## 3 Underwater Routing Protocols
### Localization-Free Routing Protocols
#### 3.2.3 Protocols Mitigating Channel Conditions  
DEAC  
The depth- and energy-aware cooperative (DEAC) routing protocol uses cooperative communications to avoid data corruption by the underwater medium [55]. The protocol adaptively selects a depth threshold for a source node based on its number of alive neighbors. Following this, a relay node is selected within the depth threshold based on its residual energy, number of neighbors and link state. The destination node is selected out of the depth threshold. The protocol performs well in terms of packets received at the sink. However, it is energy inefficient due to cooperative routing.  
DBR-NC  
Depth-based routing network coding (DBR-NC) improves the energy cost of packets transmission, delay and packets' reliability in the original DBR scheme. The network coding takes into account the adverse channel effects to ensure reliability. However, the protocol assumes an ideal MAC layer compared to the realistic MAC layer in DBR [56].  
QERP  
The authors in [57] proposed a quality-of-service (QoS)-aware evolutionary cluster-based routing protocol (QERP) to mitigate the adverse channel effects in underwater communications. The protocol uses the genetic algorithm, divides the network into clusters and specifies the cluster heads and the routing paths from the routing tables that nodes share with one another. Packet delivery ratio, end-to-end delay and energy consumption are improved. However, the load on the cluster heads makes them depleted of energy at the early stage, which creates energy holes in the network and degrades system performance.  
RIAR  
[PERSON] and his colleagues propose a reliable and interference-aware routing (RIAR) protocol to mitigate the unwanted link effects in routing data from the source to the destination [58]. A source node selects a relay node on the basis of its number of hops from the surface sink, neighbors and the greatest distance from the source to the relay node. These parameters are combined to propose a cost function. A relay node with the highest value of the cost function is the suitable candidate for data forwarding. The protocol performs well in sparse networks in terms of throughput, energy consumption and end-to-end delay. However, it causes early the death of nodes close to the water surface, which reduces the number of successful packets received at the sink.  
EEIRA  
To address interference during packet forwarding, an energy-efficient interference- and route-aware (EEIRA) protocol is proposed in [59]. The protocol selects forwarder nodes based on the lowest depth and the least number of neighbors of the forwarder nodes. These parameters ensure efficient utilization of energy and reduced interference. However, the protocol performs poorly in sparse conditions where the selection of forwarder nodes with the least number of neighbors increases the probability of not finding a forwarder node by a sensor node.  
EECOR  
The authors in [60] use cooperative opportunistic routing to mitigate adverse channel conditions during packet forwarding. The cooperative routing ensures that the destination receives copies of the same data packets from the source and the relay for reliable reception of the packets. The opportunistic routing ensures that a certain set of the best forwarder nodes is chosen for data forwarding rather thanselecting a single forwarder node. The forwarder nodes are selected based on fuzzy logic. The protocol shows promising performance in terms of packet delivery, energy consumption and end-to-end delay. However, constant checking and selection of the forwarder set add extra delay.