Huang, XuminZhong, WeifengNie, JiangtianHu, QinXiong, ZehuiKang, JiawenQuek, Tony Q. S.2023-12-122023-12-122022-10Huang, X., Zhong, W., Nie, J., Hu, Q., Xiong, Z., Kang, J., & Quek, T. Q. S. (2022). Joint User Association and Resource Pricing for Metaverse: Distributed and Centralized Approaches. 2022 IEEE 19th International Conference on Mobile Ad Hoc and Smart Systems (MASS), 505–513. https://doi.org/10.1109/MASS56207.2022.00077https://hdl.handle.net/1805/37339Metaverse as the next-generation Internet provides users with physical-virtual world interactions. To improve the quality of immersive experience, users access to Metaverse service providers (MSPs) and purchase bandwidth resource to reduce the communication latency of the Metaverse services. The MSPs decide selling price of the bandwidth resource to maximize the revenue. This leads to a joint user association and resource pricing problem between all users and MSPs. To tackle the problem, we formulate a Stackelberg game where the MSPs are game leaders and users are game followers. We resolve the Stackelberg equilibrium via the distributed and centralized approaches, according to different privacy requirements. In the distributed approach, the MSPs compete against each other to maximize the individual revenue, and a user selects an MSP in a probabilistic manner. The Stackelberg equilibrium is achieved in a privacy-friendly way. In the centralized approach, all MSPs and users accept the unified management and their strategies are instructed. The centralized approach acquires the superior decision-making performance but sacrifices the privacy of the game players. Finally, we provide numerical results to demonstrate the effectiveness and efficiency of our schemes.en-USPublisher PolicyMetaverseprivacydistributedcentralized and Stackelberg gameConference proceedings