An algorithm for lossless smoothing of MPEG video
SIGCOMM '94 Proceedings of the conference on Communications architectures, protocols and applications
IEEE/ACM Transactions on Networking (TON)
Adaptive rate control for streaming stored fine-grained scalable video
NOSSDAV '02 Proceedings of the 12th international workshop on Network and operating systems support for digital audio and video
Empirical Study of VBR Traffic Smoothing in Wireless Environment
IICS '02 Proceedings of the Second International Workshop on Innovative Internet Computing Systems
Overview of fine granularity scalability in MPEG-4 video standard
IEEE Transactions on Circuits and Systems for Video Technology
Incorporating packet semantics in scheduling of real-time multimedia streaming
Multimedia Tools and Applications
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In this work, we propose novel packet scheduling algorithm for real-time streaming of multi-resolution video. Our scheduling algorithm targets towards the situation where there exists relatively large fluctuation in bandwidth availability and the short queue depth in the receiver's end. The proposed algorithm determines which packets to send and when to send them. We develop QoS significance metric to represent the importance of a packet. QoS significance incorporates the composite transitive dependency in multi-resolution video. We develop QoS weighted traffic smoothing to determine the transmission schedule. We found that when the receiver has short queue length, e.g. mobile terminal, packet loss is very sensitive to the packet interval distribution. In determining the packet transmission schedule, we consider not only the bandwidth process of the packet traffic but also the importance of the individual packets. We introduce more slack for more important packet. We found that QoS weighted traffic smoothing makes the resulting bandwidth process burstier and entails more packet losses. However, it greatly enhances the user perceivable QoS. The simulation results show that the our scheme not only maximizes user perceivable QoS but also minimizes resource requirements.