Advertisement

On Algorithm for Efficiently Combining Two Independent Measures in Routing Paths

  • Moonseong Kim
  • Young-Cheol Bang
  • Hyunseung Choo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3483)

Abstract

This paper investigates the routing efficiency problem with quality of service (QoS). A solution to this problem is needed to provide real-time communication service to connection-oriented applications, such as video and voice transmissions. We propose a new weight parameter by efficiently combining two independent measures, the cost and the delay. The weight ω plays on important role in combining the two measures. If the ω approaches 0, then the path delay is low. Otherwise the path cost is low. Therefore if we decide an ω, we then find the efficient routing path. A case study shows various routing paths for each ω. We also use simulations to show the variety of paths for each ω. When network users have various QoS requirements, the proposed weight parameter is very informative.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Calvert, K.L., Doar, M.: Modelling Internet Topology. IEEE Communications Magazine, 160–163 (June 1997)Google Scholar
  2. 2.
    Doar, M.: Multicast in the ATM environment. PhD thesis, Cambridge Univ., Computer Lab. (September 1993)Google Scholar
  3. 3.
    Doar, M.: A Better Mode for Generating Test Networks. In: IEEE Proc. GLOBECOM 1996, pp. 86–93 (1996)Google Scholar
  4. 4.
    Garey, M., Johnson, D.: Computers and intractability: A Guide to the Theory of NP-Completeness. Freeman, New York (1979)zbMATHGoogle Scholar
  5. 5.
    Kim, M., Bang, Y.-C., Choo, H.: Estimated Link Selection for DCLC Problem. In: IEEE ICC 2004, June 2004, vol. 4, pp. 1937–1941 (2004)Google Scholar
  6. 6.
    Kumar, R., Raghavan, P., Rajagopalan, S., Sivakumar, D., Tomkins, A., Upfal, E.: Stochastic models for the Web graph. In: Proc. 41st Annual Symposium on Foundations of Computer Science, pp. 57–65 (2000)Google Scholar
  7. 7.
    Papoulis, A., Pillai, S.U.: Probability, Random Variables, and Stochastic Processes, 4th edn. McGraw-Hill, New York (2002)Google Scholar
  8. 8.
    Reeves, D.S., Salama, H.F.: A distributed algorithm for delay-constrained unicast routing. IEEE/ACM Transactions on Networking 8, 239–250 (2000)CrossRefGoogle Scholar
  9. 9.
    Rodionov, A.S., Choo, H.: On Generating Random Network Structures: Trees. In: Sloot, P.M.A., Abramson, D., Bogdanov, A.V., Gorbachev, Y.E., Dongarra, J., Zomaya, A.Y. (eds.) ICCS 2003. LNCS, vol. 2658, pp. 879–887. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  10. 10.
    Rodionov, A.S., Choo, H.: On Generating Random Network Structures: Connected Graphs. In: Kahng, H.-K., Goto, S. (eds.) ICOIN 2004. LNCS, vol. 3090, pp. 483–491. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  11. 11.
    Toh, C.-K.: Performance Evaluation of Crossover Switch Discovery Algorithms for Wireless ATM LANs. In: IEEE Proc. INFOCOM 1996, pp. 1380–1387 (1993)Google Scholar
  12. 12.
    Waxman, B.M.: Routing of Multipoint Connections. IEEE JSAC 9, 1617–1622 (1993)Google Scholar
  13. 13.
    Widyono, R.: The Design and Evaluation of Routing Algorithms for Real-Time Channels. In: International Computer Science Institute, Univ. of California at Berkeley, Tech. Rep. ICSI TR-94-024 (June 1994)Google Scholar
  14. 14.
    Zegura, E.W., Calvert, K.L., Bhattacharjee, S.: How to model an Internetwork. In: Proc. INFOVCOM 1996, pp. 594–602 (1996)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Moonseong Kim
    • 1
  • Young-Cheol Bang
    • 2
  • Hyunseung Choo
    • 1
  1. 1.School of Information and Communication EngineeringSungkyunkwan UniversitySuwonKorea
  2. 2.Department of Computer EngineeringKorea Polytechnic UniversityGyeonggi-DoKorea

Personalised recommendations