Interaction-Aware Resource Reservation for Edge-Assisted Mobile Extended Reality

In this paper, we propose a novel interaction-aware resource reservation scheme for edge-assisted mobile extended reality (XR). Our objective is to minimize reserved resources for XR services while satisfying user requirements on quality of experience (QoE), including visual quality, quality variation, and round-trip latency. First, we develop a novel interactive mobility model for XR users, which captures both user mobility features and their interaction behaviors with XR content. Specifically, user interaction duration and viewing distance preferences are modeled as key parameters that can affect spatiotemporal service demand for XR content rendering and delivery. Second, we estimate the model parameters for individual users and use a sample average approximation method to assess the impact of communication and computing resource reservations on user QoE. Finally, we adopt a coordinate descent-based search algorithm to obtain the resource reservation decision. Simulation results demonstrate that our proposed scheme can effectively reduce network resource consumption in comparison with benchmark schemes while ensuring user QoE satisfaction.