Self-adaptive routing based on learning classifier systems

Chung Yuan Huang*, Chuen-Tsai Sun

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Successful computer and internet networks require carefully designed routing protocols. The authors report on their attempt to apply evolutionary computations-that is, to place a learning classifier system on individual routers-to solve routing problems. We found that learning classifier systems are capable of fulfilling traditional routing protocol tasks (e.g., establishing routing tables) after a short period of training. Furthermore, they are capable of adapting to changing network environments and choosing the most efficient path available. Results from our experiments show that the system outperforms shortest path algorithms.

Original languageEnglish
Title of host publicationProceedings of the 2004 Congress on Evolutionary Computation, CEC2004
Pages678-682
Number of pages5
DOIs
StatePublished - 13 Sep 2004
EventProceedings of the 2004 Congress on Evolutionary Computation, CEC2004 - Portland, OR, United States
Duration: 19 Jun 200423 Jun 2004

Publication series

NameProceedings of the 2004 Congress on Evolutionary Computation, CEC2004
Volume1

Conference

ConferenceProceedings of the 2004 Congress on Evolutionary Computation, CEC2004
CountryUnited States
CityPortland, OR
Period19/06/0423/06/04

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  • Cite this

    Huang, C. Y., & Sun, C-T. (2004). Self-adaptive routing based on learning classifier systems. In Proceedings of the 2004 Congress on Evolutionary Computation, CEC2004 (pp. 678-682). (Proceedings of the 2004 Congress on Evolutionary Computation, CEC2004; Vol. 1). https://doi.org/10.1109/CEC.2004.1330924