In this work we propose a new approach to account for burst packet loss during transmission of 3D objects represented by texture and mesh over unreliable networks. Our strategy includes applying stripification on the 3D mesh following the valence-driven algorithm and distributing nearby vertices into different packets, combined with an interleaving technique that does not need texture or mesh packets to be re-transmitted. The perceptually-driven technique is able to successfully interpolate lost mesh features even under severe packet loss. The reconstructed mesh is further improved by applying our curvature-driven probabilistic strategy to safeguard visually significant structures on the 3D surface. Experimental results show that smoothness on the object surface is preserved even at 50% packet loss. At 75% packet loss, smoothness on the object surface deteriorates but the overall shape of an object is still preserved. We also define a Quality of Experience (QoE) metric to formulate the Just-Noticeable-Difference (JND) concept, to quantify the qualitative findings obtained from earlier subjective user studies, which provides flexibility to applications for reducing the transmission of visually redundant data.

Transmissions over wireless and other unreliable networks can lead to packet loss. An area that has received limited research attention is how to tailor multimedia information taking into account the way packets are lost. We provide a brief overview of our research on designing a 3D perceptual quality metric integrating two important factors, resolution of texture and resolution of mesh, which control transmission bandwidth. We then suggest alternative strategies for packet 3D transmission of both texture and mesh. These strategies are then compared with respect to preserving 3D perceptual quality under packet loss in ad hoc wireless networks. Experiments are conducted to study how the time between consecutive packet transmission and packet size affects loss in wireless channels. A preliminary model for estimating the optimal packet size is then proposed

The extreme heterogeneity in the P2P Internet environment causes the connections to candidate peers to vary significantly. Thus, selecting good candidate peers is critical to P2P networking performance. While most research in the literature focus on selecting peers with low latency, high uploading bandwidth, and high serving stability by time-consuming end-to-end measurement, we address how to quickly narrow the scope of good candidate peers. In this paper, we proposed to pick out the close peers from the same location or with low round-trip time from each other, by observing that close peers share routers along the traceroute path to the same destination. Our method only maintains online peers's traceroute records, without any offline database. Experiments with real traceroute records from 352 different IP addresses around the world verify the efficiency of our method