QOS Mapping using Human Factors for Fine Granular Scalability

To offer successful streaming video services, the Internet must have some kind of QoS control at each level of the protocol stack. This paper uses fine granular scalability for application-level QoS, because of its ability to adjust to a wide range of network channel capacities. We conduct an experiment using the DSIS method to subjectively assess fine granular scalability. Our results show that fine granular scalability provides only SNR scalability, not subjective image quality scalability. A multiple regression analysis shows that we can establish QoS mapping between user and application-levels by using both application-level QoS parameters and the human factor. Furthermore, we show that FGS can adjust to not only a wide range of channel capacities but also a wide variety of users by using the indicated QoS mapping.