## 3 Proposed Quality of Service Routing Protocol (QoSRP) in UWSNs
### Underwater Acoustic Channel Assignment Algorithm (iiwca)  
The \(\mathcal{SU}_{3}\) for a channel \(\mathcal{C}_{i}\) sense the temporal non-existence of the \(\mathcal{PU}_{i}\) and find this channel busy if occupied. The \(\mathcal{SU}_{3}\) must leave the detected channel \(\mathcal{C}_{i}\) and immediately switch to an alternative channel \(\mathcal{C}_{j}\) by identifying the spectrum holes for transferring packets in UWSNs. The spectrum detecting approaches to find vacant spectrum bands can be categorized into a cooperative (CoS) and non-cooperative (NCoS) in UWSNs. In the CoS approach, the secondary users sense the vacant channels and cooperate closely with the neighboring secondary users to make the decision for the vacant channels in the network. In the NCoS, a secondary user makes the local decision for the vacant channels based on its own spectrum measurement in the UWSNS. The cooperative sensing can be individual (ICoS) or group-based (GCoS) sensing. In the ICoS mechanism, some randomly selected ASNs monitor the data transmission activities of a specific channel independently. By contrast, in the GCoS approach, a set of predefined ASNs is assigned to monitor the activities of a channel in a group. Consequently, the cooperative sensing based on the architecture can be divided into two types, namely centralized cooperative sensing (CCoS) and decentralized cooperative sensing (DCoS) [38]. In the CCoS approach, \(\mathcal{SU}_{3}\) for a channel \(\mathcal{C}_{i}\) sense the temporal nonexistence of the \(\mathcal{PU}_{i}\) and send their local observation data to a specialized fusion center, which combines the received channel results and decides the use of the channel \(\mathcal{C}_{i}\) for packets transmission. The specialized fusion centers periodically forward the local decision updates to neighboring specialized devices since they are aware of the existing vacant channels at any given time. Thus, the key aim of the specialized devices is to allocate vacant channels efficiently to \(\mathcal{SU}_{3}\) with least information message-sharing in the UWSNs. On the contrary, in the DCoS approach, secondary users sense the vacant channels and cooperate closely with the neighboring secondary users and make the decision without using the centralized device for the vacant channels in the network. The CCoS can considerably intensify the systems aptitude in identifying and evading the \(\mathcal{PU}\) signals in the network. However, it faces several issues such as high information exchange overheads and particular region cut off issues due to a single expert device failure, and overall network deployment cost due to the high price of these controllers. Thus, it could not be the best choice for the UWSNs. In this respect, the DCoS approach due to its flexibility in deployment for autonomous decision making seems to be the best choice for UWSNs. In DCoS, a set of \(\mathcal{SU}_{3}\) without the coordination of the centralized expert devices locally detects the \(\mathcal{PU}\) signals and maintains the spectrum information to make the decision by itself. In the proposed scheme, the DCoS overcomes the drawbacks of CCoS, but the sensing capabilities of \(\mathcal{SU}_{3}\) in DCoS are usually limited due to software-defined hardware limitations such as low computation, signal processing, memory, etc. The DCoS is further divided into restricted spectrum sensing (DRS) and whole spectrum sensing (DWS) [39]. The DRS allows secondary users to sense for the vacant channels in a specific region. Although, secondary users sequentially sense the specific region for available channels might raise the probability of detecting an available channel more quickly. However, the possibility of finding a poor capacity-aware channel with high interference also arises that affects the neighboring ASNs leading to low link qualities in the network. This results in packets loss, significant delay and degrades secondary users' throughput in the network.