Performance Evaluation of Diffserv in Various Scenarios with Machine Learning Classification Effect
Neji Kouka, Jawaher ben khalfa , Jalel eddine hajaloui
Journal of Networking Technology, Vol. 16, No. 3, 2025.
DOI: https://doi.org/10.6025/jnt/2025/16/3/95-107
Link: https://www.dline.info/jnt/fulltext/v16n3/jntv16n3_1.pdf
Abstract:
DiffServ was introduced by the IETF as a standard model to offer QoS across core networks. DiffServ supports
a QoS feature based on differentiated traffic. So far, little interest has been shown in machine learning features
in QoS. In this paper, we evaluate the effectiveness of this model in QoS in various scenarios. We show that
under a heavy network load, DiffServ with machine learning classification (MLC) has a limited effect on the
QoS parameter.