## 3 System Model
### Network Model and Assumptions  
In our proposed model, \(N\) number of SNs (i.e., \(S_{1},S_{2},S_{3},\ldots S_{N}\)), each with the same \(E_{0}\) (i.e., homogeneous WSN), are randomly deployed in the Fol which is located at a distance away from the BS, as shown in Figure 2. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Metric/Features** & **EEUCH** [**Ours**] & **LEACH [19]** & **LEACH-C [20]** & **TEEN [22]** & **IEE-LEACH [23]** & **SEP [21]** & **EEECA-THWSN [24]** \\ \hline Network scenario & Homogeneous & Homogeneous & Homogeneous & Homogeneous & Homogeneous & Two-tier heterogeneous & Three-tier heterogeneous \\ \hline  & & & & & SNs decide & & & SNs decide \\  & & & & & CHs for each & & & CHs by considering \\  & Each UAV & & BS decides & SNs decide & cluster by & SNs decide & the hetero- \\  & announces & SNs decide & CHs for each & CHs for each & CRs for each & considering & CHs for each & density in \\  & formation & itself as a CH & CHs for each & cluster by & cluster & average and & cluster by & SN’s energy, \\  & and CH & for its & cluster & considering & randomly, & total energy & considering & current and \\  & & respective & randomly & SN’s energy & also clusters & of the WSN, & the hetero- & initial energy \\  & cluster & & and location & of CHs are & residual & geneticity in & of WSN, \\  & & & & & & energy of SN, & SN’s energy & average \\  & & & & & and round & & distance from \\  & & & & & number & & BS and \\  & & & & & & & SN’s location \\ \hline Location & \begin{tabular}{c} \(d\) distance \\ of BS \\ \end{tabular} & \begin{tabular}{c} \\ away from \\ the Fol \\ \end{tabular} & In the middle & In the middle & In the middle & In the middle \\ of Fol & of Fol & of Fol & of Fol & of Fol & of Fol & of Fol \\ \hline Simulation & \begin{tabular}{c} MATLAB \\ software \\ \end{tabular} & MATLAB & MATLAB & NS-2 & MATLAB & MATLAB & MATLAB & MATLAB \\ \hline WuR for SNs & Yes & No & No & No & No & No \\ \hline \
\begin{tabular}{c} Data \\ collection \\ from Fol \\ \end{tabular} &
\begin{tabular}{c} Whenever \\ required \\ (Application \\ dependent) \\ \end{tabular} & Continuous & Continuous & Continuous & Continuous & Continuous & Continuous \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Comparative analysis of the proposed EEUCH and benchmark routing protocols. Figure 2: Proposed network model. Initially, all SNs in the FoI are in sleep mode (i.e., their MRs are turned off) to save energy by diminishing idle listening and overhearing. In sleep mode, the SNs sense their surroundings and wait for the WuC. When the UAVs arrive at a certain altitude from the FoI at their desired predefined hovering positions for data collection from SNs, they send a WuC to the ground SNs. The WuC is received by the WuRxs of the SNs. The SNs activate their MRs and send joining requests to the specific UAV whose WuC is detected by their WuRxs. It is critical for SNs to reliably transmit these joining requests in order for them to participate in cluster formation as CMs. When UAVs receive joining requests from SNs, they form clusters that include all of the SNs that sent joining requests. Hence, those SNs become CMs. In order to ensure reliable data communication, the UAV assigns TDMA slots to all of its CMs. These TDMA slots are then received by the MR of SNs. Within their assigned TDMA slots, data packets are transmitted from the CMs to the UAV, as each CM is assigned a unique TDMA slot to avoid any collisions or interference between them. After successful data communication, the UAV acknowledges the received data packets, CMs receive Ack from the UAV, and turn off their MR and enable sleep mode. It is noteworthy that the SNs deployed at the cluster boundaries may receive multiple WuCs from different UAVs. However, an SN can only respond to the first WuC received from a UAV; all subsequent WuCs received from other UAVs are ignored. Consequently, an SN can only be a CM of a single UAV in the particular round, which eliminates overlapping among the clusters.