Efficient high-resolution video delivery over VANETs

Abstract

The adoption of video-equipped vehicles in Vehicular ad-hoc networks (VANETs) is experiencing a rapid growth. It is also anticipated a substantial increase in the video content distribution with the arrival of self-driving cars as both passengers and vehicles will be able to produce and consume this type of media. This unveils a set of challenges, especially in VANETs where the network resources tend to be scarce and the connections suffer from time-varying error conditions. Taking everything into consideration, a Quality of Experience (QoE)-driven mechanism is desirable to enhance the video delivery over error-prone networks. To this end, the combined use of forward error correction and unequal error protection has proven its efficiency in delivering high-quality videos with low network overhead. The proposed intelligent quality-driven and network-aware mechanism (AntArmour) uses an ant colony optimization scheme to dynamically allocate a precise amount of redundancy. This allows AntArmour to safeguard, in real-time, the live transmission of high-resolution video streams. This operation is performed according to specific high efficiency video coding details and the actual network conditions such as the signal-to-noise ratio, the network density, the vehicle’s position, and the current packet loss rate (PLR) as well as the prediction of future PLR. The experiments were performed using real map’s clippings and actual video footage. The assessment was performed with the aid of two well-known objective QoE metrics, as well as the measure of the network overhead. The results showed that the proposed mechanism outperformed all its competitors in both video quality improvement and network overhead decrement.