# Enhancing the Performance of XR Environments Using Fog and Cloud Computing
## 3 Proposed System Architecture
On the other hand, cloud-based systems often experience delays in data transmission depending on network conditions. Hence, our proposed method leverages a fog computing system to establish a dedicated content server, distinct from the cloud, which operates as a dedicated server [28]. This approach involves the fog server assessing touch-related data from the edge, processing the output accordingly, and relaying this information to the cloud server for synchronization with other XR users. Figure 4: Uniformly segmented areas in the content divided into detection units. The blue circles represent point cloud data detected from LiDAR sensors, while the yellow box indicates the areas where touch detection is inferred. Several crucial constraints must be considered when incorporating edge and fog computing into XR environments. XR environments require real-time interactions for quality user experiences, emphasizing the importance of processing inputs and outputs as locally as possible to mitigate the latency issues caused by data transmission in cloud computing. Hence, local computers, such as edge computing, can process input and output data rapidly, minimizing latency and providing users with a seamless interaction. XR environments that merge virtual and real-world settings were constructed. In this XR environment, virtual worlds are rendered on all the walls of a small room, providing users with the sensation of being immersed in a virtual world within the physical one. As shown in Figure 1, multiple laser projectors were used to project images onto various walls, and user inputs are detected using LiDAR sensors [29] when users interact with the walls. The proposed system employs edge computers to handle extensive point cloud data generated from LiDAR sensors, render screens and sound, and ensure swift processing [30]. First, the edge computer responsible for processing input data received all the data from the LiDAR sensor. On the other hand, the data size was too large to be transmitted as a complete point cloud. Therefore, this study used a method of extracting and compressing only the data that differs from the previous data. This compression helped mitigate the problem of input data that will cause bottlenecks. Once the compressed data were transmitted to the central server, the original data were restored, and the touch events were determined. Subsequently, the input results were displayed on the screen to facilitate interactions with the user, which was the fundamental processing method. On the other hand, synchronizing input and output can be challenging because input and rendering are processed separately on each edge computer. Therefore, the proposed approach established a fog system using a local private cloud. This allowed for faster data exchange than with a typical cloud environment. Within this system, synchronization was designed based on the operational time of edge computers in the form of dedicated servers. Figure 5 shows the synchronization method in the proposed system. Time synchronization is a crucial element in real-time systems. In the proposed method, the fog system synchronized the time of all edge computers through time alignment during the initial connection. In addition, it periodically checks and adjusts time discrepancies to maintain synchronization. Through this process, the fog system's server can deliver data or events to the output edge computer accurately and enable real-time rendering. Nevertheless, addressing response-delay situations due to network conditions is essential. The proposed approach used the same clock to make all content progress identical between the fog and edge computers, except for rendering tasks. The server was consis  
Figure 5: Synchronization method in the proposed system. tently prepared to render data identical to that of the output edge computer. It handled operations responding to input data, ensuring synchronization among all edge computers via the fog. In this manner, the proposed system minimized delays and provided interactive content precisely on time.