## 5 Communication in Vehicular Networks
### Clustering in Communication  
The dynamic character of the nodes in the IoV and IoFV and the resulting incessant changes in the topology of the network cause significant problems that hinder the ability to scale the network or route data effectively [73]. To address those issues, the clustering of nodes is commonly used, which is a strategy of dividing the network into groups of nodes as displayed in Figure 4 and Table 3. This division can be based on a multitude of metrics, such as the geographical distances of nodes. Typically, there are three types of nodes that can be present in clusters [80], as portrayed in Figure 4. The first type is the cluster head (CH) node, which bears the responsibility \begin{table}
\begin{tabular}{l l l l l l l l} \hline \hline
**System** & **Algorithm** & **WoS** & **Scopus** & **Year** & \
\begin{tabular}{l} **Citations** \\ **WoS** \\ \end{tabular} &
\begin{tabular}{l} **Citations** \\ **Scopus** \\ \end{tabular} & **Reference** \\ \hline EC-MOPSO & PSO & Yes & Yes & 2022 & 2 & 1 & [74] \\ \hline MADCR & MOA & Yes & Yes & 2021 & 7 & 11 & [75] \\ \hline AFS Clustering & AFS & No & Yes & 2020 & - & 3 & [76] \\ \hline CACIOOV & ACO & Yes & Yes & 2019 & 13 & 19 & [77] \\ \hline MFCA-IoV & MFO & Yes & Yes & 2019 & 31 & 38 & [78] \\ \hline CAVDO & DFO & Yes & Yes & 2018 & 52 & 64 & [79] \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Overview of swarm intelligence-based clustering algorithms. of coordination and communication with other clusters, as well as the management of the node communication inside the cluster [81]. Therefore, this node should have added features in terms of power, processing, and storage capabilities [46]. Another type of node present in a cluster is the cluster member (CM) node. This represents an ordinary node that has been included in a cluster based on a similarity metric [82]. This type of node can only communicate directly with the cluster head. The last type of node that can be present in a cluster is the so-called cluster gateway (CG), which bears some similarity to the CH and therefore is frequently merged into one node for communication outside of the cluster. The CG is frequently located on the cluster border compared to the CH [82]. The formation of clusters can have one of two forms: the centralized formation--in which a central node, usually an RSU, assigns nodes to appropriate clusters [83]--or the decentralized approach to formation--in which each node seeks its assignment locally [84]. The process of forming clusters in the network has several steps [85]:  
* Discovery: In this stage, vehicles joining the network periodically broadcast messages reporting their state as unclustered along with the data required to assign the vehicle to a cluster. * CH selection: Upon receiving broadcast messages from neighboring nodes, a vehicle will elect an appropriate node based on the gathered data. * Notification: After a CH is elected, it announces its state to the other vehicles by broadcasting to the unclustered nodes. * Association: Subsequently, other nodes request to join the cluster and change their state to clustered. * Maintenance: Both the CH and CM monitor the communication state with each other. If the link is lost, a CM will change its state to unclustered and attempt to join a different cluster. When this process is utilized in the network, clustering may have a number of advantages. The primary benefits are energy conservation and a reduction in data transfer delay [86]. However, the formation of optimal clusters in vehicular networks is considered to be an NP-hard problem; hence, it is beneficial to focus on near-optimal solutions. As a result, numerous systems have introduced swarm intelligence algorithms to perform clustering [79] such as those summarized in the Table 3. In order to determine their effectiveness, we have evaluated the available data from the experiments described in Table 4. As described earlier, the primary goal of clustering algorithms in the IoV is to generate the smallest possible amount of clusters.