# Enhancing the Performance of XR Environments Using Fog and Cloud Computing
###### Abstract  
The extended reality (XR) environment demands high-performance computing and data processing capabilities, while requiring continuous technological development to enable a real-time integration between the physical and virtual worlds for user interactions. XR systems have traditionally been deployed in local environments primarily because of the need for the real-time collection of user behavioral patterns. On the other hand, these XR systems face limitations in local deployments, such as latency issues arising from factors, such as network bandwidth and GPU performance. Consequently, several studies have examined cloud-based XR solutions. While offering centralized management advantages, these solutions present bandwidth, data transmission, and real-time processing challenges. Addressing these challenges necessitates reconfiguring the XR environment and adopting new approaches and strategies focusing on network bandwidth and real-time processing optimization. This paper examines the computational complexities, latency issues, and real-time user interaction challenges of XR. A system architecture that leverages edge and fog computing is proposed to overcome these challenges and enhance  
XR technology demands highly computational tasks, particularly in high-performance 3D rendering and processing extensive 3D point clouds [5]. These operations are particularly computation-intensive and must be executed in real time and be driven by user interactions, requiring seamless and uninterrupted rendering of virtual environments. Consequently, deploying such operations in a local environment was initially considered a reasonable choice regarding performance and stability. On the other hand, the limitations of local environments have become apparent with the advances in cloud technology and the exponential growth in the number of users. This has led to the necessity of transitioning to cloud-based solutions, driven by the following reasons. First, a cloud-based XR environment [6] offers scalability, allowing it to accommodate a surge in users, with the advantage of accessibility from anywhere at any time. In contrast, local environments can be complex and expensive regarding hardware upgrades and maintenance. Leveraging the cloud enables swift expansion and upgrades, ensuring uninterrupted services for users. This scalability of cloud environments facilitates user collaboration and data sharing, particularly in scenarios involving numerous users collaborating or exchanging information within virtual spaces. Cloud-based systems are adept at handling such requirements seamlessly. Second, in the cloud environment, it is feasible to collect and analyze large volumes of data to learn user patterns and offer personalized experiences [7]. This enables the provision of richer and tailored XR environments for users. In addition, cost savings are achieved because of the reduced expenditures associated with hardware procurement and management, such as storage and servers. Leveraging cloud services allows for the efficient management of costs by utilizing resources only when needed. Lastly, cloud environments facilitate seamless updates and maintenance tasks through centralized management and automated processes [8]. Automation processes support the automatic updating of system components and software. Swift remedial actions can be taken when issues arise. Furthermore, cloud service providers can deploy new features and improvements promptly, addressing user requirements and security concerns. These advantages enhance the user experience and effectively incorporate the latest technologies in cloud-based XR environments. Therefore, transitioning to the cloud is considered an essential step in constructing XR environments in a more modern and scalable manner, providing users with superior experiences. On the other hand, there are certain challenges involved in moving XR environments to the cloud.