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Underwater Wireless Sensor Networks Performance Comparison Utilizing Telnet and Superframe

Underwater Wireless Sensor Networks (UWSNs) have recently established themselves as an extremely interesting area of research thanks to the mysterious qualities of the ocean. The UWSN consists of sensor nodes and vehicles working to collect data and complete tasks. The battery capacity of sensor nod...

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Autores principales: Sathish, Kaveripakam, CV, Ravikumar, Ab Wahab, Mohd Nadhir, Anbazhagan, Rajesh, Pau, Giovanni, Akbar, Muhammad Firdaus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10224381/
https://www.ncbi.nlm.nih.gov/pubmed/37430763
http://dx.doi.org/10.3390/s23104844
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author Sathish, Kaveripakam
CV, Ravikumar
Ab Wahab, Mohd Nadhir
Anbazhagan, Rajesh
Pau, Giovanni
Akbar, Muhammad Firdaus
author_facet Sathish, Kaveripakam
CV, Ravikumar
Ab Wahab, Mohd Nadhir
Anbazhagan, Rajesh
Pau, Giovanni
Akbar, Muhammad Firdaus
author_sort Sathish, Kaveripakam
collection PubMed
description Underwater Wireless Sensor Networks (UWSNs) have recently established themselves as an extremely interesting area of research thanks to the mysterious qualities of the ocean. The UWSN consists of sensor nodes and vehicles working to collect data and complete tasks. The battery capacity of sensor nodes is quite limited, which means that the UWSN network needs to be as efficient as it can possibly be. It is difficult to connect with or update a communication that is taking place underwater due to the high latency in propagation, the dynamic nature of the network, and the likelihood of introducing errors. This makes it difficult to communicate with or update a communication. Cluster-based underwater wireless sensor networks (CB-UWSNs) are proposed in this article. These networks would be deployed via Superframe and Telnet applications. In addition, routing protocols, such as Ad hoc On-demand Distance Vector (AODV), Fisheye State Routing (FSR), Location-Aided Routing 1 (LAR1), Optimized Link State Routing Protocol (OLSR), and Source Tree Adaptive Routing—Least Overhead Routing Approach (STAR-LORA), were evaluated based on the criteria of their energy consumption in a range of various modes of operation with QualNet Simulator using Telnet and Superframe applications. STAR-LORA surpasses the AODV, LAR1, OLSR, and FSR routing protocols in the evaluation report’s simulations, with a Receive Energy of 0.1 mWh in a Telnet deployment and 0.021 mWh in a Superframe deployment. The Telnet and Superframe deployments consume 0.05 mWh transmit power, but the Superframe deployment only needs 0.009 mWh. As a result, the simulation results show that the STAR-LORA routing protocol outperforms the alternatives.
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spelling pubmed-102243812023-05-28 Underwater Wireless Sensor Networks Performance Comparison Utilizing Telnet and Superframe Sathish, Kaveripakam CV, Ravikumar Ab Wahab, Mohd Nadhir Anbazhagan, Rajesh Pau, Giovanni Akbar, Muhammad Firdaus Sensors (Basel) Article Underwater Wireless Sensor Networks (UWSNs) have recently established themselves as an extremely interesting area of research thanks to the mysterious qualities of the ocean. The UWSN consists of sensor nodes and vehicles working to collect data and complete tasks. The battery capacity of sensor nodes is quite limited, which means that the UWSN network needs to be as efficient as it can possibly be. It is difficult to connect with or update a communication that is taking place underwater due to the high latency in propagation, the dynamic nature of the network, and the likelihood of introducing errors. This makes it difficult to communicate with or update a communication. Cluster-based underwater wireless sensor networks (CB-UWSNs) are proposed in this article. These networks would be deployed via Superframe and Telnet applications. In addition, routing protocols, such as Ad hoc On-demand Distance Vector (AODV), Fisheye State Routing (FSR), Location-Aided Routing 1 (LAR1), Optimized Link State Routing Protocol (OLSR), and Source Tree Adaptive Routing—Least Overhead Routing Approach (STAR-LORA), were evaluated based on the criteria of their energy consumption in a range of various modes of operation with QualNet Simulator using Telnet and Superframe applications. STAR-LORA surpasses the AODV, LAR1, OLSR, and FSR routing protocols in the evaluation report’s simulations, with a Receive Energy of 0.1 mWh in a Telnet deployment and 0.021 mWh in a Superframe deployment. The Telnet and Superframe deployments consume 0.05 mWh transmit power, but the Superframe deployment only needs 0.009 mWh. As a result, the simulation results show that the STAR-LORA routing protocol outperforms the alternatives. MDPI 2023-05-17 /pmc/articles/PMC10224381/ /pubmed/37430763 http://dx.doi.org/10.3390/s23104844 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Sathish, Kaveripakam
CV, Ravikumar
Ab Wahab, Mohd Nadhir
Anbazhagan, Rajesh
Pau, Giovanni
Akbar, Muhammad Firdaus
Underwater Wireless Sensor Networks Performance Comparison Utilizing Telnet and Superframe
title Underwater Wireless Sensor Networks Performance Comparison Utilizing Telnet and Superframe
title_full Underwater Wireless Sensor Networks Performance Comparison Utilizing Telnet and Superframe
title_fullStr Underwater Wireless Sensor Networks Performance Comparison Utilizing Telnet and Superframe
title_full_unstemmed Underwater Wireless Sensor Networks Performance Comparison Utilizing Telnet and Superframe
title_short Underwater Wireless Sensor Networks Performance Comparison Utilizing Telnet and Superframe
title_sort underwater wireless sensor networks performance comparison utilizing telnet and superframe
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10224381/
https://www.ncbi.nlm.nih.gov/pubmed/37430763
http://dx.doi.org/10.3390/s23104844
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