## 2 Related Work and Motivations
By supposing such strategy they simplified the case and performed all the simulations in the 2D sensing field. At the start of the network, AUV divides the field into several clusters via Voronoi generator point strategy and transmits this information throughout the network [21; 24; 25]. On receiving this information, FNs decide the cluster they will join for the current round. After cluster formation and association phase, a FN is selected as a cluster head on some predefined grounds. This selected head further splits the clusters into small groups of FNs called sub-clusters [26]. However, in each round, AUV travels twice in the network for network division and data collection which increase the operational costs. Additionally, the network pays energy cost twice for the head selection in each round and then further divided into sub-clusters. An AUV-aided underwater routing algorithm for UANs is introduced in [21]. This protocol utilized multiple numbers of AUVs with considering limited mobility in the heterogeneous acoustical channels. Authors supposed a 3D network by keeping the same depth level of all the deployed FNs. The AUV moves on a specified trajectory and stops on some fixed points to collect the data from all the FNs. Due to underwater severe conditions, deployed FNs are mobile and constantly changing their positions. These mobile FNs are considered as neighbors of the stop points. The AUV stops at the fixed points for a short time interval called the probe interval, to discover these mobile neighbors [21; 24; 25; 26]. After recognizing these mobile neighbors, the AUV generates a transmission scheduled for them. The AUV stays for a specific time at every stop to collect the data from all the neighbor FNs. However, this probe interval of recognizing and discovering the neighbor FNs introduce the data latency. In Hop-by-Hop Dynamic Addressing Based (H2-DAB) routing algorithm [22], the authors tried to handle the issues related to the mobility of FNs. The deployed FNs are considered at different depths, where these FNs can freely move in the horizontal directions, but the movements in vertical directions are negligible. The whole network is divided into different layers from the bottom of the ocean to the surface. The numbers of layers are depending on the transmission range of FNs and the field depth level. By taking into account the average depth of the ocean, they consider 5 to 7 layers to send data towards the surface sink. This data is forwarded from the bottom to the top in the form of a chain. However, the FNs closer to the surface sink are continuously forwarding the data of their predecessors and also sensing their fields. Because of which, theses forwarder FNs deplete their batteries earlier and this may lead to end the network lifetime [33]. The proposed model has some unique characteristics to deal with such problems and perform well in the harsh underwater requirements. In our designed model, data is forwarded to the SS according to the number of layers during a complete network tour. We engage the RHs to collect the frequently occurring data from the ocean bottom without causing the end-to-end delay. These deliberate RHs only collect the data from the Selected Member Nodes (SMNs) and forward the received data towards the MS after compressing it. The MS moves to a pre-defined trajectory such as from the ocean surface to the bottom and stops for a short period at each DCP to collect the data as described in Figure 1. According to the harsh underwater environment and necessities, the RTC scheme has some different features in comparison with previously designed approaches as follows:  
1. In previously designed cooperative communication models [5; 21; 22], the FNs closer to the SS deplete their batteries earlier than expected time duration due to continuous forwarding the data of their predecessors. In our designed scheme, the FNs closer to the SS directly communicate with it. However, the remainders of the FNs forward their data through the RH and the MS.
2.