## 4 Simulation Experiments, Results, and Discussion
### Formulation of Metrics and Results  
We have formulated four metrics for the measurement of results that are briefly mentioned below:  
UAV-Energy Consumption(UAVE): UAVE is the summation of the energy consumption of all UAVs throughout the simulation period. Consumed energy is the difference between the initial energy of a UAV and its residual energy after the simulation period. So,  
\[UAVE=\Sigma_{Cur\_UAV\in UAV\_Set}(init\_energy(cur\_UAV)-final\_energy(cur\_ UAV)) \tag{13}\]  
here Cur_UAV denotes the current UAV that is being considered. UAV_Set is the set of all UAVs applied in the current simulation scenario. init_energy(cur_UAV) and final_energy(curUAV) specify initial and final powers of the UAV named cur_UAV, after the end of the simulation process. Using the formula in (13), UEC has been measured in other state-of-the-art related to EETO-GA. However, in EETO-GA, we maintain a table TASK_EXEC in each UAV where the last column is mentioned as ENRG_CONSUMED which specifies the amount of energy spent by the current UAV in the execution of these tasks (it is also specified in Section 3.5). So, big summing this column, we get the total energy consumption of the current UAV throughout the simulation period summing over all UAVs, we get UEC as shown in (14). \[UAVE=\Sigma_{Cur\_UAV\in UAV\_Set}\Sigma(ENRG_{C}ONSUMEDinTASK_{E}XEC(cur_{U}AV)) \tag{14}\]  
IoT Device Energy Consumed (IoTDEC):  
In state-of-the-art related to EETO-GA, energy consumption in IoT devices was not separately considered, So, for those algorithms, we have measured energy consumption as the difference between initial energy and residual energy, as shown in (15). \[IoTDevice=\Sigma_{cur\_dev\in IoTDevice,et}(init\_energy(cur_{dev})-final\_ energy(cur\_dev)) \tag{15}\]  
Here, init_energy(cur_dev and final energy cur_dev denote the initial and final power of the current IoT device cur_dev. IoTDevice_set is the total number of IoT devices in the network. On the other hand, in EETO-GA, each IoT device maintains energy consumption information C-Ei where C-Ei is the energy consumed so far by the ith device which was discussed in Section 3.2, so, it can be formulated as in (16). \[IoTDevice=\Sigma_{cur\_dev\in IoTDevice\_set}(C-E_{cur\_dev}) \tag{16}\]  
Average Delay in Execution of the Task (ADET): \begin{table}
\begin{tabular}{c c} \hline \hline
**Name of the Parameter** & **Value** \\ \hline Coverage Area & \(300\times 300\) m\({}^{2}\) \\ \hline Number of IoT devices & \(100,300,500,700,900\) \\ \hline Number of UAVs & \(1,3,5,7,9\) \\ \hline Min no. of devices in a cluster & \(3\) \\ \hline Max no. of devices in a cluster & \(20\) \\ \hline Hovering altitude of UAV & \(6\)m \\ \hline No. of CPU cycles/s in an UAV & \(0.5\)G cycles/s \\ \hline Channel gain & \(-20\) dB \\ \hline UAV speed & \(20\) m/s \\ \hline Noise power & \(-50\) dBm \\ \hline Transmission bandwidth & \(150\) khz \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Names and Values of Various Simulation Parameters. Average delay, for all the algorithms calculated as in (17). This is nothing but the difference between timestamps of initiation of a task and its execution, averaged over all the tasks for all CHs. \[ADET=\Sigma_{cur\_cs\in\cup_{i=\text{tmax}}CLS(i)}\Sigma_{\rho\in\text{task\_ sees}(cur\_cs)}(tm\_exec(\rho)-tm\_gen(\rho)) \tag{17}\]  
Here, cur_CS is current CH, p is a task submitted to it tm_exec(p) and tm_gen(p) are execution completion time and task generation time for the task \(\rho\). Percentage of tasks that could be completed (PTSK): As per Section 3.5, it can be formulated in (18). We experimented with proposed EETO-GA, and other state-of-the-art, namely CEC, PEM, and AoI-IP in the summation setup mentioned in Table 3. Comparative results are presented in graph formats in Figures 3-6. In this simulation scenario, if we considered highest results of CEC, PEM, and AoI-IP in each setup as standard system performance indicator, then proposed EETO-GA improved average UAVE: 43%, IoTDEC: 56%, PTSK: 7.5%, and ADET: 38%.