# A Node Placement Algorithm Utilizing Mobile Nodes in WSN and IoT Networks +
## 6 Evaluation
### Experimental Results
#### 6.3.3 Evaluation of eNPA with Different Energy Models  
In this part of the evaluation, our novel energy-efficient solution is compared with different energy models based on different mobile robots characteristics, as presented in Section 5.4. We use existing energy models based on three different types of mobile robots and simulate them with our own algorithm to compare their results. The main goal is to examine if the energy model is important in the energy consumption of the nodes in the network or the algorithm is the main resource of consumption. Evaluating the Energy Models  
In this section, we compare the different scenarios of the algorithm to each energy model. In Figure 10(a), we present the results for all scenarios using energy model 1. At first, all scenarios have similar results due to the structure of the algorithms, and when the mobile node starts acting differently, each scenario has a different result. We can observe that Scenario 3B finishes with the most consumed energy, which is normal because it is the only scenario using the most mobile nodes. In Figure 10(b), we present the results for all scenarios using energy model 2. Scenario 3B is the one with the most consumed energy, followed by scenario 1 having a slight difference. Scenario 2 has the least amount of consumed energy in the network due to the fact that only one mobile node is used in the network. In Figure 10(c), we present the results for all scenarios using energy model 3. Similar to the previous one, it is shown that scenario 3B has the most consumption. The least consumption is seen in scenario 2, where the mobile node is reused, which is normal as only one mobile node is needed in the network. In general, we can observe that all energy models have the same performance while running our algorithm. Based on the results, it is shown that energy model 3 presents the largest energy consumption and energy model 1 has the least energy consumption. Based on the scenarios, it is shown that scenario 3B is the one that uses the most mobile nodes in the network and takes the first place in energy consumption. Scenario 2 uses only one mobile node because reusing the mobile nodes in the network results in consuming the least energy of them all. Evaluating the Energy Model Based on the Scenario  
In this section, we compared different energy models for each scenario of the algorithm in order to present the differences in each robot's characteristics. Does an energy model of  
Figure 11: Evaluation of the different Energy Models. (**a**) Energy Model 1, (**b**) Energy Model 2, (**c**) Energy Model 3.  
a different robot have a different result in the total energy consumption of the network? It is worth mentioning that the speed of the node is set as 0.65 m/s, which is the same constant in all three energy models. In Figure 11(a), we present the results of each energy model for scenario 1. In this scenario, the number of mobile nodes in the network at the end of the simulation is two. We can observe that energy model 2 and energy model 3 are the ones with a slightly small difference due to their equation that uses the time variable, whereas the energy model uses the distance variable. All models use the same speed variable, so the difference is present in the other variables of the equations. In Figure 11(b), we present the results of each energy model for scenario 2. In this scenario, we reuse the mobile node in the network, so only one mobile node is inserted into it. With respect to the general energy consumption, the numbers are lower than the previous scenario, which is normal due to the number of mobile nodes used. In respect of the energy models used, the one using the distance has higher consumption than the other using the time, which is normal due to the fact that the mobile node moves and its distance is changed, whereas the time changes constantly. In Figure 11(c), we present the results of each energy model for scenario 3A.