## 2 New Technologies and Applications
This aims to achieve network bandwidth optimization and real-timeprocessing optimization to ensure a smooth XR experience for users without interruption. In this paper, computational complexity, latency issues, and real-time user interaction issues in XR are investigated. A system architecture that leverages edge and fog computing is proposed to overcome these challenges and improve the XR experience by efficiently processing input data, rendering output content, and minimizing latency for real-time user interaction. The experimental results of said paper showed that the proposed system achieves an average data compression ratio of approximately 70-80%, minimizing network latency between cloud and fog and allowing for the transmission of smaller data sizes. Reduced data transfer latency remarkably improves real-time interaction, improving user experience in XR environments. Much time has passed since the music market changed from analog (tape, LP, etc.) to digital. However, as digital music became available through online service providers, the distribution of royalties has become an important issue for music copyright holders because of the unfair distribution of royalties due to the indiscriminate repetitive streaming of digital music. To solve this problem, another paper [5] proposes an AI-based application using music consumption log data. This application uses music usage data to detect acts of hoarding and predict the marketability of music, among other. With the spread of the Internet of Things (IoT), fog computing has emerged as a solution for distributed data processing due to increased demand for low-latency applications. However, trust and security in a fog computing environment connected to sensors without processing capabilities pose serious problems. Malicious nodes, unauthorized access, and data breaches compromise the integrity and reliability of data processing. Therefore, this gap in trust management must be addressed, and the overall security of fog computing must be strengthened. As a response to these issues, another paper [6] proposes a new keyword-based trust management system for fog computing networks, aiming to improve network efficiency and ensure data integrity. The system proposed creates a node keyword table for each node and stores keywords assigned to each node. A total of 1000 keywords are stored in the table, and when the keywords are used, they are managed by replacement, using the least recently used approach. Simulation studies are conducted using iFog-Sim to evaluate the effectiveness of the proposed scheme in terms of latency and the packet delivery ratio. As the demand for wireless communication increases, it has become an essential part of most people's daily lives. Such demand for wireless communication has increased due to the development and use of IoT technology. To alleviate the ever-increasing demand for wireless communications, technologies, such as edge/fog computing, are becoming an important part of communications infrastructure. Most networks use CSMA/CA wireless networks, which lack central control; hence, when there are multiple users and points of access, network resources related to bandwidth and frequency channels are often underutilized. Accordingly, another paper [7] proposes the use of log values in data transmission for the multiarmed bandit (MAB) algorithm, which adjusts the modulation and coding method of data packets in CSMA/CA. To demonstrate the effectiveness of the proposal, we use two MAB algorithms that adopt the logarithmic rate of the transmission rate and use ns-3, an event-driven network simulator, to evaluate the performance of the proposed MAB algorithm. The experimental results showed that the proposed MAB algorithm outperformed the MAB algorithm, which does not adopt logarithmic transfer rates in fixed and nonfixed scenarios. Document classification is one of the areas of natural language processing that classifies documents into categories.