# Video Streaming in Urban Vehicular Environments: Junction-Aware Multipath Approach
## 4 Performance Evaluation  
In this section, the simulation setup results obtained and the performance evaluation with analysis against the baseline schemes are presented. The performance is evaluated considering two different  
Figure 3: Flowchart for vehicle selection considering the junction area. C-NFV: Candidate Next Forwarding Vehicle; SINR: signal to interference plus noise ratio; DVN: Destination Vehicle Node. cases. each based on vehicle density and video data rates. The evaluation is conducted by considering metrics including the Packet Loss Rate (PLR), Structural Similarity Index (SSIM) and End-to-End Delay (E2 ED). The PLR is the ratio of a transmitted video packet to that of the delivered packet. This also helps in ascertaining the quality of the video transmitted, because the lower the number of video packets dropped, the higher the number of video packets delivered at the destination vehicle, which in turn leads to higher video quality [40]; conversely, the higher the number of video packets dropped during transmission, the lower the number of received video packets at the destination vehicle, which leads to lower video quality. The SSIM is computed as the perceived similarity between the transmitted video images and the original video images. The calculation of the SSIM index is grouped into three aspects: contrast, luminance, and structural assessment [41; 42; 43]. The E2 ED is the total summation of the delay encountered from the source vehicle to the destination vehicle. The delay includes the propagation delay, transmitting delay, processing delay and startup delay [44; 45]. The level of E2 ED delay also signifies the quality of the video delivered at the destination vehicle. The metrics are tested in relation to different vehicle densities and data rates (kbps). The distribution of the vehicle density is from 50 to 500, and the video data rate considered ranges from 160 kbps to 1600 kbps. The three metrics are utilized considering the different vehicle densities and data rates. Particularly, a high data rate and high vehicle density have been considered. The discussion of the results of the proposed scheme is presented in Section 4. The baseline schemes employed for the benchmarking of the proposed scheme include Junction-Based Multipath Source Routing (JMSR) [34] and Adaptive Multipath geographic routing for Video Transmission (AMVT) in urban VANETs [35]. The simulation of the junction-aware scheme is guaranteed since the whole map of the simulation environment, including roads and junctions, has been integrated using the OSM and integrated into the Simulator of Urban Mobility (SUMO). The vehicles know their positions due to location information service. The proposed JA-MVS is implemented using the most acceptable network simulators: NS-2.34 and SUMO. The NS-2 is a network simulator that enables the simulation of network communication. The SUMO employs the mobility model generator for VANETs (MOVE). It has the ability to create a realistic model for the mobility of vehicles in urban traffic scenario. The Evalvid has been employed to provide video frames and a video quality evaluation framework. The Manhattan city digital map with a latitude of 39.191 to 39.184 and longitude of -96.574 to -96.563 is employed for the mobility and traffic environment setup (see Figure 4). The digital map structure and data are acquired from the OpenStreetMap contributors. The details of the simulation parameters are depicted in Table 1, which include the urban simulation area, simulation time, vehicle speed, number of vehicles, the MAC protocol, video resolution, video play duration, the transmission range, frequency bandwidth, propagation model, antenna model, traffic type, channel type, transmission protocol, hello packet timeout and scenarios. Figure 4: Manhattan city map.