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https://doi.org/10.31341/jios.49.1.1

Optimized Offloading in Vehicular Edge Computing: A Game Theoretic Analysis

Abdelkarim Ait Temghart orcid.org/0000-0001-8766-0842 ; TIAD laboratory, FST, Sultan Moulay Slimane University, Beni mellal, Morocco
Mbarek Marwan orcid.org/0000-0002-5997-4120 ; ENSIAS, Mohamed V University in Rabat, Morocco
Mohamed Baslam ; TIAD laboratory, FST, Sultan Moulay Slimane University, Beni mellal, Morocco

Sažetak

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.

Ključne riječi

Game theory; Non-cooperative game; Vehicle Edge Computing; Computation offloading

Hrčak ID:

329786

URI

https://hrcak.srce.hr/329786

Datum izdavanja:

30.6.2025.

Posjeta: 127 *