## 2 Related Work
### Routing Protocols for UWSN  
As mentioned before, one of the main characteristics of the underwater acoustic channel is the propagation delay. Since it is five orders of magnitude higher than its radio frequency counterpart, different routing protocols have been proposed to mitigate this effect. A centralized routing protocol is proposed in [18] to mitigate the high packet delay using a sliding window approach. The main drawback of this protocol is the increasing need of different transmission channels with the number of nodes. [PERSON] and [PERSON] study in [19] the effects of the differences between the terrestrial and underwater transmission mediums and the relationship between energy consumption and different radio modes. Furthermore, they design a set of new routing protocols considering these studied factors. Although they make the assumption that each node has information about its position, it is not specified how localization is performed. There are some approaches that use geographic routing protocols. In the VBF (Vector-Based Forwarding) algorithm [20] a node forwards a packet if the node is close enough to the estimated routing vector. The sender encapsulates into the data packet its position and the receiver position. With this information an intermediate node will forward the packet if it is close enough to the routing path. DBR (Depth Based routing) [6] routes the messages from the bottom of the ocean to the surface using only depth information. The depth of the source node and the depth of the forwarder are attached to the packet, that way, an intermediate node forwards a packet only if its depth difference with the forwarder is higher than a certain predefined threshold. In addition, an intermediate node has to wait to forward a packet for a certain amount of time called the holding time during which, if a copy of the packet is received, the transmission is cancelled. This way, the protocol avoids flooding and the routing can be made without exact location information. A similar algorithm to DBR is DSR (Direction-Sensitive Routing) [21]. This algorithm utilizes a fuzzy logic inference system to decide which nodes should forward a packet based on the distance and angle between two neighbouring sensor nodes, and the remaining energy left in the sensor node. In addition, in order to save energy, the protocol restricts the forwarding of the packet when the broadcast tree grows larger than a specified tree level. According to the authors, DSR can achieve the same packet delivery ratio as DBR but with lower end-to-end delay and less energy consumption. QELAR (Q-learning-based Routing) is presented in [22]. It is an adaptive routing protocol based on a machine learning approach. When a node needs to transmit data, it piggybacks some state information. Every time a node receives a packet, even if it is not its destination, it reads the added state information and updates its state and routing function. Authors compare performance of QELAR _versus_ the VBF algorithm and conclude that QELAR can achieve the same performance in terms of delivery rate and routing efficiency, but with more energy efficiency. In [23] a centralized routing protocol based on geographic information is proposed. The master node computes the topology and the routing paths. The main drawback of this protocol lies in the complexity of the algorithm that computes the topology and the routing paths, since it is NP-complete. Minimum Cost Clustering Protocol (MCCP) is a distributed clustering protocol proposed in [24]. The authors propose a cluster-centric cost-based optimization problem for the cluster formation. Although cluster-heads have the ability to send the data in a multi-hop manner to reach the sink, all nodes are supposed to be able to reach the sink. The cluster-head selection algorithm does not assure that the cluster-heads far away from the sink are able to relay their data to other cluster-heads. In [25] authors present MPR (Multi-Path routing).