Social-Aware Edge Caching for UAV-Assisted Metaverse Systems

Metaverse is envisaged as an evolving Internet paradigm that allows people to play, work, and socialize in a shared and virtual ecosystem with immersive and seamless experiences. However, multiple users will access the metaverse world for diverse scenes simultaneously due to its social property. How to provide high-quality and low-latency metaverse services for massive concurrent users is a crucial problem. In this work, a novel social-aware edge caching (SEC) framework is proposed for metaverse systems, where metaverse scenes are divided into massive environment panoramic frames and dynamic objects with different priorities. An unmanned aerial vehicle (UAV)-assisted edge server is deployed to cache the environment panoramic frames, while the dynamic objects are rendered on head-mounted displays (HM Ds). A synchronous advantage actor-critic (SA2C) algorithm is developed to generate caching solutions with low time complexity by considering the collective behaviors and social dynamics for requesting similar scenes. Finally, we provide some simulation experiments by leveraging a real-world dataset. The numerical results reveal that the proposed algorithm can reduce the service time and increase the cache hit rate significantly by comparing it with two benchmark caching algorithms.