## 4 Simulation Results  
### Simulation Scenario  
We analyzed the performance of our multimetric algorithm MMMR and compared it to AODV [19], GPSR [6], I-GPSR [11] and GBSR-B [20]. To do this, we carried out several simulations using the NCTUns 6.0 (National Chiao Tung University network simulator) [21]. We used the NCTUns simulator due to the fact that it allows for a simple and accurate way of designing VANET scenarios [22]. It is possible to use our own mobility model, including walls to attenuate the signal, among others.  
GBSR-B is our previous proposal that improves GPSR with its map-aware capability and a buffer scheme to be used instead of the perimeter mode of GPSR, as was explained in Section 3.2. GBSR-B only uses the distance as the metric to make forwarding decisions.  
We used a grid scenario to model a common urban scenario formed by streets and crossroads. Seeking to simulate a realistic scenario, we used Citymob [23] to generate the movements of vehicles that follow streets and respect the presence of other vehicles and traffic lights. We use in the scenarios blocks (orange lines) that work as buildings. These walls are set with the total block of the signal, and the simulation process of attenuation is detailed in [24]. The simulation area was 1,500 m \(\times\) 1,500 m. Each street was 100 m-long, with intersections of 40 m (see Figure 3) according to the area of the example in Barcelona, Spain. We considered two densities of vehicles (60 and 120 vehicles), which were randomly positioned. The maximum average speed of the vehicles was 50 km/h. There was one fixed destination, the access point (henceforth, called AP; see Figure 3), through which vehicles connect to the network to report traffic information. We use a fixed AP position in the border of the scenario, because in this way, we obtained different route lengths, depending on the position of the cars in the scenario. Half of the nodes sent 1,000-byte packets every 2 s to the unique destination for 1,000 s. The traffic profile is CBR (Constant Bit Rate) 4 Kbps per source. There is an interfeThe simulations were carried out using the IEEE 802.11 p standard on physical and MAC layers. The latter was simulated with only the best effort (BE) access category. Furthermore, we use the two-ray ground as the radio propagation model joint to the Rician fading model. We set an average transmission range of 250 m, which is a typical parameter in vehicular environments. All the figures are presented with confidence intervals (CI) of 95% obtained from five simulations per point. Table 4 summarizes the main simulation settings.  
\begin{table}
\begin{tabular}{l c} \hline \hline
**Parameter** & **Value** \\ \hline Simulation area & 1,500 m \(\times\) 1,500 m \\ Number of nodes & 60 and 120 vehicles \\ Maximum node speed & 50 km/h \\ Transmission range & 250 m \\ Sensing range & 300 m \\ Mobility model & Double-Manhattan \\ Downtown area & 700 \(\times\) 700 m \\ Mobility generator & Citymob \\ MAC specification & IEEE 802.11p \\ QoS access category & BE (best effort) \\ Bandwidth & 12 Mbps \\ Simulation time & 1,000 s \\ Maximum packet size & 1,000 bytes \\ Traffic profile & CBR 4 Kbps \\ Routing protocol & AODV, GPSR, GBSR-B, I-GPSR, MMMR \\ \hline \hline \end{tabular}
\end{table}
Table 4: The main simulation settings used in the evaluation scenarios.  
Figure 3: Dimensions of the streets in the urban scenario used in the evaluations and localization of the access point (AP; destination).