# Cooperative Position Aware Mobility Pattern of AUVs for Avoiding Void Zones in Underwater WSNs
## 2 Related Work
### Cooperative Routing Protocols  
Cooperative routing takes the benefit of the broadcast nature of wireless communication in which the transmitted signal is overheard by unintended sensor nodes within the transmission range. It is an alternate to multi-hop communication for reducing link impairments and fading. In [21], the authors propose an opportunistic routing protocol for UWSNs. They used the local topology information and adopted a greedy method for finding the set of nodes that made maximum progress with limited hidden terminals. In order to minimize hidden terminals, relay nodes are selected as the destination. The authors propose in [22] a mathematical model for cooperative routing in UWSNs to reduce the end to end delay by calculating the dominating set (DS) of a given network as a digraph. The DS formation allows the optimal formation of sensor nodes for cooperative routing; it reduces the communication overhead and minimizes the energy consumption of the network. In [23], the authors propose the cross-layer minimum collision cooperative routing (MCCR) algorithm for cooperative transmission and power allocation to overcome collision probability. [PERSON] et al. [24] propose a cooperative transmission routing protocol for UWSNs. The forwarder nodes are selected on the bases of distance cost and local measurement of the channel information. This routing protocol considers cooperative transmission at the routing layer, as well as cooperative transmission at the physical layer. In [25], the authors propose a cooperative routing protocol in which it is first determined whether cooperative routing is required or not. If required, an optimal relay is selected, which fulfills the SNR constraints. In addition, the Bellman-Ford routing technique along with mixed integer linear programming (MILP) are also used to achieve the minimum energy consumption during cooperative routing. In [26], the authors propose a collision minimization strategy using cooperative routing. They formulated the problem using mixed integer non-linear programming (MINLP). In this scheme, MINLP problems are solved by minimizing the search space with branch and bound algorithm. The authors propose [27] to achieve energy efficiency by allocating power at each hop from the source \begin{table}
\begin{tabular}{p{85.4 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline
**Technique** & **Features** & **Achievements** & **Limitations** \\ \hline Pressure routing for UASNs [21] & Cooperative routing and relay nodes are selected that are facing towards the destination & High throughput & High energy consumption \\ \hline Depth and Energy Aware Dominating Set [22] & Single and multiple relay cooperative routing & High throughput and low packet drop ratio & High energy consumption \\ \hline MCCR [23] & Cross-layer cooperative routing & Minimized collision & High end to end delay \\ \hline Cooperative transmission [24] & Cooperative routing in a multi-hop network & Increased the packet delivery ratio and reduced the end-to-end delay & Nodes with reliable link die quickly \\ \hline Optimal schemes [26] & Formulated problem with MINLP and solved using branch and bound algorithm & Reduced search space of the algorithm & The mechanism is not applicable to a dynamic topology \\ \hline Co-UWSN [27] & Destination and relay node are selected using cost function, which depends on distance and SNR of the link & Considerable low end to end delay and less energy consumption & Redundant data forwarding and ACK mechanism on every packet is costly \\ \hline \end{tabular}
\end{table} 
Table 3: Performance tradeoffs in existing cooperation-based routing protocols. UASN, underwater acoustic sensor network; MCCR, minimum collision cooperative routing. to the destination. Each node calculates its cost function based on the residual energy, distance and SNR of the link. This routing protocol is efficient in terms of end to end delay and network lifetime.