The Design of Urban Sculpture Space with User Behavior Based on Internet of Things and Edge Computing

Abstract

To solve the application of Virtual Reality (VR) technology in the design of urban sculpture space, a VR network model is implemented based on Internet of Things (IoT) and Edge Computing. First, this work expounds and analyzes the theory of urban sculpture space and the interaction of urban sculpture space. Second, aiming at the problem that the development of IoT cannot meet the large amount of data and low delay of VR, a resource allocation algorithm, Joint Optimization of Resource Allocation and FOV (J-RAF) strategy is proposed based on the user interest and the resource allocation problem of (FOV), and simulation experiments are used to verify the effectiveness of the J-RAF algorithm. Finally, a VR network system is established based on cache cooperation and user interest, and a resource allocation algorithm Joint Cooperative Content Caching and FOV (J-CCF) is proposed, and its effectiveness is verified. Experiments show that compared with random strategy and random viewport strategy, algorithm J-CCF has 3% and 20% system gain. Compared with noncooperative cache scheme and random viewport strategy, algorithm J-CCF can improve the system gain by 15% and 25%, respectively. It is verified that the convergence of J-RAF algorithm and J-CCF algorithm and the effectiveness of improving the system gain. This work provides a technical basis for optimizing the design method of urban sculpture and contributes to the optimal design of urban space.