# A Geographical Heuristic Routing Protocol for VANETs
## 5 Performance Evaluation
### Evaluation of the Recovery Phase in GHR  
In this section, we evaluate the performance of the recovery factor \(\beta\). This factor allows the routing protocol to forward a packet to a node farther from the destination than the current node instead of keeping the packet in the buffer until a better next forwarding node appears. For this evaluation, we consider only the forwarding techniques best neighbor (\(\alpha\rightarrow\infty\)) and the simulated annealing forwarding (\(\alpha=3\)), both with Tabu routing enabled. The reason for using only these two strategies in the tests of the recovery phase is that SA forwarding has the lowest percentage of packet losses in the three densities of vehicles, and the selection based on the best neighbor is the classical approach in geographical routing. Moreover, the other two techniques, i.e., random forwarding (\(\alpha=0\)) and first legal neighbor, behave similarly to the best node selection. They do not outperform the criterion of the best node in terms of packet losses and delay. For this part of our study, we work with three factors that could affect the performance of the recovery phase of GHR. These factors are:  
1. The vehicle density of the scenario (\(VD\)). 2. The forwarding technique (\(FT\)). 3. The recovery technique (\(RT\)), which depends on the \(\beta\) factor. We consider three different values for \(\beta\). They are: \(\beta\rightarrow\infty\), which is the default carry and forwarding approach; \(\beta=3\) to use a recovery SA; and \(\beta=0\), which always selects a next forwarding node if the current node has some legal neighbor. We do not evaluate the use of the recovery factor \(\beta\) for the forwarding techniques without Tabu because the packet losses increase significantly for those cases, as can be seen in Figure 5 for the forwarding technique based on the selection of the best neighbor (\(\alpha\rightarrow\infty\)). The values of \(\beta=3\) or \(\beta=0\) perform poorly because the recovery mechanism creates loops without Tabu. The recovery mechanism selects in most of the cases the previous neighbor that forwarded the packet to the current node. This creates loops, and nodes cannot avoid those nodes because they do not have a track of the previous path followed by the packet. Figure 5: Percentage of packet losses for different values of the recovery factor \(\beta\), using the best node criterion at the forwarding phase without Tabu. We have to analyze the results for each density separately because there is a significant three-way interaction \(RT\times FT\times VD\) (Step 1) with a \(p\)-value = 0.0001 ([PERSON]'s \(\Lambda\) = 3.41 and F (16,100) = 4.47). Table 5 shows the results of the further interaction test between the \(FT\) and \(RT\) for GHR protocol (Step 1). We can see that for the medium and the high density scenarios, the \"all together\" tests have a \(p\)-value under the threshold, so an independent interaction test per metric needs to be performed in those cases. The \(p\)-value \(<\) 0.05 in the interaction tests for each metric indicates that the seeking of performance differences in the recovery technique should be done for each forwarding technique (i.e., best neighbor and SA forwarding) separately. The test results to determine if there are differences in the performance metrics, according to Step 2 of the statistical procedure, are shown in Table 6. All of the \(p\)-values in this table are lower than 0.05, excluding the percentage of packet losses in the high density scenario (250 vehicles) for the forwarding factor \(\alpha\rightarrow\infty\) (select the best neighbor). Hence, the use of different values for the recovery factor \(\beta\) produces a statistical significant change among them in all performance metrics, and therefore, they require pairwise comparisons to analyze the differences.