On the relevance of using gene expression programming in destination-based traffic engineering

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dc.contributor.authorBagula A.B.
dc.contributor.authorWang H.F.
dc.date.accessioned2011-05-15T16:02:07Z
dc.date.available2011-05-15T16:02:07Z
dc.date.issued2005
dc.description.abstractThis 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. © Springer-Verlag Berlin Heidelberg 2005.
dc.description.versionConference Paper
dc.identifier.citationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.identifier.citation3801 LNAI
dc.identifier.issn3029743
dc.identifier.other10.1007/11596448_32
dc.identifier.urihttp://hdl.handle.net/10019.1/12313
dc.subjectAlgorithms
dc.subjectComputer simulation
dc.subjectParameter estimation
dc.subjectRouters
dc.subjectTelecommunication traffic
dc.subjectFine-tuning parameters
dc.subjectGene Expression Programming (GEP)
dc.subjectRouting paths
dc.subjectTraffic Engineering (TE)
dc.subjectComputer programming
dc.titleOn the relevance of using gene expression programming in destination-based traffic engineering
dc.typeConference Paper
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