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dc.contributor.authorChrysostomou, Chrysostomosen
dc.contributor.authorPitsillides, Andreasen
dc.creatorChrysostomou, Chrysostomosen
dc.creatorPitsillides, Andreasen
dc.date.accessioned2019-11-13T10:39:23Z
dc.date.available2019-11-13T10:39:23Z
dc.date.issued2006
dc.identifier.issn1109-2742
dc.identifier.urihttp://gnosis.library.ucy.ac.cy/handle/7/53768
dc.description.abstractNetwork congestion control is a complex problem that requires robust, possibly intelligent, control methodologies to obtain satisfactory performance. Designing effective congestion control strategies for computer networks is known to be hard because of the difficulty of obtaining realistic, cost effective, tractable analytical models. This renders the application of classical control system design methods, which rely on availability of these models, very hard, and possibly not cost effective. Computational Intelligence employing Fuzzy Logic Control methodology is reported to offer effective solutions for certain classes of control problems. It is particularly appealing in non-linear complex systems where satisfactory analytic models are costly or impractical to obtain, but where their behaviour is well understood and can be captured by linguistic models. Consequently, a number of researchers have looked at fuzzy logic in order to devise effective, robust congestion control techniques. In this paper, we discuss several control approaches currently in use, before we motivate the utility of Fuzzy Logic based control. Then, through a number of examples, we illustrate the power of the methodology by the successful application of fuzzy based congestion control in the two diverse networking technologies of ATM and TCP/IP.en
dc.sourceWSEAS Transactions on Communicationsen
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-33746900817&partnerID=40&md5=c86cc9e7534996f497accf6af174a745
dc.subjectInterneten
dc.subjectMathematical modelsen
dc.subjectComputer networksen
dc.subjectNetwork protocolsen
dc.subjectAnalytical modelsen
dc.subjectQuality of serviceen
dc.subjectFuzzy setsen
dc.subjectFuzzy logicen
dc.subjectFuzzy controlen
dc.subjectAsynchronous transfer modeen
dc.subjectCongestion control (communication)en
dc.subjectATMen
dc.subjectCongestion controlen
dc.subjectTCP/IPen
dc.subjectActive queue managementen
dc.titleFuzzy logic based congestion control in computer networksen
dc.typeinfo:eu-repo/semantics/article
dc.description.volume5
dc.description.issue8
dc.description.startingpage1521
dc.description.endingpage1527
dc.author.faculty002 Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences
dc.author.departmentΤμήμα Πληροφορικής / Department of Computer Science
dc.type.uhtypeArticleen
dc.source.abbreviationWSEAS Trans.Commun.en
dc.contributor.orcidPitsillides, Andreas [0000-0001-5072-2851]
dc.contributor.orcidChrysostomou, Chrysostomos [0000-0002-9287-990X]
dc.gnosis.orcid0000-0001-5072-2851
dc.gnosis.orcid0000-0002-9287-990X


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