Video streaming uploading over vehicular ad hoc networks (VANETs) can support many interesting applications. Due to the high mobility and dynamic topology of VANETs, how to support video streaming using wireless communications between vehicles and road-side access points still remains an open issue. In this paper, we propose a geographical uploading scheme, called MPVUS, which uses the moving prediction to keep the stable forwarding and reduce the high link failure probability over VANETs. The scheme also decides the AP switch opportunity by traffic flow estimation, so as to adjust the forwarding direction timely to avoid the short-sighted switch decision. Simulation results demonstrate the effectiveness of our scheme, which can achieve good performance in terms of the start-up delay, playback interruption ratio and video frame distortion.

BGP dictates routing between autonomous systems with rich policy mechanisms in today's Internet. Operators translate high-level policy principles into low-level configurations of multiple routers without a comprehensive understanding of the actual effect on the network behaviors, making the routing management and operation an error-prone and time-consuming procedure. A fundamental question to answer is: how to verify the intended routing principles against the actual routing effects of an ISP? In this paper, we develop a methodology RPIM (Routing Policy Inference Model) towards this end. RPIM extracts from the routing tables various policy patterns, which represent certain high-level policy intentions of network operators, and then maps the patterns into specific design primitives that the ISP employs. To the best of our knowledge, we are the first to infer routing policies in ISP networks comprehensively from the aspects of business relationship, traffic engineering, scalability and security. We apply RPIM to 11 ASes selected from RIPE NCC RIS project, and query IRR database to validate our approach. Vast majority of inferred policies are confirmed by the policy registries, and RPIM achieves 96.23% accuracy excluding validation difficulties caused by incompleteness of the IRR database.