Exploring optimal resource allocation methods for improved efficiency in flying ad-hoc network environments: a survey
This survey explores optimal resource allocation methods to enhance the efficiency of flying ad-hoc networks (FANETs). Unmanned aerial vehicles (UAVs), commonly known as drones, are widely deployed in military and civilian applications, necessitating effective coordination and communication to...
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2024
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Online Access: | http://irep.iium.edu.my/115193/7/115193_Exploring%20optimal%20resource%20allocation%20methods_SCOPUS.pdf http://irep.iium.edu.my/115193/8/115193_Exploring%20optimal%20resource%20allocation%20methods.pdf http://irep.iium.edu.my/115193/ https://ijece.iaescore.com/index.php/IJECE/article/view/36422/17794 http://doi.org/10.11591/ijece.v14i6.pp6433-6444 |
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my.iium.irep.1151932024-10-21T04:34:36Z http://irep.iium.edu.my/115193/ Exploring optimal resource allocation methods for improved efficiency in flying ad-hoc network environments: a survey Ahmed, Zeinab E. Abdalla Hashim, Aisha Hassan Saeed, Rashid A. Saeed, Mamoon Mohammed Ali TK7885 Computer engineering This survey explores optimal resource allocation methods to enhance the efficiency of flying ad-hoc networks (FANETs). Unmanned aerial vehicles (UAVs), commonly known as drones, are widely deployed in military and civilian applications, necessitating effective coordination and communication to overcome challenges. FANETs facilitate wireless communication among UAVs, improving coordination and information exchange in environments lacking traditional networks. The dynamic mobility of UAVs introduces unique considerations for network design and connectivity, distinguishing FANETs from conventional ad-hoc networks. This survey reviews various optimization techniques, including genetic algorithms, ant colony optimization, and artificial neural networks, which optimize resource allocation by considering mission requirements, network topology, and energy constraints. The paper also discusses the critical role of intelligent algorithms in enhancing network energy management, quality of service (QoS), maximizing resource allocation, and optimizing overall performance. The systematic literature review categorizes resource allocation strategies based on performance optimization criteria and summarizes their strengths, weaknesses, and applications. This survey highlights the potential of FANETs to revolutionize various industries and unlock new opportunities for UAV-based applications. Institute of Advanced Engineering and Science (IAES) 2024-12 Article PeerReviewed application/pdf en http://irep.iium.edu.my/115193/7/115193_Exploring%20optimal%20resource%20allocation%20methods_SCOPUS.pdf application/pdf en http://irep.iium.edu.my/115193/8/115193_Exploring%20optimal%20resource%20allocation%20methods.pdf Ahmed, Zeinab E. and Abdalla Hashim, Aisha Hassan and Saeed, Rashid A. and Saeed, Mamoon Mohammed Ali (2024) Exploring optimal resource allocation methods for improved efficiency in flying ad-hoc network environments: a survey. International Journal of Electrical and Computer Engineering (IJECE), 14 (6). pp. 6433-6444. ISSN 2088-8708 E-ISSN 2722-2578 https://ijece.iaescore.com/index.php/IJECE/article/view/36422/17794 http://doi.org/10.11591/ijece.v14i6.pp6433-6444 |
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TK7885 Computer engineering Ahmed, Zeinab E. Abdalla Hashim, Aisha Hassan Saeed, Rashid A. Saeed, Mamoon Mohammed Ali Exploring optimal resource allocation methods for improved efficiency in flying ad-hoc network environments: a survey |
description |
This survey explores optimal resource allocation methods to enhance the efficiency of flying ad-hoc
networks (FANETs). Unmanned aerial vehicles (UAVs), commonly known as drones, are widely deployed
in military and civilian applications, necessitating effective coordination and communication to
overcome challenges. FANETs facilitate wireless communication among UAVs, improving coordination
and information exchange in environments lacking traditional networks. The dynamic mobility of UAVs
introduces unique considerations for network design and connectivity, distinguishing FANETs from
conventional ad-hoc networks. This survey reviews various optimization techniques, including
genetic algorithms, ant colony optimization, and artificial neural networks, which optimize
resource allocation by considering mission requirements, network topology, and energy constraints.
The paper also discusses the critical role of intelligent algorithms in enhancing network energy
management, quality of service (QoS), maximizing resource allocation, and optimizing overall
performance. The systematic literature review categorizes resource allocation strategies based on
performance optimization criteria and summarizes their strengths, weaknesses, and applications.
This survey highlights the potential of FANETs to revolutionize various industries and unlock new
opportunities
for UAV-based applications. |
format |
Article |
author |
Ahmed, Zeinab E. Abdalla Hashim, Aisha Hassan Saeed, Rashid A. Saeed, Mamoon Mohammed Ali |
author_facet |
Ahmed, Zeinab E. Abdalla Hashim, Aisha Hassan Saeed, Rashid A. Saeed, Mamoon Mohammed Ali |
author_sort |
Ahmed, Zeinab E. |
title |
Exploring optimal resource allocation methods for improved efficiency in flying ad-hoc network environments: a survey |
title_short |
Exploring optimal resource allocation methods for improved efficiency in flying ad-hoc network environments: a survey |
title_full |
Exploring optimal resource allocation methods for improved efficiency in flying ad-hoc network environments: a survey |
title_fullStr |
Exploring optimal resource allocation methods for improved efficiency in flying ad-hoc network environments: a survey |
title_full_unstemmed |
Exploring optimal resource allocation methods for improved efficiency in flying ad-hoc network environments: a survey |
title_sort |
exploring optimal resource allocation methods for improved efficiency in flying ad-hoc network environments: a survey |
publisher |
Institute of Advanced Engineering and Science (IAES) |
publishDate |
2024 |
url |
http://irep.iium.edu.my/115193/7/115193_Exploring%20optimal%20resource%20allocation%20methods_SCOPUS.pdf http://irep.iium.edu.my/115193/8/115193_Exploring%20optimal%20resource%20allocation%20methods.pdf http://irep.iium.edu.my/115193/ https://ijece.iaescore.com/index.php/IJECE/article/view/36422/17794 http://doi.org/10.11591/ijece.v14i6.pp6433-6444 |
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1814042757849677824 |