## 3 Routing Protocol: RFAODV
### Network Model  
In reality, many underwater wireless sensor networks are composed of mostly static nodes and a certain number of mobile nodes. Underwater sensor nodes with acoustic  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Protocol** & **Classification** & **Contributions** & **Comparison** \\ \hline VBF & location-based routing protocol & uses the location information of nodes to limit the scale of flooding & too sensitive to the routing pipe radius threshold \\ \hline ALRP & location-based routing protocol & uses location information to set forwarding regions, delay, and probability strategies to increase forwarding efficiency & (1) & using probability to select forwarding nodes, there is the possibility of non-forwarding nodes; \\ \hline DVOR & location-based routing protocol & uses location information to set forwarding regions, delay, and probability strategies to increase forwarding efficiency & (2) & set the delay for the forwarding node to increase the delivery delay of packet \\ \hline AODV & location-free routing protocol & uses a flooding route discovery & flooding routing discovery method and the routing maintenance mechanism of periodically sending hello packet \\ \hline DSAODV & location-based routing protocol & uses geographical location to limit the area of RREQ’s propagation & the forwarding node in the forwarding area will still adopt the flooding protocol \\ \hline NNRR & location-based routing protocol & uses of the node’s position to rebroadcast the RREQ packet & the overhead is excessive and takes up the communication bandwidth \\ \hline GAODV & location-based routing protocol & discovers a route in a unicast manner using the locations of the RREQ sender and the destination and improve significantly the packet delivery ratio, the end-to-end latency, and the routing overhead & only applies to uniform network \\ \hline PEAB & energy-based routing protocol & trims down the flooding problem by considering nodes current remaining energy and threshold random delay to generate rebroadcast probability dynamically for efficient route discovery & single-dimensional optimization strategy \\ \hline AODV-SUARP & energy-based routing protocol & determine the energy level of nodes through energy stability parameters, and effectively select the most reliable nodes to participate in packet transmission & single-dimensional optimization strategy \\ \hline \hline \end{tabular}
\end{table}
Table 1: The comparison of the related protocol.  
modems are distributed in the interested 3-D area, with each likely to be a data source. They can collect data and help relay data to the destination. The spatial position of static nodes installed on submersible beacons or hoisted from buoys varies within a small range. Mobile nodes can move freely in the observation area. Underwater acoustic wireless sensor networks connect distributed nodes into networks by acoustic communication. We estimate the sound propagation losses using [PERSON]'s empirical formula. Over a Euclidean distance of \(d\) and for a signal frequency of \(f\), the path loss of the acoustic channel is as follows:  
\[A(d,f)=d^{k}\times a(f)^{d} \tag{1}\]  
Here, \(k\) is an expansion factor representing the geometry of propagation; \(k=1\) corresponds to cylindrical expansion and \(k=2\) corresponds to spherical expansion. (\(f\)) is the absorption coefficient of seawater. [PERSON]'s formula gives the empirical formula of \(a(f)\) as follows:  
\[10\log a(f)=\frac{0.11f^{2}}{1+f^{2}}+\frac{44f^{2}}{4100+f^{2}}+\frac{2.75f^{ 2}}{10^{4}}+0.003 \tag{2}\]  
Furthermore, we assume that each node knows its location information, and obtain the location of source node, destination node, and last forwarding node through a redefined RREQ packet.