English   español  
Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/83285
logo share SHARE   Add this article to your Mendeley library MendeleyBASE

Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL
Exportar a otros formatos:

Inference systems for network traffic control

AuthorsMontesino Pouzols, Federico ; López, D. R.; Barriga, Angel
Issue Date2011
CitationMining and Control of Network Traffic by Computational Intelligence (Cap.5): 191-262 (2011)
SeriesStudies in Computational Intelligence 342
AbstractThis 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.
Identifiersdoi: 10.1007/978-3-642-18084-2_5
isbn: 978-3-642-18083-5
Appears in Collections:(IMSE-CNM) Libros y partes de libros
Files in This Item:
File Description SizeFormat 
accesoRestringido.pdf15,38 kBAdobe PDFThumbnail
Show full item record
Review this work

WARNING: Items in Digital.CSIC are protected by copyright, with all rights reserved, unless otherwise indicated.