Shielding video streaming against packet losses over VANETs
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Vehicular ad-hoc networks (VANETs) are being widely adopted in the last few years. This type of network enables the utilization of a large diversity of distributed applications, such as road and traffic alerts, autonomous driving capabilities and video distribution. Video applications can be considered one of the most demanding services because it needs a steady and continuous flow of information. This presents a set of challenges to VANETs considering their scarce network resources due to the vehicle movement and time-varying wireless channels. Considering the above mentioned issues, an adaptive quality of experience (QoE)-driven mechanism is needed to provide live transmission capabilities to video-equipped vehicles. This mechanism has to overcome the challenges to grant a high-qua lity video transmission without adding any unnecessary network overhead. To this end, a forward error correction (FEC) technique can be adapted to enhance the video distribution, leading to higher QoE for end users. The proposed self-adaptive FEC-based mechanism (SHIELD) uses several video characteristics and specific VANETs details to safeguard real-time video streams against packet losses. One of the main contributions of this work is the combined used of network density, signal-to-noise ratio, packet loss rate, and the vehicle’s position. This allows SHIELD to better protect the video sequences and enhance the QoE. In doing that, we are able to improve the user experience, while saving network resources. The advantages and drawbacks of the proposed mechanism are demonstrated through extensive experiments and assessed with QoE metrics, proving that it outperforms both adaptive and non-adaptive mechanisms.
KeywordsVANETs Forward error correction (FEC) Unequal error protection (UEP) Fuzzy logic Quality of experience (QoE)
This work was funded by the Brazilian National Counsel of Technological and Scientific Development (CNPq), and also supported by the COST Action IC1303: AAPELE—Algorithms, Architectures and Platforms for Enhanced Living Environments and FCT Project, MIT-Portugal Program—SusCity: Urban data driven models for creative and resourceful urban transitions.
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