Vehicular ad hoc networks play an important role in the efficiency of road traffic by improving safety and acting as a facilitator of services for passengers, drivers, and public safety officers. Recent improvements in the routing protocols and topologies used in vehicular networks have contributed to improvements in scalability, reliability, and the quality of the information-sharing experience. Vehicles can cooperate with each other to stream videos of accidents or disasters and provide visual information of the monitored area with great precision. This article proposes a collaborative routing protocol for video streaming vehicular ad hoc networks using the service of fog storage to minimize the sharing of content. The routing table is based on an indicator that is generated by combining the speed, location, and recording angle parameters of each vehicle involved in vehicular collaboration to reduce the unnecessary exchange of video data in vehicleto-vehicle communications. The results of the simulations show that the proposed model performs favorably when compared with other routing protocols with respect to the availability of end-to-end communication.

Currently, the Internet is experiencing a revolution in the provisioning and demand of multimedia services. In this context, 3D-video is envisioned to attract more and more the multimedia market with the perspective for enhanced applications (video surveillance, mission critical control, entertainment, etc.). However, 3D-video content delivery places increased bandwidth demands, as well as have rigorous Quality of Service (QoS) and Quality of Experience (QoE) requirements for efficient support. This paper proposes a novel QoE-aware packet controller mechanism, which aims at connecting real-time 3D-video streaming applications over congested wireless networks with acceptable levels of QoS and QoE over the time. Simulation experiments were carried out to show the impact and benefit of our proposal. Subjective and objective QoE metrics were used for benchmarking, showing that in congestion periods our solution improves the quality level of real-time 3D-video sequences from the user point-of-view, as well as, optimizes the usage of wireless network resources.