Abstract| Rate-distortion (R-D) optimized mode selection is a fundamental problem for video communication over packet-switched networks. The classical R-D optimized mode selection only considers quantization distortion at the source. Such approach is unable to achieve global optimality under the error-prone environment since it does not consider the packetization behavior at the source, the transport path characteristics and receiver behavior. This paper presents an end-to-end approach to generalize the classical theory of R-D optimized mode selection for point-to-point v i d e o communication. We i n troduce a notion of global distortion by taking into consideration both the path characteristics (i.e., packet loss) and the receiver behavior (i.e., the error concealment s c heme), in addition to the source behavior (i.e., quantization distortion and packetization). We derive, for the rst time, a set of accurate global distortion metrics for any packetization scheme. Equipped with the global distortion metrics, we design an R-D optimized mode selection algorithm to provide the best trade-o between compression e ciency and error resilience. The theory developed in this paper is general and is applicable to many video coding standards, including H.261/263 and MPEG-1/2/4. As an application, we i n tegrate our theory with point-to-point MPEG-4 video conferencing over the Internet, where a feedback mechanism is employed to convey the path characteristics (estimated at the receiver) and receiver behavior (error concealment s c heme) to the source. Simulation results conclusively demonstrate that our end-to-end approach o ers superior performance over the classical approach f o r I n ternet video conferencing.

Abstract-It has been widely acknowledged that online storage systems within the "cloud" of the Internet provide services of a substantial value to end users who wish to share files of any sizes within a group. Such online storage services are typically provided by dedicated servers, either in content distribution networks (CDNs) or large data centers. Server bandwidth costs, however, are prohibitive in these cases, especially when serving large volumes of files to a large number of users. Though it seems intuitive to take advantage of peer upload bandwidth to mitigate such server bandwidth costs in a complementary fashion, it is not trivial to design and fine-tune important aspects of such peerassisted online storage in a real-world large-scale deployment.This paper presents FS2You, a large-scale and real-world online storage system with peer assistance and semi-persistent file availability, in order to dramatically mitigate server bandwidth costs. In this paper, we show a number of challenges involved in such a design objective, our architectural and protocol design in response to these challenges, as well as an extensive measurement study at a large scale to demonstrate the effectiveness of our design, using real-world traces that we have collected. To our knowledge, this paper represents the first attempt to design, implement, and evaluate a new peer-assisted semi-persistent online storage system at a realistic scale. Since the launch of FS2You, it has quickly become one of the most popular online storage systems in mainland China, and a favorite in many online forums across the country.

The Peer-to-Peer (P2P) live video streaming system has been demonstrated to have great potential in the public Internet; the large-scale deployment of such systems, however, critically relies on how effective they can deal with the high dynamics encountered, in particular during flash crowd. The rationale behind is that the scaling in P2P live video streaming systems is heavily determined by the timing requirement that streaming applications demand. In this paper, we present an analytical and experimental study on the inherent relationship between the time constraint and the system scale. We develop a generic model for P2P live video streaming that focuses on the peer joining process during flash crowd. We first illustrate that the simple notion of "demand vs. supply" model is insufficient in describing the system scale. By computing the peer start-up time distribution, we demonstrate that the scale is affected by several key factors, especially the peer uploading capacity and the initial system size. We further show the scale is essentially bounded by the timing requirement and the system's capability to accommodate flash crowd is subject to a maximum limit.