# Proposal of an Automated Mission Manager for Cooperative Autonomous Underwater Vehicles
## 6 Results
### Processing Environmental Reports  
The vehicles are set to send periodically environmental reports, known as state vectors, which always have the same size. Table 7 collects the total time used for processing the state vectors for each mission. Each row includes the mission number, the total number of reports received during the mission (#_Rpts_), the total number of reports that included salinity information (#_Rpts_all_), the total time spent for storing the state vector in the relation database (\(t_{sto_{\text{all}}}\)) and in the ontology (\(t_{sto_{\text{out}}}\)), the total time for storing the salinity information in the ontology (\(t_{sto_{\text{all}}}\)) and the total time used for other activities not relevant to the processing of the report (\(t_{other}\)). There were no records regarding the processing of environmental reports during mission 27. \begin{table}
\begin{tabular}{c c c} \hline
**Activity** & **Average Time (ms)** & **Contribution (\%)** \\ \hline Getting vehicle info & 5.26 & 39.39 \\ Storing task status in database & 1.21 & 9.09 \\ Sending task status to MMT & 0.28 & 2.13 \\ Assigning next action & 6.50 & 48.69 \\ Other activities & 0.09 & 0.70 \\ TOTAL AVERAGE TIME & 13.35 & 100.00 \\ \hline \end{tabular}
\end{table} 
Table 6: Average times for processing the task status reports. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline _Mission_ & **\#Rpts** & **\#Rpts\_salt** & \(t_{sto_{\text{all}}}\) & \(t_{sto_{\text{out}}}\) & \(t_{sto_{\text{all}}}\) & \(t_  
The distribution of the time required for processing the state vectors is also shown in Figure 34. It is clearly seen that for every mission the most contributing part was the storage of the state vector in the ontology, followed by the storage of the salinity information also in the ontology whenever this information was available. The averages for the storage of the state vector in the relational database and in the ontology, as well as for the other activities not relevant to the processing of the report, are calculated using the total number of reports registered for each mission. The averages for storing the salinity information in the ontology are calculated using the number of reports that included salinity information. The Pareto chart shown in Figure 35 illustrates how each part done for processing the state vector contributes to the total time required. As was clearly seen in the distribution of time from Figure 34, the part of the processing time that contributes the most is the storage of the state vector in the ontology, followed by the time required for storing the salinity information in the ontology whenever this information was available. Other activities performed for processing the state vector made negligible contributions to the total. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline _Mission_ & _\#Rpts_ & _\#Rpts\({}_{salt}\)_ & _tsto\({}_{sh}\)_ & _tsto\({}_{ant}\)_ & _tsto\({}_{salt}\)_ & _tother_ & _ttotal_ \\ \hline
32 & 14 & 0 & 137 & 810 & – & 9 & 956 \\
33 & 110 & 0 & 1040 & 5278 & – & 64 & 6382 \\
34 & 155 & 0 & 1513 & 7225 & – & 59 & 8797 \\
35 & 127 & 0 & 1192 & 6132 & – & 66 & 7390 \\
36 & 443 & 43 & 4102 & 20,727 & 1194 & 211 & 26,234 \\
37 & 53 & 0 & 471 & 3663 & – & 36 & 4170 \\
38 & 336 & 22 & 3359 & 17,326 & 617 & 189 & 21,491 \\
39 & 228 & 8 & 2242 & 10,762 & 219 & 107 & 13,330 \\
40 & 7 & 0 & 75 & 438 & – & 5 & 518 \\
41 & 45 & 0 & 404 & 2828 & – & 21 & 3253 \\
42 & 96 & 0 & 961 & 4807 & – & 57 & 5825 \\
43 & 160 & 5 & 1473 & 9557 & 129 & 57 & 11,216 \\
44 & 56 & 0 & 575 & 2955 & – & 21 & 3551 \\
45 & 163 & 2 & 1563 & 8174 & 50 & 99 & 9886 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: _Cont_. Figure 34: Distribution of times required for processing the state vectors. As mentioned before, the part contributing most was the storage of the state vector in the ontology, requiring an average of 55.34% of the average total time. The storage of the salinity information in the ontology follows with 33.85%.