# Routing Protocols for UAV-Aided Wireless Sensor Networks
## 5 Comparison of Routing Protocols
\begin{table}
\begin{tabular}{p{142.3 pt} p{142.3 pt} p{142.3 pt}} \hline \hline
**Protocol** & \multicolumn{2}{c}{**Advantages**} & **Limitations** \\ \hline HHA & Ensures an efficient set of paths to gather data and deliver to the sink. & The number of hops may increase delay. \\ \hline SN-UAV & Sensor node wake-up schedule and UAV trajectory are jointly optimized. & Considers single-UAV scenario, where UAV-sensor allocation and channel interference are not considered. \\ \hline UAV-WSN & Multi-layer approach makes equipment collaborate to provide an efficient solution. & Security issues such as network jamming are major concerns and node failure is not studied. \\ \hline UAV-AS-MS & Rapid deployment and optimal routing are obtained by solving vehicle routing problem. & Only low-density WSNs are considered. \\ \hline ULSN & Reduces communication interference for a linear deployed sensor network. & Only messaging is considered for communication between WSN and UAV. \\ \hline URP & Dynamic clustering approach with dynamic path of UAV & Considers single-UAV and single-hop communication. \\ \hline C-UAV-WSN & UAV flight path is updated on the basis of new cluster head (CH) location. & Single-hop cluster may increase the number of clusters in the network. \\ \hline rHEED & Optimizes UAV path and altitude to reduce the number of uncovered nodes. & For a large number of nodes, the single UAV approach is not realistic. \\ \hline UADG & Approach is suitable for any density of the network. & For utilizing multiple mobile agents, parallel processing is not considered. \\ \hline DPBA & Joint consideration of bandwidth allocation and energy allocation increases the transmission rate. & Single UAV-based resource optimization may decrease network performance. \\ \hline EEDGF & Minimizes the travel time by providing optimal position and path of UAV. & Communication interference is not considered for multi-UAV deployment. \\ \hline PCDG & Compressive data gathering approach reduces the number of transmissions, which reduces the energy consumption. & Compressive data gathering is effective only for a large-scale network. \\ \hline ADCP & A heuristic pricing scheme solves the three-dimensional (3D) positions of the targets while accounting for mobility and connectivity variations. & UAV path planning is not considered. \\ \hline H-UAV-WSN & Obstacle avoidance is considered in sensor clustering as well as UAV routing. & UAV data collection depends on CH location, and CH node failure may drop the data transmission. \\ \hline TADA & Achieves topology-aware data aggregation. & Link transmission failure is not considered. \\ \hline UAV-CDG & Allows a lower number of transmissions. & Suitable for large scale network. \\ \hline EEIS-WSN-UAV & UAV is used for joint optimization of node localization and time synchronization. & A large number of beacon nodes significantly increase the cost of the network. \\ \hline LS-UAV-WSN & Increases the network coverage. & UAV path and altitude are not taken into consideration, which may have effect on sensing. \\ \hline PSO-WSN-UAV & Topology optimize reduces transmission error and energy consumption. & Wind speed may have an effect on UAV traveling time. \\ \hline FSRP & Increases the data collection reliability. & Single-UAV network and transmission interference may occur. \\ \hline EFUR-WSN & UAV route can reduce energy consumption of data transmission. & 50 m of UAV altitude may not be applicable in real life scenarios due to obstacles and may have higher line of sight (LoS). \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Advantages and limitations of the existing routing protocols for UAWSNs. gathering, collection, and distribution. An efficient routing protocol has lower energy consumption, lower end-to-end delay, communication reliability, fault tolerance, and scalability. A multi-path routing protocol ensures a high data-delivery ratio and communication reliability. Nevertheless, most of the routing protocols in UAWSNs do not consider load balancing as a routing metric.