## 5 Dynamic Optimization of the Crowdsourcing Platform
### Dynamic Optimization Engine Based on Metric Indices
We chose the Centralized routing algorithm as the fixed value for the routing algorithm (ALG) parameter as it strikes a balance between the Baseline and the Distributed routing algorithms. This means it leverages the available computing and network resources in the P2P network while avoiding overloading the peers with the consensus calculation. Furthermore, the following experiments (Figures 8 and 9) as well as prior research [13] comparing the performance of these three algorithms shows that the Centralized approach generally reports better results. We set \(C=40\%\) to achieve a minimum consensus of 40%, and \(H=50\). Increasing these values also increases the computational costs, while reducing them may lead to a decrease in the quality of volunteers' votes. Finally, we set \begin{table}
\begin{tabular}{c c c} \hline \hline
**Params** & **Fixed Value** & **Range of Possible Values** \\ \hline ALG & Centralized & Baseline/Centralized/Distributed \\ \hline C & 40\% & 10–90\% \\ \hline H & 50 & 10–100 \\ \hline TTL & 24 h & 2–72 h \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Fixed values of the parameter used while varying the value of a specific parameter and the range of possible values for each parameter. the \(TTL=24\) h to avoid prematurely dropping tasks, while considering that a 24 h wait is sufficient for disaster scenarios [13; 50]. Table 2 shows the mean and standard deviation (std) reported by the Index, the IndexLimit, and the IndexF algorithms for the consensus (Cons. ); the processing time of the platform (workT); and the ISP utilization (ISP_Util). We processed a total of \(nQ=10\),000 images. By controlling only the \(H\) parameter, the index-based algorithms achieve a consensus greater than 99%. If we only control the voting threshold C the algorithms achieve consensus values between 49% and 52%, the routing algorithm (ALG) allows us to obtain consensus between 39% and 48% when individually manipulated, and the \(TTL\) allows us to achieve consensus values between 35% and 39%. Regarding the processing time (workT), by controlling the \(H\) parameter, the algorithms report values between 109 and 125 h, controlling the parameter C reports a workT between 228 and 230 h, the \(TTL\) is between 194 and 213 h, and the routing algorithm ALG is between 228 and 231 h. Finally, controlling the \(H\) parameter individually allows us to achieve ISP average utilization values between 47% and 48%, the ALG is between 34% and 42%, the \(TTL\) is between 58% and 62%, and the voting threshold \(C\) is between 57% and 58%. When controlling different combinations of parameters, including all of them together (All), the highest percentage of consensus is 0.998, which is achieved by combining \(H\) and the routing algorithm ALG using the \(IndexF\) approach. However, similar results are obtained with the other metric-indexed approaches and when using the \(H\) parameter or any combinations including \(H\). Thus, the \(H\) parameter drastically impacts the percentage of consensus. On the other hand, the lower processing time, 99.167,is reported by the \(indexF\) approach with the ALG-\(H\)-\(TTL\) combination of controllable parameters. In this case, the consensus reported is 0.994. However, the ISP utilization is higher than 60%. On the other hand, the Index approach with the same controllable parameter configuration manages to keep the average utilization of the ISP network close the limit of 40%, and the processing of the tasks is completed in approximately 102 h. Finally, when all parameters are controlled at the same time, the \(Index\) approach returns a high consensus value of 0.964, a total processing time of 108 h, and the average ISP utilization is 53%. The \(IndexF\) approach reports a consensus of 0.96, the processing time is 134 h, and the ISP utilization is 34%. The \(IndexLimit\) achieves a consensus of 0.987, a processing time of 123 h, and the ISP utilization is 42%.