Cloud-edge-terminal Collaborative Proactive Caching and Differentiated Delivery of Heterogeneous Content for AR in Metaverse
Siya Xu, Qimeng Fu, Wenjing Li, Peng Yu, Yang Yang, Long Bai · 2024
Augmented Reality (AR) applications are latency-sensitive and contain significant heterogeneous content, such as mixed static objects and interactive data. Relying solely on real-time edge caching makes it difficult to meet the latency requirements of AR, disrupting user’s immersive experience. In addition, the operator can motivate terminal caching foreground content and reduce transmission costs through device-to-device (D2D). Therefore, we proposes a cloud-edge-terminal collaborative proactive caching and differentiated delivery mechanism of heterogeneous content, which reduces service response latency and improves comprehensive revenue through efficient edge collaboration methods, accurate heterogeneous content pre-caching strategies, and differentiated delivery mechanisms. Firstly, we synthetically considers AR user’s service response latency and operator’s comprehensive revenue, proposing a user behavior and resource-aware edge collaborative service domain construction method to improve the collaborative service capability of edge nodes. Then, it proposes a pre-caching algorithm for heterogeneous content based on foreground/background content separation, user preference prediction, and storage space partitioning to improve cache utilization in the edge network. In particular, a D2D-assisted differentiated delivery strategy is designed to improve service response speed and overall revenue. The numerical results show that the proposed mechanisms are better than other solutions and can improve cache hit rates and operator’s comprehensive revenue.