Trilateration and Multiverse Optimization-Based 3D Localization for Underwater Wireless Sensor Networks in Shadow Environment.
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| Title: | Trilateration and Multiverse Optimization-Based 3D Localization for Underwater Wireless Sensor Networks in Shadow Environment. |
|---|---|
| Authors: | Rani, Seema1 (AUTHOR) seema.singroha@gmail.com, Sangwan, Anju1 (AUTHOR) anju.sangwan@yahoo.com |
| Source: | Wireless Personal Communications. Jul2025, Vol. 143 Issue 1/2, p1-34. 34p. |
| Subjects: | Localization theory, Optimization algorithms, Mathematical optimization, Triangulation, Underwater acoustic communication |
| Abstract: | Localization is one prime invention in Underwater Wireless Sensor Networks (UWSNs) as it is essential in many applications. Sensors deployed beneath water detect underwater events and convey the detected data to the base station. This data becomes valuable only when the exact location of the object is known. For localization, GPS (Global Positioning System) signals do not spread across water due to the different environmental conditions. For that reason, calculating the location of the nodes should be done using another GPS-less scheme. However, these schemes have high communication costs and their efficacy is affected by propagation delays, attenuation, multipath interference, shadowing etc. All these issues make it necessary to develop a novel localization scheme. The paper presents a novel UWSNs localization method, merging trilateration and Multiverse Optimization (MVO), while considering shadowing effects. MVO is a nature-inspired optimization algorithm that simulates the concept of multiple universes and their interactions. It introduces a level of diversity and adaptability that might make it advantageous in certain situations, including underwater localization. This scheme initially employs trilateration to estimate the sensor node's location, followed by refining its position through error minimization using MVO. The network is simulated, then error rate and accuracy of the proposed localization method is evaluated. Results from the MVO optimization scenario are anticipated to demonstrate enhanced communication reliability, reduced error rates, potentially decreased time consumption, and lower average energy consumption compared to non-optimization, GA(Genetic Algorithm), PSO(Particle Swarm Optimization), COA(Cuckoo Optimization Algorithm) scenarios. Moreover, error rate and accuracy are simulated considering the shadowing factor in the case of conventional approach, GA, PSO, COA and compared it to the MVO. [ABSTRACT FROM AUTHOR] |
| Copyright of Wireless Personal Communications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 188798308 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Trilateration and Multiverse Optimization-Based 3D Localization for Underwater Wireless Sensor Networks in Shadow Environment. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Rani%2C+Seema%22">Rani, Seema</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> seema.singroha@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Sangwan%2C+Anju%22">Sangwan, Anju</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> anju.sangwan@yahoo.com</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Wireless+Personal+Communications%22">Wireless Personal Communications</searchLink>. Jul2025, Vol. 143 Issue 1/2, p1-34. 34p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Localization+theory%22">Localization theory</searchLink><br /><searchLink fieldCode="DE" term="%22Optimization+algorithms%22">Optimization algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+optimization%22">Mathematical optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Triangulation%22">Triangulation</searchLink><br /><searchLink fieldCode="DE" term="%22Underwater+acoustic+communication%22">Underwater acoustic communication</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Localization is one prime invention in Underwater Wireless Sensor Networks (UWSNs) as it is essential in many applications. Sensors deployed beneath water detect underwater events and convey the detected data to the base station. This data becomes valuable only when the exact location of the object is known. For localization, GPS (Global Positioning System) signals do not spread across water due to the different environmental conditions. For that reason, calculating the location of the nodes should be done using another GPS-less scheme. However, these schemes have high communication costs and their efficacy is affected by propagation delays, attenuation, multipath interference, shadowing etc. All these issues make it necessary to develop a novel localization scheme. The paper presents a novel UWSNs localization method, merging trilateration and Multiverse Optimization (MVO), while considering shadowing effects. MVO is a nature-inspired optimization algorithm that simulates the concept of multiple universes and their interactions. It introduces a level of diversity and adaptability that might make it advantageous in certain situations, including underwater localization. This scheme initially employs trilateration to estimate the sensor node's location, followed by refining its position through error minimization using MVO. The network is simulated, then error rate and accuracy of the proposed localization method is evaluated. Results from the MVO optimization scenario are anticipated to demonstrate enhanced communication reliability, reduced error rates, potentially decreased time consumption, and lower average energy consumption compared to non-optimization, GA(Genetic Algorithm), PSO(Particle Swarm Optimization), COA(Cuckoo Optimization Algorithm) scenarios. Moreover, error rate and accuracy are simulated considering the shadowing factor in the case of conventional approach, GA, PSO, COA and compared it to the MVO. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Wireless Personal Communications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s11277-025-11816-1 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 34 StartPage: 1 Subjects: – SubjectFull: Localization theory Type: general – SubjectFull: Optimization algorithms Type: general – SubjectFull: Mathematical optimization Type: general – SubjectFull: Triangulation Type: general – SubjectFull: Underwater acoustic communication Type: general Titles: – TitleFull: Trilateration and Multiverse Optimization-Based 3D Localization for Underwater Wireless Sensor Networks in Shadow Environment. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Rani, Seema – PersonEntity: Name: NameFull: Sangwan, Anju IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 07 Text: Jul2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 09296212 Numbering: – Type: volume Value: 143 – Type: issue Value: 1/2 Titles: – TitleFull: Wireless Personal Communications Type: main |
| ResultId | 1 |
