## 4 Performance Evaluation
### Experimental Results and Discussion
#### 4.3.2 The Impact of Sensor Mobility  
In this section, several experiments have been conducted to verify the impact of sensor nodes mobility on the performance of the proposed SensorAnt. To achieve this, the Static-SensorAnt deployment is compared with another SensorAnt scenario where all the nodes in the network are mobile using the random way point mobility model. The effects of this operation are studied from two prospective: first, under various numbers of sensor nodes and second under different time periods using same performance metrics as before. **(a) Under Varying Number of Sensor Nodes:** the result presented here compares the Static-SensorAnt and the Mobile-SensorAnt as the number of sensor nodes varies. Figure 17 demonstrates that the Mobile-SensorAnt obtains better throughput compared to the Static-SensorAnt. This is because in the static case, the congestion and message drops occur more than in the mobile case. Moreover, notice that the difference between the two cases is not too much, which is indicative of the fact that adaptation of the proposed SensorAnt scheme from the static to a mobile environment is indeed feasible. Also, Figure 18 shows that the Static-SensorAnt presents a better performance than the Mobile-SensorAnt with regards to the total energy consumption, which is observably comparable. This phenomenon can be attributed to the fact that the mobile nodes which act as relays are regularly changed leading to a much fairer distribution of the consumed energy among the sensor nodes. It is significant to observe that the energy usage is associated with the throughput whereas packet drops increase the consumed energy. Figure 17: Comparison of throughput between Static and Mobile-SensorAnt with different sensors. Figures 19 and 20 depict the energy efficiency and average energy of the deployed sensors for both the static and mobile SensorAnt. As it can be seen, the Mobile-SensorAnt incurs a little more energy cost compared to the Static-SensorAnt but is still acceptable. Increasing the network size under the same period of time doesn't make sense, since we applied the energy-balance scheme, in both situations, where the energy consumption is totally balanced between nodes. Figure 21 clarifies this further, showing the standard deviation of the energy cost for both scenarios. As in the previous plots, the deviations in energy levels between the static and mobile scenarios are very similar; thus validating the effectiveness of the SensorAnt algorithm. **(b) Under Different Periods of Time:** The result presented here compares the energy cost incurred by the Static and Mobile-SensorAnt scenarios with time. Figure 22 shows that the Mobile-SensorAnt outperforms the Static-SensorAnt throughout the simulation time. In the static case, the congestion and packet drops occur more than in the mobile case. It can be noted that in both cases, the first 400 s of the simulation time depicts increasing throughput; however, beyond this point, Mobile-SensorAnt stabilizes whereas the Static-SensorAnt shows decreasing trends in throughput. This is so because as the path between the sender and sink nodes becomes congested with more packets, the occurrence of packet drops is likely to increase when the network is not dynamic. In the Mobile-SensorAnt however, the sensor nodes keep moving about in the WSN, thereby resulting in the re-distribution of the system bottlenecks throughput the whole WSN. Figure 23 illustrates the total energy usage of the proposed Static-SensorAnt compared to the Mobile-SensorAnt. Here, it can be clearly seen that the Static-SensorAnt decreases the energy usage compared to the Mobile-SensorAnt under all circumstances. By investigating the throughput and the energy consumption of the Mobile-SensorAnt, we observed that the Mobile-SensorAnt got a significant packets' delivery resulting to cost higher energy than Static-SensorAnt. In addition, we can  
Figure 21: Comparison of standard deviation between Static and Mobile-SensorAnt with different Sensor Nodes.