## 4 Results
### Network Model Analysis
For each configuration (topology and number of sources) we run experiments of \(T\) time units, where \(T=100\). Then, we updated the accumulated exposure induced by each node according to the number of flows traversing it and recalculated the route. This way, if a node is selected in one route during the entire experiment, its accumulated exposure would reach a value of \(\epsilon\cdot T\). On the other hand, the cost associated to the transmitted power is assumed to be proportional to the distance between the two nodes in the corresponding link. For each configuration we run 100 independent experiments of \(T\) time units to get statistically tight results. We assign the cost values as follows: we increase from 0 to 15 the cost associated with the transmission power (the longer the distance, the higher power would be required to send packets over the link). Based on that particular range of values, we establish \(\mathcal{K}\) to be increased by 5 units for each flow forwarded by the node during a time slot. Besides, we do not give a higher priority to any of the two costs, i.e., accumulated exposure or instantaneous transmit power, with respect to one another. Although the costs selection is arbitrary, it will permit us to validate the performance of the _EMFaware_ algorithm when compared to legacy ones, and to analyze its behavior. First, we studied the accumulated exposure at the different nodes during one experiment. Figure 7 shows the exposure PDF by considering all nodes for both algorithms and by using the \(TP_{1}\) topology, with both two and four sources. We can argue that the value \(\epsilon\cdot T\) corresponds to the exposure accumulated by a single node, if it had been active for one path during the whole experiment (duration \(T\)). Hence, a multiple of \(\epsilon\cdot T\) would reflect nodes that were active in more than one route. For instance, if the PDF at \(2\cdot\epsilon\cdot T\) equals 0.1, that would imply that 10% of the nodes have been active in two routes during the whole experiment. This can be easily seen for the legacy shortest path (minimum power algorithm), which shows a discrete behavior. Indeed, the PDF is greater than 0 only in points multiple of \(\epsilon\cdot T\), reflecting that the routes are kept static during the whole experiment, not changing due to the high accumulated exposure. On the other hand, the proposed _EMFaware_ algorithm is able to balance the exposure. In particular, we can observe a relevant decrease on the PDF for \(\epsilon\cdot T\), which is around 30% and 20% for the two and four sources scenarios, respectively. This reduction is reflected on the smaller bins, as can be seen for values within the interval \([0,\epsilon\cdot T]\), which were not observed for the legacy routing solution. \begin{table}
\begin{tabular}{l c c c c} \hline \hline  & \multicolumn{4}{c}{**Topology**} \\ \hline  & \(\mathbf{TP_{1}}\) & \(\mathbf{TP_{2}}\) & \(\mathbf{TP_{3}}\) & \(\mathbf{TP_{4}}\) \\ \hline Sources & \(\{2,4\}\) & \(\{2,4\}\) & \(\{2,4,6,8\}\) & \(\{2,4,6,8\}\) \\ \hline Area m\({}^{2}\) & \(120\times 120\) & \(130\times 130\) & \(140\times 140\) & \(150\times 150\) \\ \hline PDF of reachable gateways & \(\bullet\) & \(\bullet\) & \(\bullet\) & \(\bullet\) & \(\bullet\) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Configuration of the static topology. After validating that the _EMFaware_ algorithm is actually able to modulate the accumulated exposure, the analysis is broadened to consider different topologies and traffic loads. In this context, Figure 8 shows the average value of the exposure, after 100 independent experiments, for different network deployments, considering various source nodes. The bars correspond to the values observed for the legacy shortest path minimum power solution, while the horizontal line represents the results brought by the proposed _EMFaware_ solution. As can be seen, the degree of improvement for our novel algorithm reduces as long as we decrease the node density.