# Robot Delay-Tolerant Sensor Network for Overhead Transmission Line Monitoring
## 4 Results
### Results for the Change of Movement Model  
In order to investigate the influence of different movement models on several routing algorithms, Scenario 3 is constructed. Robots moved under different movement models of BPRW, BMI and PRW, and the number or rate of robot was increased from 1 to 20, or from 1-3 m/s to 10-12 m/s. In different scenarios, we have recorded message delivery ratio, message delivery time, overheads, hop count, network life time, and energy consumption. The 95% confidence intervals were calculated for every result and they were plotted on the figures. In sub-scenarios 3.1-3.4, several parameters were adjusted, such as number or movement rate of the robots and the movement model. The parameters in Scenario 3 are configured, as shown in Tables 5-8. Each scenario has changed one or two parameters based on the default values. 200 simulations were performed for each scenario. The results for Scenario 3 are shown in Figures 21-26. For Sub-scenarios 3.1-3.2, it can be seen from Figures 21-26 that, all protocols have a similar performance with Scenario 2. The proposed DTMA performs best on the indexes of delivery ratio and energy consumption. Regarding hop count and overhead performance, Prophet V2 and Spray and Wait have the smallest number of hops and overheads, and DTMA almost performs the worst. Figure 22 also indicates that delay acts as a decreasing function of the rate of robots for all protocols. DTMA and Spray and Wait show the smallest delay as the rate increases, followed by Epidemic and Prophet V2. Finally, Prophet V2 and DTMA perform best on life time (Figure 26). Figures 21-26 show the difference in the performance of two motion models. It can be indicated that with the number of robots increasing, the difference between the performances of network under the two motion models becomes larger. When the number of robots is maintained at 1-5, the network performances under both models are approximately the same. After the number of robots increase to 10-20, all protocols have a better network performance when the robots follow uniform distribution in the map (BMI model). However, the performance of network life time is an exception (Figure 26). All protocols have a longer lifetime when robots can randomly move on the paths (BPRW model). Figure 23: Results of Scenario 3, Overheads with different number of robots. (**a**) BPRW movement model; (**b**) BMI movement model. Figure 24: Results of Scenario 3, Hop count with different number of robots. (**a**) BPRW movement model; (**b**) BMI movement model. Figure 25: Results of Scenario 3, Network life time with different number of robots. (**a**) BPRW movement model; (**b**) BMI movement model. For Sub-scenarios 3.3-3.4, it can be seen from Figures 27-32 that all protocols have a similar performance with Scenario 2. The proposed DTMA has the best performance on the delivery ratio and energy consumption. Regarding the hop count and the overhead performance, Prophet V2 and Spray and Wait have the smallest number of hops and overheads, and DTMA almost perform the worst. Figure 28 also indicates that the delay acts as a decreasing function of the rate of robots for all protocols. DTMA and Spray and Wait show the smallest delay as the rate increases, followed by Epidemic and Prophet V2. Finally, Prophet V2 and DTMA have the best life time performance (Figure 32). Figures 27-32 show the divergence in the performance of two motion models. In addition, it can be indicated that in most cases, all protocols have a better network performance when the robots follow one direction in the map (BPRW model). However, network life time performance is an exception (Figure 32). All protocols have a longer lifetime when robots can freely move on the path (PRW model). Figure 30: Results of Scenario 3, Hop count with different rate of robots. (**a**) BPRW movement model; (**b**) PRW movement model. Figure 28: Results of Scenario 3, Delivery time with different rate of robots. (**a**) BPRW movement model; (**b**) PRW movement model.