# A Bandwidth-Efficient Dissemination Scheme of Non-Safety Information in Urban VANETs +
## 4 Parameter Tuning and Evaluation through Simulations
### Results
#### 4.3.3 Comparative Evaluation of the Store-Carry-Forward Strategies
Fixed Interval Approach  
In Figures 10-12, we show the simulation results of applying store-carry-forward to the roadway dissemination scheme with this approach. From all of the tested values, we have selected for representation the three smaller ones (every 0.5, 5 and 10 s). First, we can see that the aspects we have discussed about the speed-adaptive interval are present in these results, as well. Therefore, we proceed to evaluate how the configured interval length affects the performance. If we look at Figure 10, we can see that changing the actual configured value does not have a significant impact on the delivery ratio. However, the number of duplicates observed in Figure 11 is clearly higher when the retransmissions due to store-carry-forward are more frequent. All this leads to the higher ratios of retransmissions per reached vehicle that we can see in Figure 10a,b when compared to the other two. Figure 10: Involved vehicles with the fixed interval approach for store-carry-forward in the New York scenario: (**a**) roadway scheme, 25 vehicles/km\({}^{2}\); (**b**) roadway scheme, 100 vehicles/km\({}^{2}\). Figure 9: Forwarding ratio or the relation between sent duplicates and receivers with the speed-adaptive approach for store-carry-forward in the New York scenario: (**a**) roadway scheme. (**b**) map-based scheme. Map Polling Approach  
We can see the simulation results for this strategy in Figures 13-15. The number of reached vehicles, as seen in Figure 13, is slightly lower when the polling period is longer. This is due to the consequent reduction in retransmissions, which we can verify in Figure 14. Additionally, we can see that the highest polling frequency causes a higher proportion of duplicates caused by store-carry-forwarding, up to a half of the duplicates. This contrasts with the results of the other two considered values, which are in the line of the two previous options. This is very clearly seen in Figure 15, where the line for a 0.5-s period rapidly rises above one retransmission per receiver, while the other two remain below during the first 450 s.  
Figure 11: Sent messages with the fixed interval approach for store-carry-forward in the New York scenario: (**a**) roadway scheme, 25 vehicles/km\({}^{2}\); (**b**) roadway scheme, 100 vehicles/km\({}^{2}\). Figure 12: Forwarding ratio or the relation between sent messages and receivers with the fixed interval approach for store-carry-forward in the New York scenario: (**a**) roadway scheme, 25 vehicles/km\({}^{2}\); (**b**) roadway scheme, 100 vehicles/km\({}^{2}\). Figure 14: Sent duplicates with the map polling approach for store-carry-forward in the New York scenario: (**a**) roadway scheme, 25 vehicles/km\({}^{2}\); (**b**) roadway scheme, 100 vehicles/km\({}^{2}\). Figure 15: Forwarding ratio or the relation between sent messages and receivers with the map polling approach for store-carry-forward in the New York scenario: (**a**) roadway scheme, 25 vehicles/km\({}^{2}\); (**b**) roadway scheme, 100 vehicles/km\({}^{2}\). Comprehensive Comparison  
We focus especially on the graphs in Figures 9, 12 and 15, so that we can compare the results from each approach easily. They offer a summary of the performance, as they relate the number of reached vehicles with the total number of duplicates. First, we have confirmed that, the lower the density, the worse the overhead. Store-carry-forwarding is needed more often, and hence, the number of duplicates increases. However, we have seen that the number of receivers still does not reach the same value as in a higher traffic density. The speed-adaptive strategy shows a good performance, keeping the ratio under one duplicate per receiver during the 450 s of the experiments. Map polling also offers very good results, as long as the interval is long enough. Checking the map every 5 s yields approximately the same outcome as the speed-adaptive approach. Doing the check every 10 s improves it slightly because the compromise between the number of reached nodes and duplicates is more balanced.