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