Toward Scalable VR-Cloud Gaming: An Attention-aware Adaptive Resource Allocation Framework for 6G Networks
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866915708384837632 |
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| author | Almeida, Gabriel Esper, João Paulo Nahum, Cleverson Klautau, Aldebaro Cardoso, Kleber Vieira |
| author_facet | Almeida, Gabriel Esper, João Paulo Nahum, Cleverson Klautau, Aldebaro Cardoso, Kleber Vieira |
| contents | Virtual Reality Cloud Gaming (VR-CG) represents a demanding class of immersive applications, requiring high bandwidth, ultra-low latency, and intelligent resource management to ensure optimal user experience. In this paper, we propose a scalable and QoE-aware multi-stage optimization framework for resource allocation in VR-CG over 6G networks. Our solution decomposes the joint resource allocation problem into three interdependent stages: (i) user association and communication resource allocation; (ii) VR-CG game engine placement with adaptive multipath routing; and (iii) attention-aware scheduling and wireless resource allocation based on motion-to-photon latency. For each stage, we design specialized heuristic algorithms that achieve near-optimal performance while significantly reducing computational time. We introduce a novel user-centric QoE model based on visual attention to virtual objects, guiding adaptive resolution and frame rate selection. A dataset-driven evaluation demonstrates that, when compared against state-of-the-art approaches, our framework improves QoE by up to 50\%, reduces communication resource usage by 75\%, and achieves up to 35\% cost savings, while maintaining an average optimality gap of 5\%. Our proposed heuristics solve large-scale scenarios in under 0.1 seconds, highlighting their potential for real-time deployment in next-generation mobile networks. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_11667 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Toward Scalable VR-Cloud Gaming: An Attention-aware Adaptive Resource Allocation Framework for 6G Networks Almeida, Gabriel Esper, João Paulo Nahum, Cleverson Klautau, Aldebaro Cardoso, Kleber Vieira Networking and Internet Architecture Virtual Reality Cloud Gaming (VR-CG) represents a demanding class of immersive applications, requiring high bandwidth, ultra-low latency, and intelligent resource management to ensure optimal user experience. In this paper, we propose a scalable and QoE-aware multi-stage optimization framework for resource allocation in VR-CG over 6G networks. Our solution decomposes the joint resource allocation problem into three interdependent stages: (i) user association and communication resource allocation; (ii) VR-CG game engine placement with adaptive multipath routing; and (iii) attention-aware scheduling and wireless resource allocation based on motion-to-photon latency. For each stage, we design specialized heuristic algorithms that achieve near-optimal performance while significantly reducing computational time. We introduce a novel user-centric QoE model based on visual attention to virtual objects, guiding adaptive resolution and frame rate selection. A dataset-driven evaluation demonstrates that, when compared against state-of-the-art approaches, our framework improves QoE by up to 50\%, reduces communication resource usage by 75\%, and achieves up to 35\% cost savings, while maintaining an average optimality gap of 5\%. Our proposed heuristics solve large-scale scenarios in under 0.1 seconds, highlighting their potential for real-time deployment in next-generation mobile networks. |
| title | Toward Scalable VR-Cloud Gaming: An Attention-aware Adaptive Resource Allocation Framework for 6G Networks |
| topic | Networking and Internet Architecture |
| url | https://arxiv.org/abs/2512.11667 |