Intelligent video network engineering with distributed optimization: Two case studies

Video is becoming the dominant traffic over the Internet. To provide better Quality of Service (QoS) to the end users, while also achieve network resource efficiency, is an important problem for both network operators, content providers and consumers. In this work, we present intelligent video networking solutions for IPTV and Peer-to-Peer (P2P) systems that optimizes the users' QoS experiences while under network resource constraints. Given the limited network bandwidth resources, how to provide Internet users with good video playback Quality of Service (QoS) is a key problem. For IPTV systems video clips competing bandwidth, we propose an approach of Content-Aware distortion-Fair (CAF) video delivery scheme, which is aware of the characteristics of video frames and ensures max-min distortion fair sharing among video flows. Different from bandwidth fair sharing, CAF targets end-to-end video playback quality fairness among users when bandwidth is insufficient, based on the fact that users directly care about video quality rather than bandwidth. The proposed CAF approach does not require rate-distortion modeling of the source, which is difficult to estimate, but instead, it exploits the temporal prediction structure of the video sequences along with a frame drop distortion metric to guide resource allocations and coordination. Experimental results show that the proposed approach operates with limited overhead in computation and communication, and yields better QoS, especially when the network is congested. For Internet based video broadcasting applications such as IPTV, the Peer-to-Peer (P2P) streaming scheme has been found to be an effective solution. An important issue in live broadcasting is to avoid playback buffer underflow. How to utilize the playback buffer and upload bandwidth of peers to minimize the freeze-ups in playback, is the problem we try to solve. We propose a successive water-filling (SWaF) algorithm for the video transmission scheduling in P2P live streaming system, to minimize the playback freeze-ups among peers. SWaF algorithm only needs each peer to optimally transmit (within its uploading bandwidth) part of its available video segments in the buffer to other peers requiring the content and pass small amount message to some other peers. Moreover, SWaF has low complexity and provable optimality. Numerical results demonstrated the effectiveness of the proposed algorithm.