## 3 Materials and Methods
### Construction of Network
#### 3.3.1 Perceptron Classifier Based on Single-Layer Operations
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**S.No.** & **Parameters** & **Definition** & **Description** \\ \hline \multirow{3}{*}{7} & \multirow{3}{*}{\(CH\)} & \multirow{3}{*}{Cluster heads for zones} & Every zone holds a selected cluster head, which is part of the cluster, and makes effective cluster collaborations to discuss and provide the cluster-based implementation policies. The discussed results provide effective zone-based content pre-caching and enhancement strategies. \\ \hline \multirow{3}{*}{8} & \multirow{3}{*}{\(X_{rnd}\)} & \multirow{3}{*}{Zone radius} & Every zone holds a radius that consumes the zone area and provides the system enhancement features to collect and discuss the resulting privileges. \\ \hline \multirow{3}{*}{9} & \multirow{3}{*}{\(ML\)} & Machine learning algorithms for vehicles. & We adopted a machine learning vehicles-based approach to handle the content congestion and enhanced the features for the collaborative workings. \\ \hline \multirow{3}{*}{10} & \multirow{3}{*}{Data Exchange} & The data is the exchange between the network and different parties for network performance. & The content is the exchange between RSU, BS, and vehicles before and after the attacks. These devices provide the full flexibility to exchange data with high-volume perspectives. \\ \hline \multirow{3}{*}{11} & \multirow{3}{*}{\(V2V_{com}\)} & Communication point from vehicle to vehicle. & The communication point from the vehicle addresses provides the collective methodology for the results and discussions to elaborate and provide the working methodologies effectively. \\ \hline \multirow{3}{*}{12} & \multirow{3}{*}{\(V2I_{com}\)} & The communication with vehicular output architecture. & The complete network permission and vehicle communication architecture is provided with the ability to demonstrate and enhance the total communication between the vehicle to infrastructure communication. \\ \hline \multirow{3}{*}{13} & \multirow{3}{*}{\(R_{r}\)} & \multirow{3}{*}{Requested content of size r} & The content requested by the consumer node is size r, where r is the threshold value set in the algorithm to provide effective caching placement and implementation strategies. \\ \hline \multirow{3}{*}{14} & \multirow{3}{*}{\(D_{r}\)} & Delivered content of size r & The content, which is delivered to the requested vehicles, is size r. \\ \cline{1-1} \cline{3-3} \multirow{3}{*}{15} & \multirow{3}{*}{\(Req_{data}\)} & Requested content with data requested. & This shows the request for the data and content from the requested node toward the content placement and enhancement strategies. \\ \hline \multirow{3}{*}{16} & \multirow{3}{*}{\(DM_{Node}^{Z}\)} & Data rate among manager nodes and vehicles. & The data rate for the manager node and vehicles shows at which rate the data is delivered among these nodes for proper implementation. \\ \hline \multirow{3}{*}{17} & \multirow{3}{*}{\(Z_{table}\)} & \multirow{3}{*}{Intra cluster entries table} & The table stores all the communication entries found between the communication of RSUs and vehicles between different clusters. \\ \hline \hline \end{tabular}
\end{table} 
Table 2: _Cont._In step 2, the algorithm defines its predictions based on the dataset provided in this phase of the development steps.