A survey on localization and energy efficiency in UWSN: bio-inspired approach
Abstract The underwater wireless sensor networks (UWSNs) area is a developing area of research since there are tremendous opportunities like surveying marine life, installing and monitoring optical cables, detecting earthquakes, and surveillance of territorial borders. Though many applications exist...
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Springer
2024-11-01
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| Series: | Discover Applied Sciences |
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| Online Access: | https://doi.org/10.1007/s42452-024-06318-x |
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| author | J. Murali T. Shankar |
| author_facet | J. Murali T. Shankar |
| author_sort | J. Murali |
| collection | DOAJ |
| description | Abstract The underwater wireless sensor networks (UWSNs) area is a developing area of research since there are tremendous opportunities like surveying marine life, installing and monitoring optical cables, detecting earthquakes, and surveillance of territorial borders. Though many applications exist, underwater research explored to date is less than five percent as it poses many issues and challenges like water currents, temperature, pressure, water salinity, disturbance by aquatic animals, and many more factors that affect the performance of sensors deployed inside water. A significant issue UWSNs face is focusing on energy efficiency to extend the life of submerged sensors placed in isolated areas. Resolving localization concerns is a primary additional concern. In this comprehensive survey, the basics of UWSNs are covered in the introduction, followed by a thorough literature review of the existing works mainly focusing on localization, energy efficiency, Bio-inspired algorithms (BIA), and the impact of implementing Machine Learning (ML) are discussed. In concurrent sections, we have discussed attributes, parameters useful for analysis, issues and challenges in UWSN, soft computing techniques, software and hardware tools available for extended research, and opportunities in UWSN. The researchers could gain perspective pathways at the end of this survey. |
| format | Article |
| id | doaj-art-80b994a5ef6444019da0d8a8cac0a1d1 |
| institution | OA Journals |
| issn | 3004-9261 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Springer |
| record_format | Article |
| series | Discover Applied Sciences |
| spelling | doaj-art-80b994a5ef6444019da0d8a8cac0a1d12025-08-20T02:33:08ZengSpringerDiscover Applied Sciences3004-92612024-11-0161214210.1007/s42452-024-06318-xA survey on localization and energy efficiency in UWSN: bio-inspired approachJ. Murali0T. Shankar1School of Electronics Engineering, Vellore Institute of TechnologySchool of Electronics Engineering, Vellore Institute of TechnologyAbstract The underwater wireless sensor networks (UWSNs) area is a developing area of research since there are tremendous opportunities like surveying marine life, installing and monitoring optical cables, detecting earthquakes, and surveillance of territorial borders. Though many applications exist, underwater research explored to date is less than five percent as it poses many issues and challenges like water currents, temperature, pressure, water salinity, disturbance by aquatic animals, and many more factors that affect the performance of sensors deployed inside water. A significant issue UWSNs face is focusing on energy efficiency to extend the life of submerged sensors placed in isolated areas. Resolving localization concerns is a primary additional concern. In this comprehensive survey, the basics of UWSNs are covered in the introduction, followed by a thorough literature review of the existing works mainly focusing on localization, energy efficiency, Bio-inspired algorithms (BIA), and the impact of implementing Machine Learning (ML) are discussed. In concurrent sections, we have discussed attributes, parameters useful for analysis, issues and challenges in UWSN, soft computing techniques, software and hardware tools available for extended research, and opportunities in UWSN. The researchers could gain perspective pathways at the end of this survey.https://doi.org/10.1007/s42452-024-06318-xBio-inspired algorithmsEnergy efficiency algorithmsLocalizationMachine learningSoft computingUnderwater wireless sensor networks |
| spellingShingle | J. Murali T. Shankar A survey on localization and energy efficiency in UWSN: bio-inspired approach Discover Applied Sciences Bio-inspired algorithms Energy efficiency algorithms Localization Machine learning Soft computing Underwater wireless sensor networks |
| title | A survey on localization and energy efficiency in UWSN: bio-inspired approach |
| title_full | A survey on localization and energy efficiency in UWSN: bio-inspired approach |
| title_fullStr | A survey on localization and energy efficiency in UWSN: bio-inspired approach |
| title_full_unstemmed | A survey on localization and energy efficiency in UWSN: bio-inspired approach |
| title_short | A survey on localization and energy efficiency in UWSN: bio-inspired approach |
| title_sort | survey on localization and energy efficiency in uwsn bio inspired approach |
| topic | Bio-inspired algorithms Energy efficiency algorithms Localization Machine learning Soft computing Underwater wireless sensor networks |
| url | https://doi.org/10.1007/s42452-024-06318-x |
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