The Effects of Packet Delay Variation on the Perceptual Quality of Video
|Document type:||Conference Papers|
|Author(s):||Selim Ickin, Karel De Vogeleer, Markus Fiedler, David Erman|
|Title:||The Effects of Packet Delay Variation on the Perceptual Quality of Video|
|Conference name:||4th IEEE Workshop On User MObility and VEhicular Networks (On-MOVE 2010)|
|City:||Denver, Colorado, USA|
|Organization:||Blekinge Institute of Technology|
|Department:||School of Computing (Sektionen för datavetenskap och kommunikation)
School of Computing S-371 79 Karlskrona
+46 455 38 50 00
|Abstract:||The satisfaction of end-users is important when evaluating services and products. Visualizing the network behavior in mobile streaming as well as modeling the correlation between Quality of Service (QoS) and Quality of Experience (QoE) is expected to improve user satisfaction of services on the Internet. Given that network and human factors are the elements that affect the final output of the measurements, it is important to take the Packet Delay Variation (PDV) into consideration. In this paper we observe the PDV during a series of real-life experiments on a 3rd Generation (3G) network while streaming videos. User Rating (UR) values from user input are recorded accordingly. With this aim, we implemented a QoE assessment tool that measures network metrics in kernel space, while simultaneously logging user ratings with regards to the perception of an ongoing real- time video on an Android phone.
The primary goal is to identify a clear trend, so that we can assess the satisfaction of a user by deriving the QoE from measurable QoS metrics. We find that PDV degrades user perception. Observations show that, during the experiments, sudden breaks and restarts in the packet flow exist, which we call on-off flushing throughout this paper. Even though the use of Exponentially Weighted Moving Average (EWMA) assists in finding a model that shows the relationship between PDV and UR, on-off flushing is a major threat affecting this relationship. The results show that correlations with different quality can be reached with various modifications of the proposed matching model.
|Subject:||Computer Science\Networks and Communications|
|Keywords:||Quality of Experience (QoE), network measurements, QoE modeling, Always Best Connected (ABC)|