# Cognitive Routing in Software-Defined Underwater Acoustic Networks
## 2 Related Work
The whole network topology is divided into subregions where a cluster head in each sub region is responsible for gathering and transmission of data to the next upper region. AUV-aided routing method integrated path planning (AA-RP) [18] integrated the AUV's dynamic path planning algorithms into the routing protocol. It utilized the cooperation of sensor nodes to reduce energy consumption by selecting gateway nodes (GNs) as agents of AUVs, which communicate with the AUVs when ordinary sensor nodes fail to make connections. The AUVs are mobile sink nodes that forward data from sensor nodes to the surface of the ocean. None of these routing protocols for underwater sensor networks considered spectrum scarcity issues caused by limited communications frequencies. Proposing a cognitive routing protocol that takes the spectrum scarcity issue into account is essential in order to meet the increasing demands of underwater acoustic users. [PERSON] et al. [19] proposed a novel medium access control (MAC) protocol, called dynamic control channel MAC (DCC-MAC), by investigating the congestion of control channel in a UCAN. The important feature of this protocol is that each node could adjust and extend the bandwidth of its control channel by flexibly selecting proper data channels. A receiver-initiated spectrum management (RISM) [20] system is another protocol proposed for UCANs. It allows acoustic users to efficiently and courteously utilize the spectrum with both natural acoustic systems and artificial acoustic systems. The system increases the overall data transmission rate by combining a collision avoidance mechanism with joint power and channel allocation. Its results showed better performance for both the tree topology and the partially connected mesh topology by integrating spectrum sensing at the physical layer with spectrum sharing at the medium access control layer. [PERSON] et al. [21] proposed a cognitive acoustic transmission scheme, called dolphin-aware data transmission (DAD-Tx) to achieve the optimal end-to-end throughput with dolphin awareness. The protocol achieved better performance by modeling the dolphins' activities and mathematically describing the dolphin-awareness as a probabilistic constraint. OFDM-based spectrum-aware routing (OSAR) [22] was proposed to combine cognitive capability with a routing technique in order to overcome the problems of spectrum scarcity and high latency in underwater cognitive networks. Similarly, research in software-defined underwater networks is still very limited. SoftWater [23] was first introduced to facilitate such developments and to support a variety of applications for next-generation underwater sensor networks. With separation of the control and data planes, SoftWater provides a hardware infrastructure, software networking algorithms, heterogeneous underwater communications technologies, fault recovery schemes, and underwater mobility management. A software-defined network-based solution [4] was proposed to build an architecture for underwater networks in big data, which includes design of both the data plane and control plane. The study was supposed to maximize capacity, reduce management complexity, and provide technical support for underwater acoustic sensor networks. A new high data rate software-defined underwater acoustic networking platform, SEANet G2 (second generation) [24], was proposed to provide several benefits over existing underwater acoustic platforms. The study was designed to describe the hardware, software, and network architecture of the proposed platform. The design demonstrates data rates of 522 kbit/s achieved at sea over short horizontal links. [PERSON] et al. [25] discussed and reviewed the state-of-the-art security threats for underwater networks along with their existing solutions. The study addressed main research challenges related to the cooperation of static and mobile nodes and presented future solutions based on software-defined cognitive networking with the support for cross-layering communications and context-aware networking.