# A Bandwidth-Efficient Dissemination Scheme of Non-Safety Information in Urban VANETs +
## 4 Parameter Tuning and Evaluation through Simulations
### Results  
#### 4.3.1 Parameters for Broadcast Suppression  
According to the descriptions in Section 3.1, there are three key parameters: \(T_{max}\), \(T_{j}\) and \(\Delta\alpha\). \(T_{max}\) is the maximum per-hop delay for a vehicle that is not located at a junction. This parameter is important because it helps to prevent situations in which several vehicles try to forward almost simultaneously. In addition, it has to be small enough to consider the scenario almost static during the contention. The same value should work properly in very different traffic situations. Furthermore, it directly affects the latency of the scheme. \(T_{j}\) is the maximum wait for vehicles at junctions. It must be less than or equal to \(T_{max}\), and it affects the performance in a similar way. \(\Delta\alpha\) is the difference between \(\alpha_{max}\) and \(\alpha_{min}\). It defines what is considered a junction, given that a vehicle determines its position at one by comparing the reception angle with these two thresholds. As explained above, the reception angle is calculated by using the relay's reported location and the receiver knowledge of its own trajectory. From the descriptions above, the reader can note that the base roadway scheme only depends on \(T_{max}\); the map-based scheme depends on \(T_{max}\) and \(T_{j}\); and the angle-based scheme depends on the three parameters. Hence, to isolate their effects, the first step will be to tune \(T_{max}\) with simulations of the roadway scheme. Then, we will fix the resulting value for the map-based scheme to find out \(T_{j}\). Last, we will configure the angle-based scheme with those values and make a sweep of \(\Delta\alpha\). It did not make sense to try to adjust \(d_{j}\) by simulations because it is highly dependent on the given city, and we would only overfit it to our scenario. Instead, we have studied the widest diagonal at junctions from a set of four different city maps: New York (USA), Madrid (Spain), Rome (Italy) and Cologne (Germany), available via OpenStreetMap. The results are shown in Table 3. The median, the most usual value, was, respectively, 9.89 m, 9.24 m, 9.64 m and 9.61 m. Accordingly, we have set \(d_{j}=10\) m.  
The results of the simulations to find the best \(T_{max}\) using the base roadway scheme are shown in Figure 3. We show the 95% confidence interval together with the values represented in these graphs and the rest that follow. The first thing we notice is that the long-reach success (Figure 3a) and the coverage (Figure 3b) remain constant for every traffic density considered in our study. Apart from that, we can see that the redundancy ratio in Figure 3c descends when the maximum wait is longer. The reason is that, when the wait is short, there is a high probability that several vehicles will pass the message to the MAC layer almost simultaneously. This leads to the high number of lost packets that we see in Figure 3d for values of \(T_{max}\) under 350 ms. Regarding the average per-hop delay (Figure 3e) and the end-to-end delay (Figure 3f), they are proportional to \(T_{max}\), as expected. Given that this parameter does not affect the success, we search for a good trade-off between overhead and latency. The former is improved \begin{table}
\begin{tabular}{c c c c} \hline
**City** & **Minimum** & **Median** & **Maximum** \\ \hline New York & 2.34 m & 9.89 m & 49.69 m \\ Madrid & 2.56 m & 9.24 m & 45.09 m \\ Rome & 2.29 m & 9.64 m & 81.62 m \\ Cologne & 2.31 m & 9.61 m & 77.80 m \\ \hline \end{tabular}
\end{table} 
Table 3: Statistics of the widest diagonal at junctions in several cities. when the value is greater than or equal to \(350\,\mathrm{ms}\), while the latency worsens as the value gets higher. Therefore, we choose \(T_{max}=$350\,\mathrm{ms}$\). This is a rather large value when compared to our chosen value for the roadway scenario, \(T_{max}=$18\,\mathrm{ms}$\). The reason is that the broadcast storm problem is very pronounced in urban areas, as pointed out in [2].