Enhanced QoS routing protocol for an unmanned ground vehicle, based on the ACO approach
Improving models for managing the networks of firefighting unmanned ground vehicles in crowded areas, as a recommendation system (RS), represented a difficult challenge. This challenge comes from the peculiarities of these types of networks. These networks are distinguished by the network coverage a...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI
2023
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| Subjects: | |
| Online Access: | http://eprints.utm.my/106921/1/AliMAli2023_EnhancedQoSRoutingProtocolforanUnmanned.pdf |
| _version_ | 1811132438009610240 |
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| author | M. Ali, Ali Ngadi, Md. Asri Sham, Rohana Al_Barazanchi, Israa Ibraheem |
| author_facet | M. Ali, Ali Ngadi, Md. Asri Sham, Rohana Al_Barazanchi, Israa Ibraheem |
| author_sort | M. Ali, Ali |
| collection | ePrints |
| description | Improving models for managing the networks of firefighting unmanned ground vehicles in crowded areas, as a recommendation system (RS), represented a difficult challenge. This challenge comes from the peculiarities of these types of networks. These networks are distinguished by the network coverage area size, frequent network connection failures, and quick network structure changes. The research aims to improve the communication network of self-driving firefighting unmanned ground vehicles by determining the best routing track to the desired fire area. The suggested new model intends to improve the RS regarding the optimum tracking route for firefighting unmanned ground vehicles by employing the ant colony optimization technique. This optimization method represents one of the swarm theories utilized in vehicles ad–hoc networks and social networks. According to the results, the proposed model can enhance the navigation of self-driving firefighting unmanned ground vehicles towards the fire region, allowing firefighting unmanned ground vehicles to take the shortest routes possible, while avoiding closed roads and traffic accidents. This study aids in the control and management of ad–hoc vehicle networks, vehicles of everything, and the internet of things. |
| first_indexed | 2024-09-24T00:04:12Z |
| format | Article |
| id | utm.eprints-106921 |
| institution | Universiti Teknologi Malaysia - ePrints |
| language | English |
| last_indexed | 2024-09-24T00:04:12Z |
| publishDate | 2023 |
| publisher | MDPI |
| record_format | dspace |
| spelling | utm.eprints-1069212024-08-04T07:12:14Z http://eprints.utm.my/106921/ Enhanced QoS routing protocol for an unmanned ground vehicle, based on the ACO approach M. Ali, Ali Ngadi, Md. Asri Sham, Rohana Al_Barazanchi, Israa Ibraheem QA75 Electronic computers. Computer science Improving models for managing the networks of firefighting unmanned ground vehicles in crowded areas, as a recommendation system (RS), represented a difficult challenge. This challenge comes from the peculiarities of these types of networks. These networks are distinguished by the network coverage area size, frequent network connection failures, and quick network structure changes. The research aims to improve the communication network of self-driving firefighting unmanned ground vehicles by determining the best routing track to the desired fire area. The suggested new model intends to improve the RS regarding the optimum tracking route for firefighting unmanned ground vehicles by employing the ant colony optimization technique. This optimization method represents one of the swarm theories utilized in vehicles ad–hoc networks and social networks. According to the results, the proposed model can enhance the navigation of self-driving firefighting unmanned ground vehicles towards the fire region, allowing firefighting unmanned ground vehicles to take the shortest routes possible, while avoiding closed roads and traffic accidents. This study aids in the control and management of ad–hoc vehicle networks, vehicles of everything, and the internet of things. MDPI 2023-01-28 Article PeerReviewed application/pdf en http://eprints.utm.my/106921/1/AliMAli2023_EnhancedQoSRoutingProtocolforanUnmanned.pdf M. Ali, Ali and Ngadi, Md. Asri and Sham, Rohana and Al_Barazanchi, Israa Ibraheem (2023) Enhanced QoS routing protocol for an unmanned ground vehicle, based on the ACO approach. Sensors, 23 (3). pp. 1-13. ISSN 1424-8220 http://dx.doi.org/10.3390/s23031431 DOI:10.3390/s23031431 |
| spellingShingle | QA75 Electronic computers. Computer science M. Ali, Ali Ngadi, Md. Asri Sham, Rohana Al_Barazanchi, Israa Ibraheem Enhanced QoS routing protocol for an unmanned ground vehicle, based on the ACO approach |
| title | Enhanced QoS routing protocol for an unmanned ground vehicle, based on the ACO approach |
| title_full | Enhanced QoS routing protocol for an unmanned ground vehicle, based on the ACO approach |
| title_fullStr | Enhanced QoS routing protocol for an unmanned ground vehicle, based on the ACO approach |
| title_full_unstemmed | Enhanced QoS routing protocol for an unmanned ground vehicle, based on the ACO approach |
| title_short | Enhanced QoS routing protocol for an unmanned ground vehicle, based on the ACO approach |
| title_sort | enhanced qos routing protocol for an unmanned ground vehicle based on the aco approach |
| topic | QA75 Electronic computers. Computer science |
| url | http://eprints.utm.my/106921/1/AliMAli2023_EnhancedQoSRoutingProtocolforanUnmanned.pdf |
| work_keys_str_mv | AT maliali enhancedqosroutingprotocolforanunmannedgroundvehiclebasedontheacoapproach AT ngadimdasri enhancedqosroutingprotocolforanunmannedgroundvehiclebasedontheacoapproach AT shamrohana enhancedqosroutingprotocolforanunmannedgroundvehiclebasedontheacoapproach AT albarazanchiisraaibraheem enhancedqosroutingprotocolforanunmannedgroundvehiclebasedontheacoapproach |