## 3 Related Work
### Underwater Monitoring
#### Underwater Acoustic Sensor Networks  
Intensive research is going on to discover a suitable framework for underwater sensor networks [10, 28, 29, 30, 31, 32, 33, 34]. In [28], authors proposed two distinct UASN design structures: the first one resembles the conventional cellular system based on a base station, whereas the second one focuses on decentralized _ad hoc_ network with multihop routing. The study in [29] classified the UASN architecture into three categories, among which hybrid architecture is analyzed in [10, 30, 31]. The authors of [30] studied an energy efficient and delay tolerant sensing model that requires strict time constrains. In [32], in order to cover a large scale underwater area with minimal power consumption, a hierarchical architecture called tree of wheels (ToW) topology is proposed. To the same direction an architecture named TurtleNet [33] is proposed, which incorporates vertical mobility of the underwater sensor nodes to increase the overall throughput of the network. In TurtleNet, a sensor node performs data transmissions in dual modes; when a node is underwater, it uses short-range acoustic modIn order to determine the path from U-sensors to the sink node or GWs, the sink node and GWs periodically flood _PHE_ (Pheromone) messages to the network. Upon receiving _PHE_ messages, based on the length of the path (e.g., the number of hops) that those messages have taken, each U-sensor determines the next hop to forward the data, _i.e._, a U-sensor selects the next hop such that the path length is minimized. A U-sensor also forwards _PHE_ messages received from other U-sensors, GWs, or the sink. Rather than forwarding all _PHE_ messages that it has received, a U-sensor forwards only _PHE_ messages that are sent by its next hop node. As a result, the number of flooded _PHE_ message is independent of the number of GWs. In fact, the number of _PHE_ message sent is asymptotically \(O(n)\) during a message transmission interval where \(n\) is the number of U-sensors. Therefore, the network can scale with the number of GWs and the sink. Figure 2(a) shows an example of determination of the next hop using _PHE_ messages. In the example, _US6_ (U-sensor 6) received two _PHE_ messages, \(P_{GW1}\) and \(P_{GW3}\), each has been generated by \(GW1\) and \(GW3\), respectively. Since \(P_{GW3}\) has the less value of the number of hops (e.g., 1), _US6_ selects \(GW3\) as the next hop (the next hop is represented by a dotted line in the example). Then, _US6_ forwards \(P_{GW3}\) to its neighboring node, _US3_. \(P_{GW3}\) is discarded by _US3_, since _US3_ selects \(GW1\) as the next hop based on the hop count information as shown in Figure 2(a). In other words, _PHE_ messages are flooded only in a local area. AUVs move in a pre-determined or dynamically controlled movement fashion. Note that, even though determining the trajectories and the movement pattern of AUVs is not within the scope of this paper, in order to gain insight into the effect of AUVs' mobility, we analyze the network performance with a various AUVs' movement patterns and the number of AUVs in Section 5, which assures that having an optimal AUVs' movement pattern is important to achieve a maximal network performance. When a GW detects that an AUV is passing by and it is close enough for data transmission, the GW sends data that it has collected from U-sensors to the AUV using a short-range, high data rate acoustic channel. In other words, GWs and AUVs take an advantage of the fact that they can be geographically close to each other, which allows a short-range high rate communication. Note also that the transmissions in a separate acoustic channel do not interfere other transmissions among U-sensors  
Figure 2: AUV-aided Underwater Routing Protocol: (**a**) Next hop determination based PHE Msg; (**b**) Data forwarding and aggregation. and GWs. The short-range acoustic communications is also used for data transmissions between AUVs and the sink node. An example of sensing data transmission is illustrated in Figure 2(b).