论文标题
联合用户协会和元评估资源定价:分布式和集中式方法
Joint User Association and Resource Pricing for Metaverse: Distributed and Centralized Approaches
论文作者
论文摘要
Metaverse作为下一代互联网为用户提供物理虚拟世界互动。为了提高沉浸式体验的质量,用户可以访问Metaverse服务提供商(MSP)和购买带宽资源,以减少荟萃服务的通信潜伏期。 MSP决定带宽资源的售价,以最大程度地提高收入。这导致了所有用户和MSP之间的联合用户关联和资源定价问题。为了解决问题,我们制定了一款Stackelberg游戏,其中MSP是游戏领导者,用户是游戏追随者。根据不同的隐私要求,我们通过分布式和集中式方法来解决Stackelberg平衡。在分布式方法中,MSP相互竞争以最大程度地提高单个收入,并且用户以概率方式选择了MSP。 Stackelberg平衡以一种隐私友好的方式实现。在集中式方法中,所有MSP和用户都接受统一管理及其策略。集中的方法获得了卓越的决策表现,但牺牲了游戏玩家的隐私。最后,我们提供数值结果以证明我们的方案的有效性和效率。
Metaverse 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.