# Review and Comparison of Emerging Routing Protocols in Flying Ad Hoc Networks
## 4 Routing Protocols
### Topology Aware Routing Protocols
#### 4.1.5 Discussion and Analysis  
For each protocol, we have discussed its advantages and disadvantages. The following table (Table 2) illustrates the comparison of metrics that are used to quantify the performance of the above routing protocols. From this table, we can see that, although these protocols are designed for FANETs, they have different emphasis on performance because they must be applicable to different application scenarios and satisfy different requirements. The works in [36; 38; 39; 41] have a common feature in that they all reduced latency by adjusting the network topology. However, the authors of [36] mainly solve the problem of network segmentation and the selection of relay nodes when ground network and aerial ad hoc network coexist. Therefore, the application environment of this protocol is the ground-aerial network, rather than the completely independent FANET. The authors of [38; 41], according to the characteristics of dynamic topology of FANET, proposed adaptive methods to construct network topology. However, the application scenarios in [38] are 2-dimensional, and the PSO algorithm it used is too simple to satisfy the special flying nodes. The author of [39] combined the classical DSR protocol with the concept of neural network. Neural network is a popular machine learning algorithm, which builds thinking models by simulating the logic of the human brain. This article made use of the historical topology information of the nodes to make the best decision at the next time when finding a path. However, there is still a lot of defects for improvement in this article, such as considering the dynamic position changes of the UAVs.  
\begin{table}
\begin{tabular}{l c c c c c c c} \hline \hline \multirow{2}{*}{**PROCOCOCOCO**} & **PACKET** & **END-TO-END** & **END-TO-END** & **CHANNEL** & **OVERHEAD** & **LINK** & **COILSION** \\  & **RATIO** & **DELAY** & & **UTILIZATION** & & **QUALITY** & **SAFETY** \\ \hline
**DPTR**[36] & ✓ & ✓ & ✓ & ✓ & ✓ & ✓ & ✓ & x \\
**TCM**[38] & x & ✓ & x & x & x & ✓ & ✓ \\
**CHNN-DSR**[39] & ✓ & ✓ & ✓ & x & x & x & x \\
**TARCS**[41] & ✓ & ✓ & ✓ & x & x & x & x \\ \hline \hline \end{tabular}
\end{table}
Table 2: Comparison of metrics used in topology aware routing protocols.  
Although the above protocols have many advantages, we have to list some key issues and hope to improve it in future research:  
(1) Whether there is a fixed time interval when a node measures topology changes?  
(2) Whether there is an upper limit on the topology change and how to measure it?  
(3) How to assign weights to the influencing metrics?  
(4) How to solve the problem when the number of nodes changes?  
It can be seen that it is necessary to develop an optimal routing method to handle different node numbers while maintaining consistent data delivery in the network. Reducing network overhead and identifying optimal routes are both challenging problems that need to be overcome because routing strategies require to adaptively handle high node mobility to identify optimal routes with less latency.