## 4 Proposed Method
### Coverage Hole Repair Based on Mobile Node Redeployment
#### 4.2.2 Calculate the Number of Mobile Sensors Required
We verified the effects of sensor quantity, sensing angle, and sensing radius on coverage in three monitoring areas of different sizes. When setting simulation experiment parameters, the variable is either the number of sensors, sensing angle, or sensing radius, while the other two are constants. The range of values for these three parameters is shown in Table 3.

As shown in Figure 6, when the number of sensors is small, the coverage of all four algorithms is low. When the density of sensors is low, not enough schedulable mobile sensors can be found, resulting in some coverage holes that cannot be repaired. With the increase in the number of sensors, the coverage rate of all four algorithms is greatly improved. Under the same conditions, our method outperforms the other three methods in terms of coverage rate. VB-IVFA, VF-IALO, and MEP-PSO only use mobile sensors for coverage enhancement without considering rotating sensors. Our method adds the step of rotating the sensor, so it has a certain advantage in terms of coverage rate. \begin{table}
\begin{tabular}{c c c c} \hline \hline  & \(\mathbf{n_{s}}\) & \(\mathbf{\kappa}\) (\({}^{*}\)) & \(\mathbf{r}\) (\(\mathbf{m}\)) \\ \hline Constant & 100 & 90 & 20 \\ Variable & [50, 300] & [60, 240] & [10, 40] \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Simulation parameter settings. Figure 7 shows the impact of the sensing angle on coverage. As the sensing angle increases, the coverage rate of the four algorithms also increases. The increase in sensor sensing angle means that the coverage range of the sensor also expands. When the number of sensors is the same, the coverage range is higher. The results of Figure 7 indicate that the coverage increases rapidly when the sensing angle increases from 60 degrees to 120 degrees. When the sensing angle continues to increase from 120 degrees, the improvement in coverage rate is not significant. Under the same conditions, our method has a higher coverage rate than the other three methods. From Figure 8, it can be seen that the sensing radius has an impact on coverage. Like the sensing angle, the sensing radius is positively correlated with the coverage rate. In experiments using the same sensing radius, the proposed method achieved a higher coverage rate than the three compared algorithms. The coverage rate of all algorithms increases with the increase in sensing radius. We compared the results of the proposed method with the theoretical CUB, which from another perspective demonstrates that the proposed method has good coverage performance. As shown in Figure 9, as the number of iterations increases, the coverage of our method tends to approach the CUB. With a sufficient number of sensors, our method can achieve the theoretical maximum value through multiple iterations. Figure 7: Comparison of coverage rate under various sensing angles: (**a**) ROI = 100 m \(\times\) 100 m, (**b**) ROI = 200 m \(\times\) 200 m, (**c**) ROI = 300 m \(\times\) 300 m.

The experimental results in this section indicate that the proposed method outperforms the other three methods in terms of coverage rate. The proposed method consists of two stages, each of which can improve the effective coverage range. Therefore, compared to the other three methods, it has a higher coverage rate. ### Comparison of Coverage Efficiency and Redundancy Rate

This experiment separately calculated the coverage efficiency of VB-IVFA, VF-IALO, MEP-PSO, and the proposed method. To avoid the influence of errors, we conducted multiple experiments in environments with different ROIs and node densities. The experimental results are shown in Table 4.