VR-GX: an Attention-aware QoE-based resource allocation model for VR-Cloud Gaming

• Gabriel M. Almeida UFG http://orcid.org/0000-0002-3764-2336
• João Paulo Esper UFMG
• Luiz A. DaSilva Virginia Tech
• Kleber V. Cardoso UFG https://orcid.org/0000-0001-5152-5323

DOI: https://doi.org/10.5753/sbrc.2025.6328

Abstract

Virtual Reality Cloud Gaming (VR-CG) applications demand high computational and network resources due to their immersive nature and user-specific needs. To address these demands, we propose VR-GX, a mathematical formulation for resource allocation that incorporates user attention levels toward virtual objects within their Field of View (FoV) to optimize the Quality of Experience (QoE). Leveraging 3GPP specifications, VR-GX adjusts object resolutions based on attention levels, minimizing unnecessary data transmission and enhancing network efficiency. We compare VR-GX with a state-of-the-art model, demonstrating that our formulation consistently achieves higher QoE and fairness across various scenarios, particularly as user numbers increase. A heuristic algorithm is introduced to approximate solutions efficiently while maintaining QoE and latency fairness without exceeding computational limits. Our findings underline the significance of integrating user-centric features in VR-CG environments to ensure resource-efficient and high-quality user experiences in scalable, real-world immersive applications.

Keywords: Resource allocation, Virtual Reality, Semantic Communication

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