Digital video processing
Simulation and Analysis of Packet Loss in User Datagram Protocol Transfers
The Journal of Supercomputing
Temporal Synchronization Models for Multimedia Data
IEEE Transactions on Knowledge and Data Engineering
A Method and Apparatus for Measurung media Synchronization
NOSSDAV '95 Proceedings of the 5th International Workshop on Network and Operating System Support for Digital Audio and Video
Real-Time Motion-Based Frame Estimation in Video Lossy Transmission
SAINT '01 Proceedings of the 2001 Symposium on Applications and the Internet (SAINT 2001)
Generation of High Bandwidth Network Traffic Traces
MASCOTS '02 Proceedings of the 10th IEEE International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems
SCAN-Based Compression-Encryption-Hiding for Video on Demand
IEEE MultiMedia
A Prototyping Tool for Analysis and Modeling of Video Transmission Traces over IP Networks
RSP '06 Proceedings of the Seventeenth IEEE International Workshop on Rapid System Prototyping
Streaming Video with Transformation-Based Error Concealment and Reconstruction
ICMCS '99 Proceedings of the IEEE International Conference on Multimedia Computing and Systems - Volume 2
The optimal error exponent for Markov order estimation
IEEE Transactions on Information Theory
A survey of packet loss recovery techniques for streaming audio
IEEE Network: The Magazine of Global Internetworking
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In the best-effort IP network, quality of service (QoS) cannot be guaranteed, and thus packets could possibly be delayed or lost. Packet delay/loss will inevitably degrade the perceptual quality of real-time multimedia-over-IP service, such as Voice-over-IP (VoIP), Video-on-Demand (VoD), etc. In general, packet loss/delay exhibits temporal dependence. In order to efficiently conduct error recovery/concealment and improve the perceptual quality of the transmitted multimedia contents, packet loss/delay has to be precisely modeled. Different mathematical models, such as Bernoulli Model, Gilbert Model, Extended Gilbert Model, have been proposed to model network trace. However, none of them is able to precisely model the networked multimedia trace like the General Markov Model (GMM), which has rarely been applied in practice due to massive computational resource requirements. With the developments of modern computing hardware and parallel processing algorithms, GMM is becoming computationally feasible. In this paper, in order to obtain network traces for real-time VoD transmission, different connections have been setup to simulate a real VoD system. Data packets have been transmitted between the server and clients under RTP/UDP/IP protocol stack. Different models have been applied to analyze and model the obtained video transmission network traces. Specifically, a 6-state GMM has been applied to analyze the network trace, and the parameterized model has been obtained for further error recover/concealment. Compared to the other models, GMM offers the best modeling precision, in terms of loss-run distribution (LSD) and Forward Error Correction (FEC) performance prediction. The parameterized GMM is very useful to model and analyze network traces and further improve the QoS in multimedia-over-IP based on the modeling and analysis.