Modified Ant Colony Optimization to Improve Energy Consumption of Cruiser Boundary Tour with Internet of Underwater Things

The Internet of Underwater Things (IoUT) holds significant promise for developing a smart ocean. In recent years, there has been swift progress in data collection methods using autonomous underwater vehicles (AUVs) within underwater acoustic sensor networks (UASNs). One of the key challenges in the...

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Main Authors: Hadeel Mohammed, Mustafa Ibrahim, Ahmed Raoof, Amjad Jaleel, Ayad Q. Al-Dujaili
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Computers
Subjects:
Online Access:https://www.mdpi.com/2073-431X/14/2/74
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author Hadeel Mohammed
Mustafa Ibrahim
Ahmed Raoof
Amjad Jaleel
Ayad Q. Al-Dujaili
author_facet Hadeel Mohammed
Mustafa Ibrahim
Ahmed Raoof
Amjad Jaleel
Ayad Q. Al-Dujaili
author_sort Hadeel Mohammed
collection DOAJ
description The Internet of Underwater Things (IoUT) holds significant promise for developing a smart ocean. In recent years, there has been swift progress in data collection methods using autonomous underwater vehicles (AUVs) within underwater acoustic sensor networks (UASNs). One of the key challenges in the IoUT is improving both the energy consumption (EC) of underwater vehicles and the value of information (VoI) necessary for completing missions while gathering sensing data. In this paper, a hybrid optimization technique is proposed based on boundary tour modified ant colony optimization (BTMACO). The proposed optimization algorithm was developed to solve the challenging problem of determining the optimal path of an AUV visiting all sensor nodes with minimum energy consumption. The optimization algorithm specifies the best order in which to visit all the sensor nodes, while it also works to adjust the AUV’s information-gathering locations according to the permissible data transmission range. Compared with the related works in the literature, the proposed method showed better performance, and it can find the best route through which to collect sensor information with minimum power consumption and a 6.9% better VoI.
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publisher MDPI AG
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series Computers
spelling doaj-art-1a7c59d3965d45eeae03921e0b38cbe52025-08-20T02:44:59ZengMDPI AGComputers2073-431X2025-02-011427410.3390/computers14020074Modified Ant Colony Optimization to Improve Energy Consumption of Cruiser Boundary Tour with Internet of Underwater ThingsHadeel Mohammed0Mustafa Ibrahim1Ahmed Raoof2Amjad Jaleel3Ayad Q. Al-Dujaili4Department of Vocational Education, Iraq Ministry of Education, Baghdad 10001, IraqElectronic Computer Center, Al-Nahrain University, Jadriya, Baghdad 10001, IraqControl and Systems Engineering Department, University of Technology, Baghdad 10001, IraqControl and Systems Engineering Department, University of Technology, Baghdad 10001, IraqElectrical Engineering Technical College, Middle Technical University, Baghdad 10001, IraqThe Internet of Underwater Things (IoUT) holds significant promise for developing a smart ocean. In recent years, there has been swift progress in data collection methods using autonomous underwater vehicles (AUVs) within underwater acoustic sensor networks (UASNs). One of the key challenges in the IoUT is improving both the energy consumption (EC) of underwater vehicles and the value of information (VoI) necessary for completing missions while gathering sensing data. In this paper, a hybrid optimization technique is proposed based on boundary tour modified ant colony optimization (BTMACO). The proposed optimization algorithm was developed to solve the challenging problem of determining the optimal path of an AUV visiting all sensor nodes with minimum energy consumption. The optimization algorithm specifies the best order in which to visit all the sensor nodes, while it also works to adjust the AUV’s information-gathering locations according to the permissible data transmission range. Compared with the related works in the literature, the proposed method showed better performance, and it can find the best route through which to collect sensor information with minimum power consumption and a 6.9% better VoI.https://www.mdpi.com/2073-431X/14/2/74internet of underwater things (IoUT)autonomous underwater vehicle (AUV)value of information (VoI)energy efficiencymodified ant colony optimization (MACO) algorithm
spellingShingle Hadeel Mohammed
Mustafa Ibrahim
Ahmed Raoof
Amjad Jaleel
Ayad Q. Al-Dujaili
Modified Ant Colony Optimization to Improve Energy Consumption of Cruiser Boundary Tour with Internet of Underwater Things
Computers
internet of underwater things (IoUT)
autonomous underwater vehicle (AUV)
value of information (VoI)
energy efficiency
modified ant colony optimization (MACO) algorithm
title Modified Ant Colony Optimization to Improve Energy Consumption of Cruiser Boundary Tour with Internet of Underwater Things
title_full Modified Ant Colony Optimization to Improve Energy Consumption of Cruiser Boundary Tour with Internet of Underwater Things
title_fullStr Modified Ant Colony Optimization to Improve Energy Consumption of Cruiser Boundary Tour with Internet of Underwater Things
title_full_unstemmed Modified Ant Colony Optimization to Improve Energy Consumption of Cruiser Boundary Tour with Internet of Underwater Things
title_short Modified Ant Colony Optimization to Improve Energy Consumption of Cruiser Boundary Tour with Internet of Underwater Things
title_sort modified ant colony optimization to improve energy consumption of cruiser boundary tour with internet of underwater things
topic internet of underwater things (IoUT)
autonomous underwater vehicle (AUV)
value of information (VoI)
energy efficiency
modified ant colony optimization (MACO) algorithm
url https://www.mdpi.com/2073-431X/14/2/74
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AT ahmedraoof modifiedantcolonyoptimizationtoimproveenergyconsumptionofcruiserboundarytourwithinternetofunderwaterthings
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