Rate-distortion optimized frame dropping and scheduling for multi-user conversational and streaming video

We propose a Rate-Distortion (RD) optimized strategy for frame-dropping and scheduling of multi-user conversa- tional and streaming videos. We consider a scenario where conversational and streaming videos share the forwarding resources at a network node. Two buffers are setup on the node to temporarily store the packets for these two types of video applications. For streaming video, a big buffer is used as the associated delay constraint of the application is moderate and a very small buffer is used for conversational video to ensure that the forwarding delay of every packet is limited. A scheduler is located behind these two buffers that dynamically assigns transmission slots on the outgoing link to the two buffers. Rate-distortion side information is used to perform RD-optimized frame dropping in case of node overload. Sharing the data rate on the outgoing link between the con- versational and the streaming videos is done either based on the fullness of the two associated buffers or on the mean incoming rates of the respective videos. Simulation results showed that our proposed RD-optimized frame dropping and scheduling ap- proach provides significant improvements in performance over the popular priority-based random dropping (PRD) technique.

Distributed media cooperation for enhanced video communication

The author designed two algorithms for distributed cooperation among multiple video streams sharing common communication resources. The algorithms take advantage of an optimization framework that characterizes video packets such that joint resource allocation can be implemented not only over the packets of a single stream, but also across packets of different streams. The first algorithm enables collaboration among multiple video senders in an 802.11 CSMA/CA wireless network such that their joint performance is maximized. Via the algorithm, the users cooperatively establish transmission priorities based on the assigned characterizations of their video packets. The second technique allows for low-complexity joint bandwidth adaptation of multiple video streams at intermediate network nodes in the Internet in order to maximize the overall network performance. The author analyzes the advantages of the proposed algorithms over conventional solutions employed in such scenarios. It is shown that depending on system parameters such as available network data rate the proposed techniques can provide substantial gains in end-to-end performance.