## 4 Performance Evaluation
### Performance Evaluation Using Node MCU
Arrow-Curve achieves lower values of standard deviation in indoor environment than in outdoor environment. For Arrow-Curve, the average position error\({}_{\text{std}}=1.0267\) in outdoor environment and 0.4719 in indoor environment. For H-Curve, the average position error\({}_{\text{std}}=1.1164\) in outdoor environment and 0.5681 in indoor environment. For R-Curve, the average position error\({}_{\text{std}}=1.14395\) in outdoor environment and 0.8134 in indoor environment. R-Curve achieves the highest values of standard deviation of error because of the nature of unsymmetric models. Hence, there are non-localized nodes in the corner which have higher error than others, which affects the values for standard deviation of error. Figure 21: Standard deviation of error (SDE) corresponding to resolution (L) in Arrow-Curve model, R-Curve path model, and H-Curve: (**a**) outdoor environment; (**b**) indoor environment. Figure 20: Average localization error (m) corresponding to sub-field (S) number at resolution (L) in indoor environment: (**a**) L = 7; (**b**) L = 6; (**c**) L = 5; (**d**) L = 4; (**e**) L = 3. 3. Coverage ratio. Coverage ratio is the percentage of nodes localized successfully in the network. As noted from Figure 22, the position coverage ratio at all resolutions in outdoor equals 100%, which means that all unknown nodes have been localized. The two proposed models achieve full coverage area in addition to the H-Curve model. 4. Number of pausing points. As noted from Figure 23, the number of pausing points depend on the number of edges of the path model. The number of pausing points outdoor is higher than those indoor because the network size is larger. 5. Path length. The path length does not influence the position error. However, it impacts the power consumed by the mobile node and the overall time of the localization procedure. The unpretentious solution for decreasing the power consumption is to reduce the path length covered by the mobile anchor node. The path length of H-curve trajectory [33] is compared to that of the proposed models. As noted from Figure 24, the path length is affected by the network size and the path model. Arrow-Curve and R-Curve have a shorter path model length in both outdoor and indoor environments than H-Curve because of the nature of the two paths and H-Curve path. Figure 23: Number of pausing points (PP) corresponding to resolution (L) in Arrow-Curve model, R-Curve path model, and H-Curve: (**a**) outdoor environment; (**b**) indoor environment. Figure 22: Localization coverage ratio corresponding to resolution (L) in Arrow-Curve path model, R-Curve path model, and H-Curve: (**a**) outdoor environment; (**b**) indoor environment. Power consumption. As noted from Figure 25, Arrow-Curve achieves lower power consumption results than H-Curve by 50% (outdoor) and 75% (indoor). R-Curve achieves power consumption results lower than H-Curve by 27% in outdoor and 24% in indoor. The power consumption is affected by the network size, path length, number of pausing points, and energy dissipated during communication. Arrow-Curve and R-Curve dissipate less power in both outdoor and indoor environments. On the other hand, H-Curve has high power consumption because of the nature of the path length of H-Curve and high number of pausing points. The power consumption is reduced through choosing the path model, with the lowest path length, and by reducing time at each pausing point.