# A Novel Cloud Approach for Connected Vehicles
## 5 Evaluation
### Simulation Results
#### 5.1.3 Data Freshness Simulation Results  
The data freshness is measured as the percentage of vehicles which receives the data before the latter expires. The data expire when updated data have been generated. In our environment, the data frequency (\(\sigma\)) fixes the validity duration. We will compare the behavior of each approach by varying some parameters associated with the vehicles (number and range), the RSUs (number and range), and the data (frequency). Because the analytic model is pessimistic about the data freshness associated with GeoVCDN, the simulation will always give better results. The gap between the two results will be higher if there are more or fewer RSUs because the analytic model does not take into account the dissemination to the segments without RSUs. On one hand, the communication range of the vehicles has no effect on the approach that does not handle the V2V exchanges, as we can see in Figure 24. However, for the GeoVCDN approach, where the vehicle's transmission range is high enough to communicate with the surrounding vehicles, the freshness increases until it quickly reaches 100%, if the hop limit allows it. For example, with a range of 150 m, with GeoVCDN, we reach a \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Approach** & **Expected Value** & **Observed Value** & **Difference** \\ \hline NDN & 2,278,400 & 2,338,049.13 & \(+\)2.6\% \\ RENE & 17,554.36 & 17,281,2667 & \(-\)1.55\% \\ VCDN & 164,315.36 & 160,374.2 & \(-\)2.39\% \\ VCDNoCAM & 9684.26 & 9462.53 & \(-\)2.28\% \\ GeoVCDN & 28,900.20 & 28,399.6 & \(-\)1.73\% \\ \hline \hline \end{tabular}
\end{table} 
Table 14: Network Overhead Comparison for Data Update Frequency. Figure 23: Data Update Frequency. freshness of 100% compared to 60% with the other approaches. With a range lower than the inter-distance, we still do better than the other approaches with almost 16% more vehicles receiving the data, thanks to the bidirectional traffic. The more we increase the range, the more we optimize the broadcast from client to client; finally reaching the optimum freshness if the other parameters allow it. Table 15 presents a comparison between the expected values and the observed values for a vehicle range of 150 m.  
The differences between the obtained values with the model and with the simulations are small (max three points). As shown in Figure 25, where \(\beta=8\), increasing the number of vehicles does not have any effect on the approaches that do not handle the V2V exchanges. As expected, the percentage of vehicles in the coverage area and entering the coverage area before the expiration of the data remains the same, since the vehicle distribution is homogeneous and their speed is constant, so the freshness is also constant. Because the freshness is expressed as a percentage, the absolute amount of vehicles has importance only for the GeoVCDN approach. With this one, the increase in the number of vehicles has a positive effect on the freshness because we optimize our transmission range and our farthest neighbor is located farther away, so we cover a bigger area. Let us note that the freshness is limited by other settings such as the hop limit. With 170 vehicles, the GeoVCDN approach sees its freshness 50 points above the others. With 1000 vehicles, the performance is even better with 99% of the vehicles which obtain the information before it expires against 40% with the other approaches. The performance increase is logarithmically evolving according to the inter-vehicle distance. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Approach** & **Expected Value** & **Observed Value** & **Difference** \\ \hline NDN & 64.13\% & 64\% & \(-\)0.13 pt \\ RENE & 62.50\% & 63\% & +0.5 pt \\ VCDN & 64.13\% & 64\% & \(-\)0.13 pt \\ VCDNoCAM & 64.13\% & 64\% & \(-\)0.13 pt \\ GeoVCDN & 95\% & 98\% & +3 pt \\ \hline \hline \end{tabular}
\end{table} 
Table 15: Data Freshness Comparison for Vehicles’ Range. Figure 24: Vehicles’ Range.