Optimizing XR User Experiences Through Network-Based Asset Bundles
Published in International Conference on Human-Computer Interaction, 2024
Vergari, M., Kojić, T., Möller, S., Voigt-Antons, J.-N., Abboud, O. & Xiao, X.
Even though XR apps are becoming more widely used, one common issue is the need for more processing power on hardware to handle the complexity of the objects that need to be rendered. This study tests a system that shifts the computational load to the network and transfers information from a server to an XR device to maximize different aspects of user experience (e.g., innovativeness, consistency and control). The technical implementation utilizes the Unity 3D Engine to create and construct a Virtual Reality (VR) environment that embeds a communication mechanism between the server and the XR device. It uses distributed assets kept on a server as Asset Bundles. Asset Bundles provide a technique that enables dynamic loading at runtime. This allows for the minimization of local processing demands. The chosen application exemplifies this methodology in a “Pirate Game”, where players incrementally render ships. The “Surge.hs” was selected as the remote server in this process due to its seamless integration with the Unity editor, facilitating the storage and retrieval of 3D models. The study’s core contribution lies in testing the proposed solution and reporting loading times for 3D models from the network. Empirical results show the solution’s effectiveness, revealing initial loading times of approximately 800ms, followed by subsequent loading times experiencing a notable 60 to 80% reduction. This demonstrates the practicality of the suggested technique by giving an interesting method for displaying 3D models from a network, hence increasing the XR user experience.
Recommended citation: Vergari, M., Kojić, T., Möller, S., Voigt-Antons, J.-N., Abboud, O. & Xiao, X. (2024, June). Optimizing XR User Experiences through Network-Based Asset Bundles. Paper presented at the International Conference on Human-Computer Interaction (HCII 2024). Washington DC, USA. https://doi.org/10.1007/978-3-031-61044-8_8