## 4 Privacy-Preserving Optimization Based on Advanced CH Selection (P2O-ACH)
### Enhanced ROA-Based CH Selection
Then, CH selection parameters are measured using the Equations (1)-(7) and the optimal CH is chosen according to the process of the ROA algorithm from Equations (16)-(20). Following that, the mobility model is assigned according to the rekeying and mobility supervision process, which consists of vehicle blending and the vehicle migration process. To calculate the performance of the network, we assess the parameters, which, concentrated in this research, are energy efficiency, energy consumption, network lifetime, packet delivery ratio, packet loss, network latency, network throughput, and routing overhead. For the process of performance comparison, our proposed P2O-ACH is compared with earlier works, such as GWO-CH [36], ACO-SCRS [37], and QMM-VANET [38]. The software used for the simulation experimentation is NS2.35 with from-end OTCL and back-end C language on Ubuntu 16.04. OTCL is used for network construction, data transmission, and configuration. The initial energy allocated for the network is 1000 Joules, and the data transmission and reception energies are 0.005 Joules and 0.001 Joules, respectively. The network coverage area is 1500 \(\times\) 1500 m. Eight clusters are deployed and the coverage area of each cluster is 500 m and the sensing range of the cluster head is 15 m. The network parameters [39; 40; 41] are listed in parameter Table 4.

### Scenarios Details

For the performance analysis process, two scenarios are taken, which are according to the number of vehicles and speed of vehicles. The parameters, which are calculated according to the number of vehicles, are energy efficiency, energy consumption, network lifetime, packet delivery ratio, packet loss, network latency, network throughput, and routing overhead. The parameters, which are calculated according to the various speed of vehicles, are cluster head efficiency and cluster member efficiency. All the calculations are elaborated on below. ### Performance Analysis Based on the Number of Vehicles

In Figure 2, the graphical representation of the energy efficiency calculation of the proposed P2O-ACH is given and it is compared with the earlier approaches. The major parameters, which are concentrated by the proposed P2O-ACH, are to reduce the energy consumption of the network using the enhanced ROA-based CH selection. During the \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameters** & **Values** \\ \hline Simulator Version & NS-2.35 \\ Simulation Time & 200 ms \\ Simulation Coverage Area & 1500 m \(\times\) 1500 m \\ MAC Interface & MAC/802.11 \\ Number of Vehicles & 150 Vehicles \\ Cluster Radius & 500 m \\ Transmission Range & 150 m \\ Vehicle Speed Range & 10 m/s to 35 m/s \\ Channel & Channel/Wireless \\ Radio Propagation Model & Two-Ray Propagation Model \\ Antenna Type & Omni-Directional Antenna \\ Queue Type & DropTail \\ Initial Power & 1000 Joules \\ Transmission Power & 0.005 Joules \\ Receiving Power & 0.001 Joules \\ Data Packet Size & 512 bytes \\ Agent Type & Transmission Control Protocol \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Simulation Parameters. simulation, it is greatly achieved and the energy efficiency of the proposed P2O-ACH is much better than others. Because of using the wider optimization-based CH selection process, an optimized stable CH is chosen that reduces the energy consumption of the network. In Figure 3, the energy consumption of the network is shown. In Table 5 the simulation result values of energy efficiency and energy consumption are given. The values stated in Table 5 prove that the efficiency achieved by the proposed P2O-ACH is better than earlier works where the efficiency of the P2O-ACH is 864 Joules and the efficiency of the GWO-CH, ACO-SCRS, and QMM-VANET is 357 Joules, 598 Joules, and 657 Joules, respectively. Then, the energy consumption of the proposed P2O-ACH is

Figure 3: Energy Consumption Calculation.