## 3 A Corpus for Routing Evaluation in OppNets
### Corpus Creation Methodology  
This section presents the corpus creation methodology depicted in Figure 3. The corpus creation methodology has five well-delimited stages, each with specific inputs, outputs and tasks. The input information of one stage is the output of the previous one, except for the first stage, which does not have an earlier stage.  
The first stage, characteristics selection, decides those characteristics that describe a scenario. The selected seventeen characteristics are displayed in Table 1. A Pearson correlation [59] study of the selected characteristics was performed as shown in Figure 4. Some characteristics have a high correlation because they are based on connections and interaction between nodes. However, despite the redundancy and the high correlation, the characteristics reflect essential connectivity behaviors of the scenarios. This is why these highly correlated characteristics remain within the selected characteristics.  
Figure 4 made it clear that some characteristics were highly correlated. At first glance, one way to deal with highly correlated characteristics is by removing them. However, removing characteristics that describe scenarios was considered a wrong approach because fewer scenario characteristics might hinder the scenario description accuracy. The high correlation helped us understand that selecting scenarios would not be straightforward and that it will require a backtracking process to achieve diversity and representativeness among scenarios in the corpus. The backtracking process uses additional information about the characteristics. Specifically, the variance of the characteristics was used in the case there is a need to achieve representativeness and diversity objectives.  
The second stage, creation of scenarios, received the characteristics found in stage one and then created scenarios for the given characteristics. This stage generated over 200,000 OppNet scenarios, many of which had similar behaviors and therefore similar vectors of characteristics. The scenarios with a similar vector of characteristics were considered equivalent.  
The third and fourth stages, scenario selection and enhanced distribution, were loop-connected. Each characteristic range was evenly divided into sub-ranges called windows. Then, a subset of scenarios was selected for each window, and this process sequentially looped through the list of characteristics. The number of scenarios was reduced because the  
Figure 4: Heatmap of Pearson correlation coefficients between scenarios’ characteristics. Only significant Pearson’s correlation coefficients are shown.  
scenarios should belong to all windows of the characteristics. If there was no scenario in the window, those empty-scenario windows were re-adjusted until scenarios were found.  
When all of the characteristics had been run through, and a representative number of scenarios had been obtained, stage four checked the diversity of the scenario collection. The loop was broken if the diversity of scenarios was fulfilled, which implies not having similar scenarios and that the distribution of characteristics manages to cover the entire range of each characteristic. Each scenario fulfills a part of the range of the characteristic. All scenarios, as a whole, complete the range of the characteristics.  
The final stage, publish corpus, made the corpus of OppNet scenarios available for the research community. This assures the usability set as a quality requirement shown in Section 3.4. The following section describes the corpus obtained following the corpus creation methodology presented in this section.