9. 9.
    Carvalho, P., Solis, P., et al.: A Traffic Analysis per Application in real IP/MPLS Service Provider Network. In: 2nd IEEE/IFIP International Workshop on Broadband Convergence Networks (BCN 2007), pp. 1–5 (2007)Google Scholar
  10. 10.
    Park, K., Willinger, W.: Self-Similar Network Traffic and Performance Evaluation (2000); ISBN: 9780471206446Google Scholar
  11. 11.
    Sheluhin, O., Smolskiy, S., Andrew, O.: Self-Similar Processes in Telecommunications. Wiley Publishers, Chichester (2007)CrossRefGoogle Scholar
  12. 12.
    Norros, I.: On the use of fractional Brownian motion in the theory of connectionless networks. Journal on Selected Areas in Communications 13, 953–962 (1994)CrossRefGoogle Scholar
  13. 13.
    Fonseca, N.L.S., Gilberto, M., e Neto, C.A.V.: On the equivalent bandwidth of self-similar sources. In: ACM Transactions on Modeling and Computer Simulation, vol. 10(2), pp. 104–124 (2000)Google Scholar
  14. 14.
    Lee, K., Toguyeni, A., Noce, A., Rahmani, A.: Comparison of Multipath Algorithms for Load Balancing in a MPLS Network. In: Kim, C. (ed.) ICOIN 2005. LNCS, vol. 3391, pp. 463–470. Springer, Heidelberg (2005)Google Scholar
  15. 15.
    Elwalid, A., Jin, C., Low, S., Widjaja, I.: MATE: MPLS Adaptive Traffic Engineering. In: Infocom 2001, pp. 1300–1309 (2001)Google Scholar
  16. 16.
    Fortz, B., Rexford, J., Thorup, M.: Traffic engineering with traditional IP routing protocols. IEEE Communications Magazine 40(10), 118–124 (2002)CrossRefGoogle Scholar
  17. 17.
    Fortz, B., Thorup, M.: Robust optimization of OSPF/IS-IS weights. In: Proc. INOC 2003, pp. 225–230 (2003)Google Scholar
  18. 18.
    Gerla, M., e Kleinrock, L.: On the Topological Design of Distributed Computer Networks. IEEE Transactions on Communications 25(1), 48–60 (1977)MathSciNetCrossRefGoogle Scholar
  19. 19.
    Solis Barreto, P., de Carvalho, P.H.P., Soares, A.M., Abdalla Jr., H.: A Traffic Model for Multimedia Applications in Converged Networks. In: 13th IEEE Modelling, Analysis and Simulation in Computer and Telecommunications, pp. 163–170. IEEE Computer Society, Los Alamitos (2005)Google Scholar
  20. 20.
    Solis Barreto, P., de Carvalho, P.H.P.: Hybrid Traffic Model for Multimedia Network Performance Evaluation. In: AINA - 22nd International Conference on Advanced Information Networking and Applications-Workshops, Okinawa, Japão. IEEE Computer Society, Los Alamitos (2008)Google Scholar
  21. 21.
    Kelly, F.P.: Notes on effective bandwidth. In: Kelly, F.P., Zachary, S., Ziedins, I.B. (eds.) Stochastic Networks: Theory and Applications, pp. 141–168. Oxford University Press, Oxford (1996)Google Scholar
  22. 22.
    Kesidis, G., Walrand, J., Chang, S.: Effective Bandwidths for Multiclass Markov Fluids and Other ATM Sources. IEEE/ACM Transactions on Networking 1(4), 424–428 (1993)CrossRefGoogle Scholar
  23. 23.
    Solis Barreto, P., de Carvalho, et al.: Open Source Software for Evaluation of Applications in an Experimental Testbed for Converged Networks. In: TRIDENTCOM 2006, p. 6 (2006)Google Scholar
  24. 24.
    Khanna, A., Zinky, J.: The revised ARPANET routing metric. ACM SIGCOMM Computer Communication Review 19(4), 45–56 (1989)CrossRefGoogle Scholar
  25. 25.
    Moy, J.: OSPF Version 2, RFC 2328 (accessed 14th, July 2007),

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Priscila Solís Barreto
    • 2
  • Paulo H. P. de Carvalho
    • 1
  • Rafael Dias Oliveira
    • 1
    • 2
  • Maximiliano Prestes Ceppo
    • 1
    • 2
  1. 1.Department of Electrical EngineeringBrasil
  2. 2.Department of Computer ScienceUniversity of BrasiliaBrasília-DFBrasil

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