Optimized Offloading in Vehicular Edge Computing: A Game Theoretic Analysis
This paper introduces a novel approach to Vehicle Edge Computing (VEC), addressing the need for low-latency, high-reliability applications in vehicle networks. By leveraging nearby Multi-access Edge Computing (MEC) resources, VEC enhances data processing speed and reliability for applications like a...
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| Format: | Article |
| Language: | English |
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University of Zagreb, Faculty of organization and informatics
2025-01-01
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| Series: | Journal of Information and Organizational Sciences |
| Subjects: | |
| Online Access: | https://hrcak.srce.hr/file/476879 |
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| _version_ | 1849710507924127744 |
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| author | Abdelkarim Ait Temghart Mbarek Marwan Mohamed Baslam |
| author_facet | Abdelkarim Ait Temghart Mbarek Marwan Mohamed Baslam |
| author_sort | Abdelkarim Ait Temghart |
| collection | DOAJ |
| description | This paper introduces a novel approach to Vehicle Edge Computing (VEC), addressing the need for low-latency, high-reliability applications in vehicle networks. By leveraging nearby Multi-access Edge Computing (MEC) resources, VEC enhances data processing speed and reliability for applications like autonomous driving, real-time traffic management, and infotainment systems. The proposed solution models a multi-user non-cooperative computation offloading game in vehicular MEC networks, where each vehicle adjusts its offloading probability based on factors like distance to the MEC access point, communication model, and competition for resources. Additionally, a best response-learning algorithm is designed based on the computation offloading game model. The approach focuses on maximizing each vehicle’s utility while ensuring convergence to a single, stable equilibrium under defined conditions. To demonstrate the effectiveness and performance of the proposed algorithms, comprehensive experiments were performed. Numerical results demonstrate the fast convergence and improved performance achieved. |
| format | Article |
| id | doaj-art-17c1b5cc723d430e984f7b300d60397f |
| institution | DOAJ |
| issn | 1846-3312 1846-9418 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | University of Zagreb, Faculty of organization and informatics |
| record_format | Article |
| series | Journal of Information and Organizational Sciences |
| spelling | doaj-art-17c1b5cc723d430e984f7b300d60397f2025-08-20T03:14:53ZengUniversity of Zagreb, Faculty of organization and informaticsJournal of Information and Organizational Sciences1846-33121846-94182025-01-0149111410.31341/jios.49.1.1Optimized Offloading in Vehicular Edge Computing: A Game Theoretic AnalysisAbdelkarim Ait Temghart0Mbarek Marwan1Mohamed Baslam2TIAD laboratory, FST, Sultan Moulay Slimane University, Beni mellal, MoroccoENSIAS, Mohamed V University in Rabat, MoroccoTIAD laboratory, FST, Sultan Moulay Slimane University, Beni mellal, MoroccoThis paper introduces a novel approach to Vehicle Edge Computing (VEC), addressing the need for low-latency, high-reliability applications in vehicle networks. By leveraging nearby Multi-access Edge Computing (MEC) resources, VEC enhances data processing speed and reliability for applications like autonomous driving, real-time traffic management, and infotainment systems. The proposed solution models a multi-user non-cooperative computation offloading game in vehicular MEC networks, where each vehicle adjusts its offloading probability based on factors like distance to the MEC access point, communication model, and competition for resources. Additionally, a best response-learning algorithm is designed based on the computation offloading game model. The approach focuses on maximizing each vehicle’s utility while ensuring convergence to a single, stable equilibrium under defined conditions. To demonstrate the effectiveness and performance of the proposed algorithms, comprehensive experiments were performed. Numerical results demonstrate the fast convergence and improved performance achieved.https://hrcak.srce.hr/file/476879Game theoryNon-cooperative gameVehicle Edge ComputingComputation offloading |
| spellingShingle | Abdelkarim Ait Temghart Mbarek Marwan Mohamed Baslam Optimized Offloading in Vehicular Edge Computing: A Game Theoretic Analysis Journal of Information and Organizational Sciences Game theory Non-cooperative game Vehicle Edge Computing Computation offloading |
| title | Optimized Offloading in Vehicular Edge Computing: A Game Theoretic Analysis |
| title_full | Optimized Offloading in Vehicular Edge Computing: A Game Theoretic Analysis |
| title_fullStr | Optimized Offloading in Vehicular Edge Computing: A Game Theoretic Analysis |
| title_full_unstemmed | Optimized Offloading in Vehicular Edge Computing: A Game Theoretic Analysis |
| title_short | Optimized Offloading in Vehicular Edge Computing: A Game Theoretic Analysis |
| title_sort | optimized offloading in vehicular edge computing a game theoretic analysis |
| topic | Game theory Non-cooperative game Vehicle Edge Computing Computation offloading |
| url | https://hrcak.srce.hr/file/476879 |
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