## 4 Cluster Sleep-Wake Scheduling Algorithm
### Cluster Sleep-Wake Scheduling Algorithm
#### 4.3.4 Description of the Algorithm
Given the emergence of redundant nodes in the network, operations such as waking up working nodes, sleeping useless nodes, and rotating temporary control nodes were performed to save network energy consumption and extend the network lifetime cycle. Finally, a UWSN with good coverage, connectivity, and network lifetime cycle was obtained. Simulation experiments revealed that compared with random deployment, the proposed algorithm performed better in connectivity, coverage, and network lifetime cycle. Compared with the depth adjustment algorithm in the same underwater 3D environment, the algorithm also had advantages in coverage. In UWSN, excellent topology control ensures network coverage and connectivity. Due to the complex underwater environment, using a 3D coordinate system to study UWSNs is realistic and has research value. The scheduling algorithm designed in this paper, based on the network's 3D topology control, analyzes residual node energy and connectivity and sets the node's sleep and wake time. Simulation results indicate that, under the same experimental conditions, the proposed algorithm has better coverage and connectivity than the random deployment algorithm. The sleep-wake mechanism of the working node in the algorithm can prolong the network life cycle. Simulation results also show that the cluster sleep-wake scheduling algorithm is more efficient compared with other similar topology control algorithms. [PERSON] researched the literatures, conceived the study concepts, designed underwater wireless sensor network model, proposed the topology control and the cluster sleep-wake scheduling algorithm, carried out the simulation, analyzed the simulation results, and took charge of the entire manuscripts. [PERSON] and [PERSON] assisted with the integrity of the entire study, provided the crucial intellectual support, and revised the manuscript. [PERSON] contributed to compute the size of partition unit and cluster. [PERSON] contributed to polish the revised manuscript. Figure 16:0 Relationship between the packet loss rate and time. **Funding:** The work is supported by \"Liaoning fourth bulk transfer of distinguished professor project (2014)\" and \"Liaoning distinguished professor project (2017)\" and supported by \"Liaoning BaiQianWan Talents Program (2016)\" and supported by \"Natural Science Foundation of Liaoning Province Project Grant No. 20170540793\" and supported by \"Program for Liaoning Excellent Talents in University (LR2017009)\" and supported by \"Fundamental Research Funds for the Central Universities (No. DUT17 RC(3)094)\" and supported by \"general project of Liaoning province Grant No. 2015465\" and supported by \"open foundation project of Shenyang Ligong University\" and supported by the National Natural Science Foundation of China under Grant (No. 61572172, No. 61872124) and supported by the National Natural Science Foundation of China-Guangdong Joint Fund (No. U1801264). **Conflicts of Interest:** The authors declare no conflict of interest. ## References

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