# Context-Aware Data Dissemination for ICN-Based Vehicular Ad Hoc Networks
## 4 Test and Evaluation of the Results
### Evaluation Results
This is because, when there are fewer vehicles on the road, the participation in forwarding by vehicles outside the suppression angle can increase the possibility of finding the location of vehicles holding the requested content and, similarly, the Data packet can be returned quickly to the requestor. Note that although GPSR has the shortest data response time due to its distance greedy forwarding algorithm, the packet loss rate is higher, and the successful data delivery ratio is lower than other methods. Figure 17 illustrates the average number of hops traversed by the Data packets. Compared with Basic-NDN and V-NDN, the hops using CA-VNDN are relatively stable. When the number of vehicles is between 400 and 1000, the difference between the number of hops by using CA-VNDN and by using Basic-NDN is negligible. This also shows that the reverse-path routing realized by CA-VNDN can reduce the hops of Data packets compared with V-NDN. Although the number of hops by using GPSR is the least, as is the data response time, when used in VANET the successful data delivery ratio and packet loss rate are worse due to the rapid movement of vehicles. Figure 17: Hops of Data packets vs. the number of nodes and suppression angle. Figure 18 shows the optimal suppression angle calculated according to Equation (4). We can see that the suppression angle increases with the increase of the density of vehicles. The optimal suppression angles are also in accordance with the results shown in Figure 15, in other words, by using the optimal suppression angle, the best performance can be achieved. To test the influence of the content requesting interval and the simulation time on the performance, we extended the simulation time to 5 min, changed the sending interval of Interest packets to 0.2 s and compared the successful content delivery ratio. As shown in Figure 19, we listed the value of the successful delivery ratio when the simulation time is 60 s and the sending interval is 0.1 s and when the simulation time is 5 min and the sending interval is 0.1 s and 0.2 s, respectively. From the figure, we can see that the difference among the values is not big. The average of the standard deviation of the three curves is 0.012781. To test the influence of content priority on the performance of data delivery, we configured the priority of different types of information (i.e., data content) randomly assigned to data objects, and measure the packet loss rate, minimum, and maximum response time. Table 2 lists the different content categories and their associated priorities (lower priority number indicates higher priority). From Figure 20 we can see that with the decrease of the priorities of the content, the performance in terms of successful data delivery ratio, packet loss rate, minimum, and maximum response time also decreases. This means that our packet-forwarding mechanism can also control the performance of data delivery by setting the priorities of the content. Figure 19: Successful delivery ratio under different simulation time and content sending interval. Figure 18: Optimal suppression angle varying with the number of vehicular nodes. From the results, we can see that the CA-VNDN mechanism proposed in the paper has greatly reduced the total number of packets transmitted in the network and, therefore, reduced the network bandwidth and packet loss rate. At the same time, the CA-VNDN mechanism can also provide a high ratio for the successful delivery of the requested data.