A naïve Bayes Multi-class Weighted Classifier of Internet Packet flows over a MPLS Network

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AuteurDEGUENONVO, ROLAND
AuteurDOSSOU OLORY, AUDACE AMEN VIOUTOU
AuteurSANYA, MAX FREJUS O
Date d'ajout2026-06-02T16:06:57Z
Date de disponibilite2026-06-02T16:06:57Z
Date de publication2022
ResumeOur simulation is based first, on a qualitative approach for the classification of flows and traffic, and next on an experimental approach for the management of data volume on the other hand. The adopted approaches allowed us to get an idea on a NBWM (Naive Bayes Weighted Multi-class) classifier capable to output differentiated service classes in MPLS (Multiple Protocol Label Switching) networks. The classifiers we compared to our benchmark model were thoroughly processed. The accuracy rate of the proposed NBWM (Naïve Bayes Weighted Multiclass) classifier is about 68.75%, which puts it ahead of the other models encoun- tered.
DOI10.55162/MCET.03.062
Autre identifiantBECDB-16877
URIhttps://dspace.uac.bj/handle/123456789/14108
Languefr
Fait partie deMedicon Engineering Themes
SujetSimulation
Sujetflow and traffic classification
SujetNBMW classifier
SujetMPLS networks
Sujetaccuracy rate
TitreA naïve Bayes Multi-class Weighted Classifier of Internet Packet flows over a MPLS Network
TypeArticle

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