## 4 Summary and Conclusions  
A new method for the optimal deployment of underwater sensor nodes, which can be applied to the UWASN, has been proposed in this paper. The algorithm includes four sub-algorithms, which are a routine for underwater acoustic channel modeling in temporally and spatially varying ocean environments, a routine for estimating the communication performance using the simulated underwater acoustic channels, a routine for constructing the communication PS, and a routine for searching for the optimal deployment of the sensor nodes on the PS. Most previous studies for the optimal deployment of sensor nodes have been performed under the assumption that the sensing range of every sensor node is the same without consideration of the spatial and temporal variations of the ocean environment. In contrast, the proposed method is an algorithm finding the optimal positions of sensor nodes using the communication radii extracted from the communication PS, which is the main difference from the previous algorithms. Moreover, it uses the VFPSO algorithm, which is a hybrid optimization method combining the advantages of the VFA and the PSO. Therefore, the sensor nodes are not placed in equidistant intervals. The optimal deployment based on the PS has been simulated for two different seasons for an area located off the eastern coast of Korea as the selected targeted area. As a result, the communication coverage rate in winter (February) was somewhat better than that in summer (August), implying that the optimal deployment scheme may vary with variations of the ocean environment. The algorithm does not propose the optimal number of sensor node, but it finds the optimal positions of sensor nodes for a given number of sensor nodes. In this paper, it was assumed that the communication channel was time invariant. If the system is used for a short time period using portable sensors such as sonobuoy-type devices, the ocean parameters corresponding to that time should be used as input parameters. However, if it is for the long-term ocean surveillance monitoring for a certain area, it is highly recommended to use the ocean environmental parameters producing the worst communication radii to obtain the robust deployment scheme and, in this case, the sensor nodes would be closer to each other. Also, it was assumed that the BPSK signal with a center frequency of 10 kHz was transmitted as a communication sequence and each sensor node was composed of a three-receiver array with an element spacing of 1.5 m. Other communication sequences [such as OFDM (Orthogonal Frequency Division Multiplexing)] or a different type of receiver system, which might be more robust to (frequency/time-selective)] fading channels, could provide better communication performance and produce a different deployment scheme; however, these are beyond the scope of this paper. Nevertheless, our algorithm can be applied to other types of communication sequences and receivers. Figure 12: Network connections of the sensor nodes after optimal deployment in (**a**) February and (**b**) August. In this paper, it was assumed that all sensor nodes were positioned near the seafloor. The depth change of the sensor nodes may yield a better communication performance, and in addition the combinations of different types of sensors, including AUV (Autonomous Underwater Vehicle), may improve the performance. The algorithm suggested herein can be extended to these cases, which will be our future work. This work was supported by the Agency for Defense Development, Korea (UD160006 DD), the National Research Foundation of Korea (NRF-2016R1D1A1B03930983) and the Ministry of Oceans and Fisheries (the project titled : Development of Distributed Underwater Monitoring & Control Networks). The authors would like to thank [PERSON] of Agency for Defense Development, Korea for helpful discussions concerning algorithm for optimal deployment of underwater sensor nodes.