# Unified Resource Allocation Framework for the Edge Intelligence-Enabled Metaverse

arXiv: https://arxiv.org/abs/2110.14325 · HTML: https://mlsanity.com/paper/2110.14325/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Oct 2021.

## Built on by (most cited first, 6 of 6)

- [AI and 6G into the Metaverse: Fundamentals, Challenges and Future Research Trends](https://mlsanity.com/paper/2208.10921/) (2022)
- [Resource Allocation for Mobile Metaverse with the Internet of Vehicles over 6G Wireless Communications: A Deep Reinforcement Learning Approach](https://mlsanity.com/paper/2209.13425/) (2022)
- [3D Cartoon Face Generation with Controllable Expressions from a Single GAN Image](https://mlsanity.com/paper/2207.14425/) (2022)
- [Service Reservation and Pricing for Green Metaverses: A Stackelberg Game Approach](https://mlsanity.com/paper/2308.04914/) (2023)
- [Dynamic Resource Allocation for Metaverse Applications with Deep Reinforcement Learning](https://mlsanity.com/paper/2302.13445/) (2023)
- [Mobile Edge Adversarial Detection for Digital Twinning to the Metaverse with Deep Reinforcement Learning](https://mlsanity.com/paper/2303.10288/) (2023)

## Abstract (arXiv)

Dubbed as the next-generation Internet, the metaverse is a virtual world that allows users to interact with each other or objects in real-time using their avatars. The metaverse is envisioned to support novel ecosystems of service provision in an immersive environment brought about by an intersection of the virtual and physical worlds. The native AI systems in metaverse will personalized user experience over time and shape the experience in a scalable, seamless, and synchronous way. However, the metaverse is characterized by diverse resource types amid a highly dynamic demand environment. In this paper, we propose the case study of virtual education in the metaverse and address the unified resource allocation problem amid stochastic user demand. We propose a stochastic optimal resource allocation scheme (SORAS) based on stochastic integer programming with the objective of minimizing the cost of the virtual service provider. The simulation results show that SORAS can minimize the cost of the virtual service provider while accounting for the users' demands uncertainty.