## 6 Conclusions  
This paper developed a proposed DEDG 3D-UWSN with the aim of improving the network lifetime and reducing the delay. The key processes handled in this work to address this aim were: clustering with MO-SHO for optimal CH selection; member-balanced scheduling to allot sleep slots; three-step, inter-cluster routing with fuzzy-LeNet; DACP prediction in AUVs; and event message transmission. Initially, the 3D-UWSN environment is categorized into two levels relating to the depth of the ocean. The sensors in each level are clustered, and an optimal CH is selected by estimating the fitness with node's lifetime, degree and centrality. The optimal selection of CH results in the sustainability of the CH for a longer time, and it reduces the energy consumption for frequent CH selection. An equal number of members in the cluster is assigned to sleep mode and wakeup mode by energy consumption and the number of hops from the CH. The CH also reduces redundant data by measuring the Hassanat distance and eliminates similar data before forwarding it to the AUV. According to this proposed work, the CHs wait for a particular waiting time unless the AUV reaches a CH, then they request the gateway for an inter-cluster path. For path selection, the gateway identifies all the possible routes, then ignores longer routes, and, further, the filtered routes are validated using fuzzy-LeNet by considering energy consumption, fairness, synthesis speed and efficiency. This inter-cluster routing occurs in rare cases, since the movement of the AUV is predicted by two factors. These CH parameters are fed into DACP prediction followed by the estimation of the mid-point and then the AUV moves to collect data from the four CHs. Therefore, this reduces delay in data collection. This work also supports the transmission of event messages using a weighted method which selects a forwarder towards the AUV. The proposed DEDG 3D-UWSN showed better results in terms of energy efficiency and delay when compared with previous works.  
In future, this DEDG 3D-UWSN architecture is planned to be extended with network partitioning for further reduction of the energy consumption of sensors nodes. additionally, this environment will be tested in any specific application that exists for UWSNs.  
Conceptualization, R.A. and A.C.; methodology, M.S.A.M.; software, R.A.; validation, A.M. and A.C.; formal analysis, R.A.; investigation, M.A.A.; resources, N.A.S.; data curation, M.A.A.; writing--original draft preparation, A.C. and M.S.A.M.; writing--review and editing, D.P. and A.C.; visualization, A.M.; supervision, A.M.; project administration, R.A.; funding acquisition, D.P. and R.A. All authors have read and agreed to the published version of the manuscript.  
[PERSON] [PERSON] bint Abdulrahman University Researchers Supporting Project number (PNURSP2022R323), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia. Part of the reported study was funded by RFBR, project number 20-37-90131 (recipient [PERSON]).  
The data are contained within the article and/or available from the corresponding author upon reasonable request.  
The authors express their gratitude to Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2022R323), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.  
The authors declare no conflict of interest.