Game Theory-Based UAV-Cloud for Service Selection Architecture in Flying Ad Hoc Networks
The rapid progression of Cloud Computing (CC) technology has ushered in innovative ecosystem concepts such as Mobile Cloud Computing (MCC). In this context, the incorporation of Unmanned Aerial Vehicles (UAVs) into these cloud ecosystems has unlocked new avenues for use cases such as delivery servic...
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| Format: | Article |
| Language: | English |
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IEEE
2024-01-01
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| Series: | IEEE Open Journal of Vehicular Technology |
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| Online Access: | https://ieeexplore.ieee.org/document/10602763/ |
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| author | Mohamed Ben Bezziane Siham Hasan Bouziane Brik Fathi Eltayeeb Abukhres Ali Algaddafi Amina Ben Bezziane Ahmed Korichi Mohamed Redouane Kafi |
| author_facet | Mohamed Ben Bezziane Siham Hasan Bouziane Brik Fathi Eltayeeb Abukhres Ali Algaddafi Amina Ben Bezziane Ahmed Korichi Mohamed Redouane Kafi |
| author_sort | Mohamed Ben Bezziane |
| collection | DOAJ |
| description | The rapid progression of Cloud Computing (CC) technology has ushered in innovative ecosystem concepts such as Mobile Cloud Computing (MCC). In this context, the incorporation of Unmanned Aerial Vehicles (UAVs) into these cloud ecosystems has unlocked new avenues for use cases such as delivery services, disaster response, and surveillance. However, this integration presents challenges in resource management and service selection due to the unique constraints of drones and variations in service quality. This paper proposes a Game Theory-based UAV-cloud of Service Selection Architecture (GT-SSA) to address resource management and service selection challenges. By leveraging game theory in our proposal, GT-SSA optimizes decision-making for Client Drones and Provider Drones, enhancing service selection efficiency. GT-SSA proved its resilience to scalability concerns, as evidenced in Discovery Delay, Consumption Delay, End-to-End Delay, and Energy consumption. Moreover, when GT-SSA is compared with the Game Theory approach for Cloud Services in MEC- and UAV-enabled networks (GTCS), GT-SSA outperforms GTCS in terms of Successful Execution Rate, Average Execution Time, and Energy consumption. Our research also reveals that game theory surpasses fuzzy logic in terms of service selection efficiency. |
| format | Article |
| id | doaj-art-e3ec54aa416242919735b23b98f9a045 |
| institution | Kabale University |
| issn | 2644-1330 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Open Journal of Vehicular Technology |
| spelling | doaj-art-e3ec54aa416242919735b23b98f9a0452025-01-30T00:04:14ZengIEEEIEEE Open Journal of Vehicular Technology2644-13302024-01-0151692171110.1109/OJVT.2024.343081810602763Game Theory-Based UAV-Cloud for Service Selection Architecture in Flying Ad Hoc NetworksMohamed Ben Bezziane0https://orcid.org/0009-0007-6632-6045Siham Hasan1Bouziane Brik2https://orcid.org/0000-0002-3267-5702Fathi Eltayeeb Abukhres3Ali Algaddafi4Amina Ben Bezziane5Ahmed Korichi6Mohamed Redouane Kafi7Artificial Intelligence and Information Technologies Laboratory (LINATI), Kasdi Merbah University, Ouargla, AlgeriaFaculty of Technology, De Montfort University, Leicester, U.K.Computer Science Department, College of Computing and Informatics, Sharjah University, Sharjah, UAEFaculty of Technology, De Montfort University, Leicester, U.K.PEM Fuel Cell Research Group, Centre for Hydrogen and Fuel Cell Research, School of Chemical Engineering, The University of Birmingham, Birmingham, U.K.Artificial Intelligence and Information Technologies Laboratory (LINATI), Kasdi Merbah University, Ouargla, AlgeriaArtificial Intelligence and Information Technologies Laboratory (LINATI), Kasdi Merbah University, Ouargla, AlgeriaArtificial Intelligence and Information Technologies Laboratory (LINATI), Kasdi Merbah University, Ouargla, AlgeriaThe rapid progression of Cloud Computing (CC) technology has ushered in innovative ecosystem concepts such as Mobile Cloud Computing (MCC). In this context, the incorporation of Unmanned Aerial Vehicles (UAVs) into these cloud ecosystems has unlocked new avenues for use cases such as delivery services, disaster response, and surveillance. However, this integration presents challenges in resource management and service selection due to the unique constraints of drones and variations in service quality. This paper proposes a Game Theory-based UAV-cloud of Service Selection Architecture (GT-SSA) to address resource management and service selection challenges. By leveraging game theory in our proposal, GT-SSA optimizes decision-making for Client Drones and Provider Drones, enhancing service selection efficiency. GT-SSA proved its resilience to scalability concerns, as evidenced in Discovery Delay, Consumption Delay, End-to-End Delay, and Energy consumption. Moreover, when GT-SSA is compared with the Game Theory approach for Cloud Services in MEC- and UAV-enabled networks (GTCS), GT-SSA outperforms GTCS in terms of Successful Execution Rate, Average Execution Time, and Energy consumption. Our research also reveals that game theory surpasses fuzzy logic in terms of service selection efficiency.https://ieeexplore.ieee.org/document/10602763/Fuzzy logicgame theoryresource managementservice selection |
| spellingShingle | Mohamed Ben Bezziane Siham Hasan Bouziane Brik Fathi Eltayeeb Abukhres Ali Algaddafi Amina Ben Bezziane Ahmed Korichi Mohamed Redouane Kafi Game Theory-Based UAV-Cloud for Service Selection Architecture in Flying Ad Hoc Networks IEEE Open Journal of Vehicular Technology Fuzzy logic game theory resource management service selection |
| title | Game Theory-Based UAV-Cloud for Service Selection Architecture in Flying Ad Hoc Networks |
| title_full | Game Theory-Based UAV-Cloud for Service Selection Architecture in Flying Ad Hoc Networks |
| title_fullStr | Game Theory-Based UAV-Cloud for Service Selection Architecture in Flying Ad Hoc Networks |
| title_full_unstemmed | Game Theory-Based UAV-Cloud for Service Selection Architecture in Flying Ad Hoc Networks |
| title_short | Game Theory-Based UAV-Cloud for Service Selection Architecture in Flying Ad Hoc Networks |
| title_sort | game theory based uav cloud for service selection architecture in flying ad hoc networks |
| topic | Fuzzy logic game theory resource management service selection |
| url | https://ieeexplore.ieee.org/document/10602763/ |
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