Self-adaptive routing based on learning classifier systems

Chung Yuan Huang; Chuen-Tsai Sun

doi:10.1109/CEC.2004.1330924

Self-adaptive routing based on learning classifier systems

Chung Yuan Huang^*, Chuen-Tsai Sun

^*Corresponding author for this work

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-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 language	English
Title of host publication	Proceedings of the 2004 Congress on Evolutionary Computation, CEC2004
Pages	678-682
Number of pages	5
DOIs	https://doi.org/10.1109/CEC.2004.1330924
State	Published - 13 Sep 2004
Event	Proceedings of the 2004 Congress on Evolutionary Computation, CEC2004 - Portland, OR, United States Duration: 19 Jun 2004 → 23 Jun 2004

Publication series

Name	Proceedings of the 2004 Congress on Evolutionary Computation, CEC2004
Volume	1

Conference

Conference	Proceedings of the 2004 Congress on Evolutionary Computation, CEC2004
Country	United States
City	Portland, OR
Period	19/06/04 → 23/06/04

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10.1109/CEC.2004.1330924

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title = "Self-adaptive routing based on learning classifier systems",

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.",

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Huang, CY & Sun, C-T 2004, Self-adaptive routing based on learning classifier systems. in Proceedings of the 2004 Congress on Evolutionary Computation, CEC2004. Proceedings of the 2004 Congress on Evolutionary Computation, CEC2004, vol. 1, pp. 678-682, Proceedings of the 2004 Congress on Evolutionary Computation, CEC2004, Portland, OR, United States, 19/06/04. https://doi.org/10.1109/CEC.2004.1330924

Self-adaptive routing based on learning classifier systems. / Huang, Chung Yuan; Sun, Chuen-Tsai.

Proceedings of the 2004 Congress on Evolutionary Computation, CEC2004. 2004. p. 678-682 (Proceedings of the 2004 Congress on Evolutionary Computation, CEC2004; Vol. 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Self-adaptive routing based on learning classifier systems

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