Evaluating The Use Of Qos For Video Delivery In Vehicular Networks

In a near future, video transmission capabilities in intelligent vehicular networks will be essential for deploying high-demanded multimedia services for drivers and passengers. Applications and services like video on demand, iTV, context-aware video commercials, touristic information, driving assistance, multimedia e-call, etc., will be part of the common multimedia service-set of future transportation systems. However, wireless vehicular networks introduce several constraints that may seriously impact on the final quality of the video content delivery process. Factors like the shared-medium communication model, the limited bandwidth, the unconstrained delays, the signal propagation issues, and the node mobility, will be the ones that will degrade video delivery performance, so it will be a hard task to guarantee the minimum quality of service required by video applications. In this work, we will study how these factors impact on the received video quality by using a detailed simulation model of a urban vehicular network scenario. We will apply different techniques to reduce the video quality degradation produced by the transmission impairments like (a) Intra-refresh video coding modes, (b) frame partitioning (tiles/slices), and (c) quality of service at the Medium Access Control (MAC) level. So, we will learn how these techniques are able to fight against the network impairments produced by the hostile environment typically found in vehicular network scenarios. The experiments were carried out with a simulation environment based on the OMNeT++, Veins and SUMO simulators. Results show that the combination of the proposed techniques significantly improves the robustness of video transmission in vehicular networks, paving the way, with a wise collaboration with other techniques, to achieve a robust video delivery system that supports multimedia applications in future intelligent transportation systems.