Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/38618
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dc.coverage.spatialA study on performance enhancement Of multiclass network traffic using Effective queuing modelsen_US
dc.date.accessioned2015-04-06T04:37:33Z-
dc.date.available2015-04-06T04:37:33Z-
dc.date.issued2015-04-06-
dc.identifier.urihttp://hdl.handle.net/10603/38618-
dc.description.abstractQueue management methods and congestion control algorithms are newlineinevitable to keep the stability of the network This research work mainly newlinefocuses on improving the performance of network by implementing the newlineenhanced queuing models The first Chapter deals with a brief introduction newlineabout networks network architecture basic concepts of queuing theory newlineQuality of Service in networks role of queuing models for maintaining QoS newlineand various Active Queue Management techniques A detailed survey of newlineliterature is given in the second chapter newlineIn a network the elastic and inelastic flows require different types newlineof treatment in order to prevent the elastic flows from starving and inelastic newlineflows from congestion In the third chapter an Enhanced Core Stateless Fair newlineQueuing with Fuzzy Based Congestion Detection ECSFQ FBCD is newlinePresented With the expression for delay and loss, the flows are differentiated newlineinto elastic and inelastic flows Elastic flows are treated with max min newlineprinciple of CSFQ Further for inelastic flows a fuzzy based congestion newlinedetection is applied and as per the congestion level the flows are either newlinescheduled with Multiple Queue Fair Queuing MQFQ or with max min newlineprinciple of CSFQ newlineThe fourth chapter utilises the concept of CSFQ MQFQ and token newlinebucket model newline newlineen_US
dc.format.extentxx, 134p.en_US
dc.languageEnglishen_US
dc.relationp124-133.en_US
dc.rightsuniversityen_US
dc.titleA study on performance enhancement Of multiclass network traffic using Effective queuing modelsen_US
dc.title.alternativeen_US
dc.creator.researcherNandhini Sen_US
dc.subject.keywordActive Queue Management techniquesen_US
dc.subject.keywordFuzzy Based Congestion Detectionen_US
dc.subject.keywordMultiple Queue Fair Queuingen_US
dc.subject.keywordQuality of Serviceen_US
dc.description.notereference p124-133.en_US
dc.contributor.guidePalaniammal Sen_US
dc.publisher.placeChennaien_US
dc.publisher.universityAnna Universityen_US
dc.publisher.institutionFaculty of Science and Humanitiesen_US
dc.date.registeredn.d,en_US
dc.date.completed01/08/2014en_US
dc.date.awarded30/08/2014en_US
dc.format.dimensions23cm.en_US
dc.format.accompanyingmaterialNoneen_US
dc.source.universityUniversityen_US
dc.type.degreePh.D.en_US
Appears in Departments:Faculty of Science and Humanities

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01_title.pdfAttached File43.89 kBAdobe PDFView/Open
02_certificate.pdf2.09 MBAdobe PDFView/Open
03_abstract.pdf9.35 kBAdobe PDFView/Open
04_acknowledgement.pdf7.53 kBAdobe PDFView/Open
05_content.pdf43.2 kBAdobe PDFView/Open
06_chapter1.pdf41.64 kBAdobe PDFView/Open
07_chapter2.pdf54.01 kBAdobe PDFView/Open
08_chapter3.pdf310.35 kBAdobe PDFView/Open
09_chapter4.pdf137.86 kBAdobe PDFView/Open
10_chapter5.pdf156.97 kBAdobe PDFView/Open
11_chapter6.pdf336.61 kBAdobe PDFView/Open
12_chapter7.pdf153.21 kBAdobe PDFView/Open
13_reference.pdf470.36 kBAdobe PDFView/Open
14_publication.pdf22.6 kBAdobe PDFView/Open


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