# Reinforcement Learning-Based Routing Protocols in Flying Ad Hoc Networks (FANET): A Review
## 5 Proposed Classification
### Classification of RL-Based Routing Protocols Based on Routing Algorithm
#### 5.2.3 Data Delivery Method  
In this section, the routing schemes are divided into three categories based on data delivery method: greedy, store-carry-forward, and route discovery. Table 5 presents a comparison between different data delivery methods. In the following, we describe these techniques in summary:  
Figure 16: Flat routing scheme.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Routing Scheme** & **Management of Node Roles** & **Scalability** & **Routing Overhead** & **Network Congestion** & **Energy Consumption** & **Network Lifetime** \\ \hline
**Hierarchical** & Difficult & High & Low & Low & Low & High \\ \hline
**Flat** & Simple & Low & High & High & High & Low \\ \hline \hline \end{tabular}
\end{table}
Table 4: Comparison of hierarchical and flat routing methods.  
Figure 15: Hierarchical routing scheme.  
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline
**Data Delivery Scheme** & **Bandwidth** & **Scalability** & **Routing** & **Network** & **Delay in the** & **Delay in the** & **Local** & **Broadcast** \\
**Consumption** & **Scalability** & **Overhead** & **Density** & **Transmission** & **Route** & **Discovery** & **Optimum** & **Storm** \\ \hline
**Greedy** & Low & High & Low & High & Low & Low & High & Yes & No \\ \hline
**Store-carry-forward** & Very low & High & Very low & Low & Very High & Very high & Very low & No & No \\ \hline
**Route discovery** & High & Medium & High & High and low & Medium & High & Medium & Low & Yes \\ \hline \hline \end{tabular}
\end{table}
Table 5: Comparison of data delivery methods.  
* The purpose of this routing technique is to reduce the number of hops in the created path between the source UAV and destination UAV. The main principle in the greedy method is that the closest UAV to the destination is geographically selected as a next-hop node, and this process continues until the packet reaches the destination. Figure 17 shows this process. The performance of this method is desirable when the network density is high. However, trapping in a local optimum is the most important weakness of this method. In this case, the data transmission process is stopped at the nearest node to the destination because there is no node closer to the destination. As a result, a path recovery technique is used to find an alternative path and guarantee the reliability of this method.
* This routing technique is efficient when the network is periodically connected and the source node fails to find an intermediate node to send its data packets. In this case, the source UAV must carry this data packet until it finds a suitable relay or destination node. This process is presented in Figure 18. According to this figure, the source UAV has no intermediate node around itself to send data packets. Therefore, it carries its data until it meets the destination UAV. This method is beneficial in low-density networks such as FANETs. In addition, this routing method has low routing overhead and is scalable. However, it is not suitable for real-time applications because it increases delay in the data transmission process.
* **Route discovery:*
* When the source UAV does not know the geographic position of the destination UAV, the route discovery technique is suitable. In this case, UAVs use the flooding technique and broadcast the route request (RREQ) packets to discover all possible paths to the destination UAV. After receiving the RREQ packet, the destination node is responsible for selecting a suitable path among the discovered paths based on certain criteria. Finally, this route is used to transfer the data packet between source and destination. This process is shown in Figure 19. This routing technique is highly regarded by researchers due to its simplicity. However, it has a high routing overhead  
Figure 17: Greedy routing technique.  
Figure 18: Store-carry-forward technique.  
due to flooding messages. This issue can lead to a broadcast storm in some cases. This greatly increases bandwidth consumption.