On the Relevance of Using Gene Expression Programming in Destination-Based Traffic Engineering

  • Antoine B. Bagula
  • Hong F. Wang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3801)


This paper revisits the problem of Traffic Engineering (TE) to assess the relevance of using Gene Expression Programming (GEP) as a new fine-tuning algorithm in destination-based TE. We present a new TE scheme where link weights are computed using GEP and used as fine-tuning parameters in destination-based path selection. We apply the newly proposed TE scheme to compute the routing paths for the traffic offered to a 23- and 30-node test networks under different traffic conditions and differentiated services situations. We evaluate the performance achieved by the GEP algorithm compared to a memetic and the Open Shortest Path First (OSPF) algorithms in a simulated routing environment using the NS packet level simulator. Preliminary results reveal the relative efficiency of GEP compared to the memetic algorithm and OSPF routing.


Gene Expression Programming Memetic Algorithm Link Weight Open Short Path First Maximum Link Utilisation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Antoine B. Bagula
    • 1
  • Hong F. Wang
    • 1
  1. 1.Department of Computer ScienceUniversity of StellenboschStellenboschSouth Africa

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