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... 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. Read More Read Less