# Video Streaming in Urban Vehicular Environments: Junction-Aware Multipath Approach
## 2 Related Literature
### Junction-Oriented Vehicle Selection  
In this subsection, the existing solutions that consider road junctions during video data forwarding are discussed. In the multipath setup, very few research studies have considered the realistic nature of VANET roads; for example, in [34; 35]. The intersections and junctions of roads need to be considered to select vehicles for multipath transmission. The incorporation of junctions/intersection into multipath transmission offers more realistic and efficient and higher- quality video streaming. Thus, in [PERSON] et al. [34], an analytical Junction-Centric Multipath Source Routing mechanism (JMSR) has been suggested. JMSR features include junction-aware logics, the multipath route from the source to destination and the source routing scheme. The JMSR employs geographic routing protocols, meaning that the locations of the junctions of a street are leveraged through the street's digital maps for data forwarding purposes. In the multipath setup, two paths are preserved concurrently considering the numerous junctions which a routed data packet has to traverse before reaching its destination. In addition, the JMSR embeds routing details into an individual packet, based on the source routing standard. The source routing standard is set-up in such a way that every individual vehicle in the path knows the route the packet must traverse. However, in JMSR, all vehicles are partitioned or grouped into different routes of paths, and then the cost of each path is calculated before being selected as the path for data forwarding. This approach is prone to high overhead and delay, which is a critical issue in video streaming requirements. In addition, the JMSR updates the information about the position of other vehicles when the position of the destination vehicle changes. Since it is believed that vehicles are moving very quickly, there is a frequent change of position; thus, it is important to consider the different points of the junction area and the direction of the vehicle at the junction. The different points of the junctions that have not been considered include the vehicle after the junction, before the junction, and inside the junction. The vehicle position, road-ID and traffic status can be employed to estimate whether a vehicle has exited the junction and has taken a direction towards the destination vehicle. Thus, video packet loss can be minimized since the most optimal vehicle is considered as a forwarder at the junction area. In Salkuyeh and Abolhassani Salkuyeh and [PERSON] (2018), an adaptive multipath video streaming method based on geographic routing has been suggested. The adaptive scheme selects multiple paths, depending on the volume and lifetime of the video to be transmitted from the source to destination. The route connection probability has been employed to select the best route. The connection probabilities are divided into two, namely street and junction connection probability, based on the cells and line of sight of the vehicles, respectively. However, the probabilistic connectivity approach does not consider the position and direction of the vehicle for connectivity. In addition, priority is not given to a vehicle that has already exited the junction and which is in the direction of the destination vehicle. This may lead to the selection of an inappropriate next forwarding vehicle in the junction, which can cause packet loss and affect the quality of the video streaming. [PERSON] et al. [PERSON] et al. (2018) suggested a distributed beaconless routing protocol for pre-recorded video data transmission (DBD) over VANETs. It is an integrated framework that handles the QoE of video services and routing protocols. DBD further advances the performance of the IEEE 802.11p/WAVE MAC layer by resolving the spurious forwarding problem. However, an adaptive backbone mechanism is not considered for the DBD. An opportunistic routing solution for pre-recorded video (ORV) streaming is proposed to handle the interference of wireless fading channels Salkuyeh and Abolhassani (2018).