Dispersal Foraging Strategy With Cuckoo Search Optimization Based Path Planning in Unmanned Aerial Vehicle Networks
Unmanned aerial vehicles (UAVs) are assumed to be a promising model of automatic emergency tasks in dynamic marine ecosystems. But, the real-time communication efficacy betwixt UAVs and base platforms is developing a serious challenge. The compact-sized powerful flying robots can be wirelessly contr...
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10081355/ |
| _version_ | 1797853010272976896 |
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| author | Mofadal Alymani Hadeel Alsolai Mashael Maashi Adeeb Alhebri Hussain Alshahrani Fahd N. Al-Wesabi Abdullah Mohamed Manar Ahmed Hamza |
| author_facet | Mofadal Alymani Hadeel Alsolai Mashael Maashi Adeeb Alhebri Hussain Alshahrani Fahd N. Al-Wesabi Abdullah Mohamed Manar Ahmed Hamza |
| author_sort | Mofadal Alymani |
| collection | DOAJ |
| description | Unmanned aerial vehicles (UAVs) are assumed to be a promising model of automatic emergency tasks in dynamic marine ecosystems. But, the real-time communication efficacy betwixt UAVs and base platforms is developing a serious challenge. The compact-sized powerful flying robots can be wirelessly controlled and accomplish end tasks with and without human involvement. UAVs still face severe challenges that limit the dream of completely autonomous unmanned flying machines. The main difficulties contain path planning and hindrance avoidance of such unmanned flying robots, which are mandatory but carry out the application-specific functionality in either indoor or outdoor environments. This study introduces a new Dispersal Foraging Strategy with Cuckoo Search Optimization based Path Planning (DFSCSO-PP) technique for UAV networks. In the presented DFSCSO-PP technique, the identification of optimal paths for data transmission is performed in the UAV network. In addition, the presented DFSCSO-PP technique involves the optimal allocation of resources while finding the optimal paths in the network. Moreover, the DFSCSO technique can be designed by integrating the DFS concept into the CSO method to avoid local optima problems. A widespread simulation analysis is performed to exhibit the enhanced outcome of the DFSCSO-PP approach. A detailed set of comparative studies assured the improved performance of the DFSCSO-PP technique over other approaches. |
| first_indexed | 2024-04-09T19:43:41Z |
| format | Article |
| id | doaj.art-c76fac3a8a8146658e6fcc6067b0ed7a |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-09T19:43:41Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-c76fac3a8a8146658e6fcc6067b0ed7a2023-04-03T23:00:36ZengIEEEIEEE Access2169-35362023-01-0111313653137210.1109/ACCESS.2023.326216010081355Dispersal Foraging Strategy With Cuckoo Search Optimization Based Path Planning in Unmanned Aerial Vehicle NetworksMofadal Alymani0https://orcid.org/0009-0008-4830-6590Hadeel Alsolai1https://orcid.org/0000-0002-4897-8038Mashael Maashi2https://orcid.org/0000-0003-0446-5430Adeeb Alhebri3Hussain Alshahrani4https://orcid.org/0000-0001-9261-6133Fahd N. Al-Wesabi5https://orcid.org/0000-0002-4389-4927Abdullah Mohamed6Manar Ahmed Hamza7Department of Computer Engineering, College of Computing and Information Technology, Shaqra University, Shaqra, Saudi ArabiaDepartment of Information Systems, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, Riyadh, Saudi ArabiaDepartment of Software Engineering, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi ArabiaDepartment of Accounting, Applied College, King Khalid University, Mohail Asser, Saudi ArabiaDepartment of Computer Science, College of Computing and Information Technology, Shaqra University, Shaqra, Saudi ArabiaDepartment of Computer Science, College of Science and Art at Mahayil, King Khalid University, Abha, Saudi ArabiaResearch Centre, Future University in Egypt, New Cairo, EgyptDepartment of Computer and Self Development, Preparatory Year Deanship, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi ArabiaUnmanned aerial vehicles (UAVs) are assumed to be a promising model of automatic emergency tasks in dynamic marine ecosystems. But, the real-time communication efficacy betwixt UAVs and base platforms is developing a serious challenge. The compact-sized powerful flying robots can be wirelessly controlled and accomplish end tasks with and without human involvement. UAVs still face severe challenges that limit the dream of completely autonomous unmanned flying machines. The main difficulties contain path planning and hindrance avoidance of such unmanned flying robots, which are mandatory but carry out the application-specific functionality in either indoor or outdoor environments. This study introduces a new Dispersal Foraging Strategy with Cuckoo Search Optimization based Path Planning (DFSCSO-PP) technique for UAV networks. In the presented DFSCSO-PP technique, the identification of optimal paths for data transmission is performed in the UAV network. In addition, the presented DFSCSO-PP technique involves the optimal allocation of resources while finding the optimal paths in the network. Moreover, the DFSCSO technique can be designed by integrating the DFS concept into the CSO method to avoid local optima problems. A widespread simulation analysis is performed to exhibit the enhanced outcome of the DFSCSO-PP approach. A detailed set of comparative studies assured the improved performance of the DFSCSO-PP technique over other approaches.https://ieeexplore.ieee.org/document/10081355/Unmanned aerial vehiclesroute selectionpath planningcuckoo Searchautonomous system |
| spellingShingle | Mofadal Alymani Hadeel Alsolai Mashael Maashi Adeeb Alhebri Hussain Alshahrani Fahd N. Al-Wesabi Abdullah Mohamed Manar Ahmed Hamza Dispersal Foraging Strategy With Cuckoo Search Optimization Based Path Planning in Unmanned Aerial Vehicle Networks IEEE Access Unmanned aerial vehicles route selection path planning cuckoo Search autonomous system |
| title | Dispersal Foraging Strategy With Cuckoo Search Optimization Based Path Planning in Unmanned Aerial Vehicle Networks |
| title_full | Dispersal Foraging Strategy With Cuckoo Search Optimization Based Path Planning in Unmanned Aerial Vehicle Networks |
| title_fullStr | Dispersal Foraging Strategy With Cuckoo Search Optimization Based Path Planning in Unmanned Aerial Vehicle Networks |
| title_full_unstemmed | Dispersal Foraging Strategy With Cuckoo Search Optimization Based Path Planning in Unmanned Aerial Vehicle Networks |
| title_short | Dispersal Foraging Strategy With Cuckoo Search Optimization Based Path Planning in Unmanned Aerial Vehicle Networks |
| title_sort | dispersal foraging strategy with cuckoo search optimization based path planning in unmanned aerial vehicle networks |
| topic | Unmanned aerial vehicles route selection path planning cuckoo Search autonomous system |
| url | https://ieeexplore.ieee.org/document/10081355/ |
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