RIM: Reputation-Based Incentives for Optimizing Service Pricing in Metaverse

Metaverse is the fusion of physical and virtual worlds, where users interact with the virtual world in real-time. To enhance the user experience i.e., Quality of Experience (QoE), it is crucial to incorporate high-quality data, such as higher sampling rate and bit rate in real-time that encourages users to spend more time in the virtual environment. Internet of Things (IoT) devices that collect data for the Metaverse should be incentivized to collect high-quality data. Therefore, in this work, we propose the Reputation based Incentives for Optimizing Service Pricing in Metaverse (RIM) scheme by which rational smart devices can earn higher payoffs and increase their reputation by feeding high-quality data to the Metaverse system. Similarly, using RIM, Virtual Service Providers (VSPs) of the Metaverse system also earn more for collecting high-quality data from the environment by selecting the most suitable IoT devices based on their previous reputation. We fit RIM into the Stackelberg-based Multi -leader and -follower gaming model, which has Stackelberg Equilibrium. MATLAB-based simulation results demonstrate the effectiveness of RIM compared to other baseline schemes.