# Estimation and Healing of Coverage Hole in Hybrid Sensor Networks: A Simulation Approach
## 6 Performance Evaluation and Analysis  
In this section, we will conduct comparative simulations about our algorithm HCHA, the main simulation platform we used is Matlab. In order to make a remarkable contrast, we compare HCHA deployment with the random deployment, COVEN deployment in paper [17] and DT-Score deployment in paper [19]. The simulation area we choose is 100 m \(\times\) 100 m and sensing radius \(R_{s}\) is 5 m, \(\mu\) is 0.5, red nodes represent mobile sensors and blue represent static sensors. Because COVEN, DT-Score and HCHA have different abilities to be estimated, so we can only set some same parameters such as number of static sensors 50, as to the number of mobile sensors, it need to be calculate by COVEN and HCHA separately, which is not decide by manual setting, as well as DT-Score calculate the candidate positions. Coverage simulation results are demonstrated in Figures 8-16. Figures 8 and 10 are randomly deployment and HCHA deployment with 50 static sensors and 72 mobile sensors, which number is figured out by HCHA. Figure 9 is the COVEN deployment with 50 mobile sensors and 58 mobile sensors, which are figured out by COVEN. Figure 11 is the HCHA deployment after DT repaired with 50 static sensors and 88 mobile sensors, which number is calculated by HCHA after the DT paired, and the DT repaired aims to cover the area boundary. In Figure 10 we  
Figure 11: HCHA(Repair DT) deployment of 50 static sensors coupled with 88 mobile sensors. Figure 12: Obstacles. Figure 13: Obstacle coverage with DT-Score. In order to compare HCHA with DT-Score, we construct obstacles scenario as shown in Figure 12. For the same one obstacles exist scenario, Figure 13 shows the coverage with DT-Score, the blue point represent contour point and red represent candidate point, Figure 14 is the coverage with HCHA after DT repair. Figure 15 shows four algorithms including COVEN, DT-Score, random and our HCHA coverage ratio in the without obstacles exist scenario, for the main picture x-label is the number of static sensors and y-label is corresponding coverage ratio, the subgraph in the bottom right corner shows the relationship between the number of static sensors and mobile sensors. In Figure 15 we repeat the simulation for 200 times and take the average to plot the line chart, because the static nodes is deployed randomly, which leads to the simulation result is different every time. It can be seen that HCHA provides almost 100% more coverage than COVEN when there are 10 static nodes, while it requires about 50% more mobile nodes than COVEN. And the gap shrinks with the increasing of static nodes. It is also important that HCHA can detect and heal coverage holes well even when there is a little number of static nodes, and COVEN cannot provide better coverage by increasing the mobile nodes in such circumstances. This means HCHA is less dependent on the density of static nodes than COVEN. In Figure 16 we statistic the standard deviation of 200 times simulation, and from the results we discover HCHA is more stable than Random and COVEN. As to the obstacles exist condition, the coverage of HCHA and DT-Score is shown in Figure 17. It is easy to learn that the DT-Score has a better performance in the obstacles exist scenarios. Because our HCHA is proposed without the consideration of obstacles condition, and this condition will be researched in our future work. Our HCHA follow three key steps. Step one, static sensors construct DT. Step two, select head node to calculate coverage holes and find optimal position in the triangle. Step three, head nodes order mobile sensors to heal coverage holes. Compared to the COVEN, our algorithm exists some advantages. Firstly, our coverage holes detected algorithm based on Delaunay is relatively simpler than COVEN in three aspcts:  
* The coverage holes detecting. The COVEN algorithm divide the area based on the Voronoi diagram, as the result, the area is divided into many cells, and then divided every cell into several triangles to detect and calculate coverage holes.