Self-adaptive routing method based on learning classifier systems

Chungyuan Huang*, Chuen-Tsai Sun, Chenghsien Yu, Chaofang Chen

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

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
Pages417-421
Number of pages5
StatePublished - 17 Sep 2004
EventWCICA 2004 - Fifth World Congress on Intelligent Control and Automation, Conference Proceedings - Hangzhou, China
Duration: 15 Jun 200419 Jun 2004

Conference

ConferenceWCICA 2004 - Fifth World Congress on Intelligent Control and Automation, Conference Proceedings
CountryChina
CityHangzhou
Period15/06/0419/06/04

Keywords

  • Genetic algorithms
  • Learning classifier systems
  • Reinforcement learning
  • Routing protocol
  • Self-adaptive

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