No abstract

This paper describes the Stanford P2P Multicast (SPPM) streaming system that employs an overlay architecture specifically designed for low delay video applications. In order to provide interactivity to the user, this system has to keep the end-to-end delay as small as possible while guaranteeing a high video quality. A set of complimentary multicast trees is maintained to efficiently relay video traffic and a Congestion-Distortion Optimized (CoDiO) scheduler prioritizes more important video packets. Local retransmission is employed to mitigate packet loss. Real-time experiments performed on the Planet-Lab show the effectiveness of the system and the benefits of a content-aware scheduler in case of congestion or node failures.

Video streaming with virtual pan/tilt/zoom functionality allows the viewer to watch arbitrary regions of a high-spatial-resolution scene. In our proposed system, the user controls his region-of-interest (ROI) interactively during the streaming session. The relevant portion of the scene is rendered on his screen immediately. An additional thumbnail overview aids his navigation. We design a peer-to-peer (P2P) multicast live video streaming system to provide the control of interactive region-of-interest (IROI) to large populations of viewers while exploiting the overlap of ROIs for efficient and scalable delivery. Our P2P overlay is altered on-the-fly in a distributed manner with the changing ROIs of the peers. The main challenges for such a system are posed by the stringent latency constraint, the churn in the ROIs of peers and the limited bandwidth at the server hosting the IROI video session. Experimental results with a network simulator indicate that the delivered quality is close to that of an alternative traditional unicast client-server delivery mechanism yet requiring less uplink capacity at the server.Index Terms-peer-to-peer video streaming, interactive regionof-interest, pan/tilt/zoom

In live peer-to-peer streaming, a video stream is transmitted to a large population of viewers, through the use of the uplink bandwidth of participating peers. This approach overcomes the cost of large-scale deployment of such services. An essential problem of this type of system is to limit the incurred congestion. In particular, overwhelming the uplink of some peers would create a large increase in the latency of the system and make this application less compelling. In this work we focus on limiting the congestion in a peer-to-peer network where multiple multicast trees are used to distribute video to a large set of receivers. We present the idea of congestiondistortion optimized streaming which aims at maximizing decoded video quality while limiting network congestion. We describe how this type of media scheduling maintains high video quality even for low latencies, and extend its usage to the peer-to-peer scenario. Experiments over a simulated network of 300 peers illustrate the benefits of the suggested approach.

We study peer-to-peer multicast streaming, where a source distributes real-time video to a large population of hosts by making use of their forwarding capacity rather than relying on dedicated media servers. We present a distributed streaming protocol which builds and maintains multiple multicast trees. The protocol is combined with an adaptive scheduling algorithm which ensures packets destined to a large number of peers, or particularly important to decode the video, are sent in priority. Experiments carried out over a simulated network of up to 3000 peers illustrate the performance of the protocol. For low latency video streaming, the prioritization algorithm offers performance gains, especially for large audiences and low latencies.