PRAM: Penalized Resource Allocation Method for Video Services

The human visual system response to picture quality degradation due to packet loss is very different from the responses of objective quality measures. While video quality due to packet loss may be impaired by at most for one Group of Pictures (GOP), its subjective quality degradation may last for several GOPs. This has a great impact on resource allocation strategies, which normally make decisions on instantaneous conditions of multiplexing buffer. This is because, when the perceptual impact of degraded video quality is much longer than its objective degradation period, any assigned resources to the degraded flow is wasted. This paper, through both simulations and analysis shows that, during resource allocation, if the quality of a video stream is significantly degraded, it is better to penalize this degraded flow from getting its full bandwidth share and instead assign the remaining share to other flows preventing them from undergoing quality degradation

Efficient Streaming Packet Video over Differentiated Services Networks

We investigate streaming video over Differentiated Services (Diffserv) networks that can provide a number of aggregated traffic classes with increasing quality guarantee. We propose a method to measure the loss impact of a video packet on the quality of the decoded video images. We show how the optimal Quality-of-Service (QoS) mapping from the video packets into a set of traffic classes depends on the loss rates of the classes and the pricing model, and we develop an algorithm to accurately find the optimal QoS mapping. The performance of our algorithm is evaluated through computer simulations and compares favorably to an existing algorithm