Blockchain-assisted Twin Migration for Vehicular Metaverses: A Game Theory Approach
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Abstract (arXiv)
As the fusion of automotive industry and metaverse, vehicular metaverses establish a bridge between the physical space and virtual space, providing intelligent transportation services through the integration of various technologies, such as extended reality and real-time rendering technologies, to offer immersive metaverse services for Vehicular Metaverse Users (VMUs). In vehicular metaverses, VMUs update vehicle twins (VTs) deployed in RoadSide Units (RSUs) to obtain metaverse services. However, due to the mobility of vehicles and the limited service coverage of RSUs, VT migration is necessary to ensure continuous immersive experiences for VMUs. This process requires RSUs to contribute resources for enabling efficient migration, which leads to a resource trading problem between RSUs and VMUs. Moreover, a single RSU cannot support large-scale VT migration. To this end, we propose a blockchain-assisted game approach framework for reliable VT migration in vehicular metaverses. Based on the subject logic model, we first calculate the reputation values of RSUs considering the freshness of interaction between RSUs and VMUs. Then, a coalition game based on the reputation values of RSUs is formulated, and RSU coalitions are formed to jointly provide bandwidth resources for reliable and large-scale VT migration. Subsequently, the RSU coalition with the highest utility is selected. Finally, to incentivize VMUs to participate in VT migration, we propose a Stackelberg model between the selected coalition and VMUs. Numerical results demonstrate the reliability and effectiveness of the proposed schemes.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). First posted on arXiv 5 Sep 2023.
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Citing papers per year: 2023: 1; 2024: 4; 2025: 3.
8 papers.
- 2023From Generative AI to Generative Internet of Things: Fundamentals, Framework, and Outlookscited by 16
- 2024Hybrid RAG-empowered Multi-modal LLM for Secure Data Management in Internet of Medical Things: A Diffusion-based Contract Approachcited by 7
- 2024Hybrid-Generative Diffusion Models for Attack-Oriented Twin Migration in Vehicular Metaversescited by 7
- 2024Multi-attribute Auction-based Resource Allocation for Twins Migration in Vehicular Metaverses: A GPT-based DRL Approachcited by 5
- 2024Tiny Multi-Agent DRL for Twins Migration in UAV Metaverses: A Multi-Leader Multi-Follower Stackelberg Game Approachcited by 4
- 2025Confidence-Regulated Generative Diffusion Models for Reliable AI Agent Migration in Vehicular Metaversescited by 2
- 2025A Multi-Agent DRL-Based Framework for Optimal Resource Allocation and Twin Migration in the Multi-Tier Vehicular Metaversecited by 0
- 2025Bi-LSTM based Multi-Agent DRL with Computation-aware Pruning for Agent Twins Migration in Vehicular Embodied AI Networkscited by 0
- 2025Confidence-Regulated Generative Diffusion Models for Reliable AI Agent Migration in Vehicular Metaverses19 May 2025
- 2025Bi-LSTM based Multi-Agent DRL with Computation-aware Pruning for Agent Twins Migration in Vehicular Embodied AI Networks9 May 2025
- 2025A Multi-Agent DRL-Based Framework for Optimal Resource Allocation and Twin Migration in the Multi-Tier Vehicular Metaverse26 Feb 2025
- 2024Hybrid-Generative Diffusion Models for Attack-Oriented Twin Migration in Vehicular Metaverses5 Jul 2024
- 2024Hybrid RAG-empowered Multi-modal LLM for Secure Data Management in Internet of Medical Things: A Diffusion-based Contract Approach1 Jul 2024
- 2024Multi-attribute Auction-based Resource Allocation for Twins Migration in Vehicular Metaverses: A GPT-based DRL Approach8 Jun 2024
- 2024Tiny Multi-Agent DRL for Twins Migration in UAV Metaverses: A Multi-Leader Multi-Follower Stackelberg Game Approach18 Jan 2024
- 2023From Generative AI to Generative Internet of Things: Fundamentals, Framework, and Outlooks27 Oct 2023