Multimedia Data Flow Traffic Classification Using Intelligent Models Based on Traffic Patterns

• Published in: IEEE network Vol. 32; no. 6; pp. 100 - 107
• Main Authors: Canovas, Alejandro, Jimenez, Jose Miguel, Romero, Oscar, Lloret, Jaime
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.11.2018; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Classification; Data mining; Jitter; Multimedia; Multimedia communication; Order parameters; Packet loss; Quality assessment; Streaming media; Telecommunication network management; Telecommunication traffic; Traffic control; Traffic flow; Traffic models; Video data; Video transmission
• DOI: 10.1109/MNET.2018.1800121
• ISSN: 0890-8044

Nowadays, there is high interest in modeling the type of multimedia traffic with the purpose of estimating the network resources required to guarantee the quality delivered to the user. In this work we propose a multimedia traffic classification model based on patterns that allows us to differentiate the type of traffic by using video streaming and network characteristics as input parameters. We show that there is low correlation between network parameters and the delivered video quality. Because of this, in addition to network parameters, we also add video streaming parameters in order to improve the efficiency of our system. Finally, it should be noted that, based on the objective video quality received by the user, we have extracted traffic patterns that we use to perfor