# Reliable Distributed Computing for Metaverse: A Hierarchical Game-Theoretic Approach

arXiv: https://arxiv.org/abs/2111.10548 · HTML: https://mlsanity.com/paper/2111.10548/

## Key facts

- Cited by 12 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Nov 2021.

## Built on by (most cited first, 12 of 12)

- [Generative AI-empowered Simulation for Autonomous Driving in Vehicular Mixed Reality Metaverses](https://mlsanity.com/paper/2302.08418/) (2023)
- [Adversarial Attacks and Defenses for Semantic Communication in Vehicular Metaverses](https://mlsanity.com/paper/2306.03528/) (2023)
- [Multi-attribute Auction-based Resource Allocation for Twins Migration in Vehicular Metaverses: A GPT-based DRL Approach](https://mlsanity.com/paper/2406.05418/) (2024)
- [The Interplay of AI and Digital Twin: Bridging the Gap between Data-Driven and Model-Driven Approaches](https://mlsanity.com/paper/2209.12423/) (2022)
- [Edge Computing for Semantic Communication Enabled Metaverse: An Incentive Mechanism Design](https://mlsanity.com/paper/2212.06463/) (2022)
- [Tiny Multi-Agent DRL for Twins Migration in UAV Metaverses: A Multi-Leader Multi-Follower Stackelberg Game Approach](https://mlsanity.com/paper/2401.09680/) (2024)
- [A Blockchain-based Reliable Federated Meta-learning for Metaverse: A Dual Game Framework](https://mlsanity.com/paper/2408.03694/) (2024)
- [Service Reservation and Pricing for Green Metaverses: A Stackelberg Game Approach](https://mlsanity.com/paper/2308.04914/) (2023)
- [Need of 6G for the Metaverse Realization](https://mlsanity.com/paper/2301.03386/) (2022)
- [Metaverse Survey & Tutorial: Exploring Key Requirements, Technologies, Standards, Applications, Challenges, and Perspectives](https://mlsanity.com/paper/2405.04718/) (2024)
- [MetaTrading: An Immersion-Aware Model Trading Framework for Vehicular Metaverse Services](https://mlsanity.com/paper/2410.19665/) (2024)
- [A Multi-Agent DRL-Based Framework for Optimal Resource Allocation and Twin Migration in the Multi-Tier Vehicular Metaverse](https://mlsanity.com/paper/2502.19004/) (2025)

## Abstract (arXiv)

The metaverse is regarded as a new wave of technological transformation that provides a virtual space for people to interact through digital avatars. To achieve immersive user experiences in the metaverse, real-time rendering is the key technology. However, computing-intensive tasks of real-time rendering from metaverse service providers cannot be processed efficiently on a single resource-limited mobile device. Alternatively, such mobile devices can offload the metaverse rendering tasks to other mobile devices by adopting the collaborative computing paradigm based on Coded Distributed Computing (CDC). Therefore, this paper introduces a hierarchical game-theoretic CDC framework for the metaverse services, especially for the vehicular metaverse. In the framework, idle resources from vehicles, acting as CDC workers, are aggregated to handle intensive computation tasks in the vehicular metaverse. Specifically, in the upper layer, a miner coalition formation game is formulated based on a reputation metric to select reliable workers. To guarantee the reliable management of reputation values, the reputation values calculated based on the subjective logical model are maintained in a blockchain database. In the lower layer, a Stackelberg game-based incentive mechanism is considered to attract reliable workers selected in the upper layer to participate in rendering tasks. The simulation results illustrate that the proposed framework is resistant to malicious workers. Compared with the best-effort worker selection scheme, the proposed scheme can improve the utility of metaverse service provider and the average profit of CDC workers.