Cris Koutsougeras¹, Mohammad Y Saadeh² and Nikolaos I Xiros³

¹Department of Computer Science, Southeastern Louisiana University, Hammond, Louisiana, USA
²Department of Industrial and Engineering Technology, Southeastern Louisiana University, Hammond, Louisiana, USA
³Bollinger School of Naval Architecture and Marine Engineering Department of Electrical and Computer Engineering University of New Orleans, USA

*Corresponding Author: Nikolaos I Xiros, Bollinger School of Naval Architecture and Marine Engineering Department of Electrical and Computer Engineering University of New Orleans, USA.

Received: August 08, 2023; Published: August 17, 2023

Abstract

This work concerns communications for underwater (submerged) vessels. The stage consists of a set of underwater exploration vessels which are exploring cooperatively and need to communicate. The range of underwater signals is rather short, so a set of surface vessels (boats) is used to facilitate the communications. The surface vessels must position themselves properly so as to minimize the distance which signals must travel. Each surface vessel serves one group of the submerged vessels so this distance metric has to be optimized among all such groups (one for each surface vessel). As the underwater vessels move around, the surface vessels must also continually reposition accordingly. The issue at hand is how should the movement of the surface vessels be coordinated so as to optimize communications. In addition, the grouping (which of the submerged vessels is served by which surface boat) is not static; as the submerged vessels move around, this grouping may change dynamically. This complicates the problem and a good method is needed to handle the problem of controlling the topological distribution of the set of water surface boats in response to the independent movements of the submerged vessels.
This work is an application of unsupervised intelligent methods for the purpose of controlling/planning the surface boats positions in a coordinated way without centralized decision making. The self organizing maps are adopted to make the topological distribution of the surface vessels simulate the density distribution of the submerged vessels. The results are analyzed in the light of specific measures which relate to communication efficiency and clarity.

Keywords: Underwater Exploration; Self Organizing Maps; Unsupervised Intelligent Methods

References

1. "Editorial Underwater Acoustic Communications: Where We Stand and What Is Next?" IEEE Journal of Oceanic Engineering 44.1(2019): 1-6.
2. N Tang., et al. “Research on development and application of underwater acoustic communication system”. Journal of Physics Conference Series 1617(2020):  012036.
3. M Jahanbakht., et al. “Internet of underwater things and big marine data analytics -- a comprehensive survey". arXiv (2012): 06712.
4. T Kohonen. “Self-organized formation of topologically correct feature maps”. Biological Cybernetics 43(1982): 59-69.
5. T Kohonen. “The self-organizing map”. Proceedings IEEE 78(1990): 1464-1480.
6. F Murtagh and M Hernández-Pajares. “The Kohonen self-organizing map method: an assessment”. Journal        of Classification 12(1995): 165–190.
7. C Koutsougeras., et al. “Event-driven sensor deployment using selforganizing maps”. International Journal of Sensor Network 3.3 (2008): 142-151.
8. G Wang., et al. “Sensor relocation in mobile networks”. In Proc. IEEE 24^th Annual Joint Conference of the IEEE Computer and Communications Societies., Miami, FL, USA 4(2005): 2302-2312.
9. G Wang., et al. “Movement-assisted sensor deployment”. IEEE Transactions on Mobile Computing 5.6(2006): 640-652.
10. Arthur D and Vassilvitskii S. "k-means++: the advantages of careful seeding". In Proc. of The Eighteenth Annual ACM-SIAM Symposium on Discrete Algorithms. Society for Industrial and Applied Mathematics Philadelphia, PA, USA (2007): 1027-1035.

Citation

Citation: Nikolaos I Xiros., et al. “Positioning Surface Vessels for Underwater Communication using Self Organizing Maps". Acta Scientific Computer Sciences 5.9 (2023): 16-21.

Copyright

Copyright: © 2023 Nikolaos I Xiros., et al This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.