Inference systems for network traffic control

Federico Montesino Pouzols; Diego R. Lopez; Angel Barriga Barros

doi:10.1007/978-3-642-18084-2_5

Inference systems for network traffic control

Federico Montesino Pouzols, Diego R. Lopez, Angel Barriga Barros

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

Abstract

This chapter deals with control of network traffic in routers as well as end-to-end flows. First it is proposed an scheme for implementing end-to-end traffic control mechanisms through fuzzy inference systems. A comparative evaluation of simulation and implementation results from the fuzzy rate controler as compared to that of traditional TCP flow and rate control mechanisms is performed for a wide set of realistic scenarios. Then, fuzzy inference systems for traffic control in routers are designed. A particular proposal has been evaluated in realistic scenarios and is shown to be robust. The proposal is compared against the random early detection (RED) scheme. It is experimentally shown that fuzzy systems can provide better performance and better adaptation to different requirements with mechanisms that are easy to modify using linguistic knowledge.

Original language	English
Title of host publication	Mining and Control of Network Traffic by Computational Intelligence
Pages	191-262
Number of pages	72
Volume	342
DOIs	https://doi.org/10.1007/978-3-642-18084-2_5
Publication status	Published - 2011
MoE publication type	A3 Book section, Chapters in research books

Publication series

Name	Studies in Computational Intelligence
Volume	342
ISSN (Print)	1860-949X

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10.1007/978-3-642-18084-2_5

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AB - This chapter deals with control of network traffic in routers as well as end-to-end flows. First it is proposed an scheme for implementing end-to-end traffic control mechanisms through fuzzy inference systems. A comparative evaluation of simulation and implementation results from the fuzzy rate controler as compared to that of traditional TCP flow and rate control mechanisms is performed for a wide set of realistic scenarios. Then, fuzzy inference systems for traffic control in routers are designed. A particular proposal has been evaluated in realistic scenarios and is shown to be robust. The proposal is compared against the random early detection (RED) scheme. It is experimentally shown that fuzzy systems can provide better performance and better adaptation to different requirements with mechanisms that are easy to modify using linguistic knowledge.

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Inference systems for network traffic control

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