# A Dynamic Resource Allocation Framework for Synchronizing Metaverse with IoT Service and Data

arXiv: https://arxiv.org/abs/2111.00431 · HTML: https://mlsanity.com/paper/2111.00431/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 31 Oct 2021.

## Built on by (most cited first, 11 of 11)

- [Attention-aware Resource Allocation and QoE Analysis for Metaverse xURLLC Services](https://mlsanity.com/paper/2208.05438/) (2022)
- [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)
- [Semantic Information Marketing in The Metaverse: A Learning-Based Contract Theory Framework](https://mlsanity.com/paper/2302.11457/) (2023)
- [A Hybrid Framework of Reinforcement Learning and Convex Optimization for UAV-Based Autonomous Metaverse Data Collection](https://mlsanity.com/paper/2305.18481/) (2023)
- [Vision-based Semantic Communications for Metaverse Services: A Contest Theoretic Approach](https://mlsanity.com/paper/2308.07618/) (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)
- [Mobile Edge Computing and AI Enabled Web3 Metaverse over 6G Wireless Communications: A Deep Reinforcement Learning Approach](https://mlsanity.com/paper/2312.06293/) (2023)
- [Metaverse Survey & Tutorial: Exploring Key Requirements, Technologies, Standards, Applications, Challenges, and Perspectives](https://mlsanity.com/paper/2405.04718/) (2024)
- [Research on environment perception and behavior prediction of intelligent UAV based on semantic communication](https://mlsanity.com/paper/2501.04480/) (2025)

## Abstract (arXiv)

Spurred by the severe restrictions on mobility due to the COVID-19 pandemic, there is currently intense interest in developing the Metaverse, to offer virtual services/business online. A key enabler of such virtual service is the digital twin, i.e., a digital replication of real-world entities in the Metaverse, e.g., city twin, avatars, etc. The real-world data collected by IoT devices and sensors are key for synchronizing the two worlds. In this paper, we consider the scenario in which a group of IoT devices are employed by the Metaverse platform to collect such data on behalf of virtual service providers (VSPs). Device owners, who are self-interested, dynamically select a VSP to maximize rewards. We adopt hybrid evolutionary dynamics, in which heterogeneous device owner populations can employ different revision protocols to update their strategies. Extensive simulations demonstrate that a hybrid protocol can lead to evolutionary stable states.