# Cooperative Communication Based Protocols for Underwater Wireless Sensors Networks: A Review
## 4 Network Layer Protocols  
Typically, underwater nodes are battery-supplied devices that work with low transmit power to reduce the energy consumption. This unavoidably limits the achievable communication range since the acoustic signal may be strongly corrupted by noise and other channel impairments. Therefore, cooperative networking is considered as a promising strategy to deal with such issues since, by means of nodes cooperation, long and unstable links can be replaced with shorter multi-hop routes. A potential reference structure for multi-hop a UWSN scenario is that one provided in Figure 1. However, it is worth highlighting that, while in computer-like networks routing is essentially aimed to optimize data traffic, in UWSNs path selection is more oriented to energy efficiency. In fact, selecting the highest quality network hop reduces the need for potential packet retransmission (at link layer level), hence minimizing the nodes power consumption. So, as already discussed for link layer protocols, even routing strategies at the network layer address challenges rising directly from signal propagation. One of the main concerns addressed by the literature refers to network clustering, aimed to achieve a convenient nodes grouping and optimize signal path selection. In [45], the authors present a tree-topological based UWSN where nodes exploit packet flooding to get continuously updated information about neighbors availability, so that packet routing and reconfiguration can be performed efficiently and adaptively with respect to the current network status. In [46], nodes clustering is instead realized by resorting to the \(k\)-means algorithm. Furthermore, by resorting to AF and MRC at the physical layer, a reliable data transfer is provided that, in general, leads to network energy efficiency and throughput improvement. A clustering algorithm oriented to energy optimization is also proposed in [47] for multi-hop network scenarios, where nodes management and path selection are performed based on several information, including the number of neighbor nodes,the nodes residual energy and their distance from the reference sink node. Following a similar approach, a cost function taking into account nodes distance and residual energy is considered in [48] to realize an optimal clustering and routing. Spatial diversity is also exploited at the physical layer to increase the signal detection reliability. Several works in the literature investigate routing by referring to network scenarios with nodes location awareness, hence path selection is performed essentially based on channel conditions. An example is given in [49], where a multi-sector nodes deployment and sink mobility are considered to handle an energy efficient data routing, supported by cooperative DF to improve the network reliability. Channel awareness also exploited in [50; 51], where a cross-layer strategy involving routing relays for packet forwarding and cooperative relays for signaling is proposed. The first ones are selected based on the link capacity, while the second ones are suitably chosen to conveniently realize DF and mitigate the signal propagation impairments. Network nodes clustering and sink mobility are jointly considered in [52]. Here, a sink node operates data collection from sensor nodes located in a specific network area, by eventually resorting to physical layer cooperation in order to improve the link robustness to errors, and forwards the information to the destination node. So the presence of a mobile sink avoids the use unreliable direct links between end nodes, thus improving nodes lifespan, throughput and delay performance. Other approaches to underwater routing consider nodes location unawareness, as for example in [53]. The authors propose in fact two energy efficient routing protocols where path selection is performed based on nodes residual energy, number of hops and the bit error rate measured on the link.