Unequal error protection systems are a popular technique for video streaming. Forward error correction (FEC) is one of error control techniques to improve the quality of video streaming over lossy channels. Moreover, frame-level FEC techniques have been proposed for video streaming because of different priority video frames within the transmission rate constraint on a Bernoulli channel. However, various communication and storage systems are likely corrupted by bursts of noise in the current wireless behavior. If the burst losses go beyond the protection capacity of FEC, the efficacy of FEC can be degraded. Therefore, our proposed model allows an assessment of the perceived quality of H.264/AVC video streaming over bursty channels, and is validated by simulation experiments on the NS-2 network simulator at a given estimate of the packet loss ratio and average burst length. The results suggest a useful reference in designing the FEC scheme for video applications, and as the video coding and channel parameters are given, the proposed model can provide a more accurate evaluation tool for video streaming over bursty channels and help to evaluate the impact of FEC performance on different burst-loss parameters.
The QoS support for multimedia on wireless network is one of the most important researches in recent years. IEEE wireless 802.1le is the most hopeful among these methods. However, the performance metrics used in 802.1le experiments are almost network-level measures. They represent the network state and not the perceptual quality of the end user. Besides, wireless network is error prone and errors are unavoidable. In this paper, we evaluate the effect of Random error Model and Gillbert-Elliot(GE) error model on the quality of multimedia applications.
With the wide deployment of wireless networks and the rapid integration of various emerging networking technologies nowadays, Internet video applications must be updated on a sufficiently timely basis to support high end-to-end quality of service (QoS) levels over heterogeneous infrastructures. However, updating the legacy applications to provide QoS support is both complex and expensive since the video applications must communicate with underlying architectures when carrying out QoS provisioning, and furthermore, should be both aware of and adaptive to variations in the network conditions. Accordingly, this paper presents a transparent loss recovery scheme to transparently support the robust video transmission on behalf of real-time streaming video applications. The proposed scheme includes the following two modules: (i) a transparent QoS mechanism which enables the QoS setup of video applications without the requirement for any modification of the existing legacy applications through its use of an efficient packet redirection scheme; and (ii) an instant frame-level FEC technique which performs online FEC bandwidth allocation within TCP-friendly rate constraints in a frame-by-frame basis to minimize the additional FEC processing delay. The experimental results show that the proposed scheme achieves nearly the same video quality that can be obtained by the optimal frame-level FEC under varying network conditions while maintaining low end-to-end delay.
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