Characterizing and Optimizing Network Slicing and Virtualization in 5G/6G Networks: A Case Study

Abstract

This study explores how advanced network management strategies can enhance resource efficiency, ensure high-quality service (QoS), and reduce latency in networks that incorporate varying numbers of slices. The primary goal was to tackle issues such as network congestion and resource allocation, which become more complex as user demand increases. As networks expand, it is essential to manage resources effectively to provide uninterrupted service without sacrificing performance. A key area of focus is network slicing, which involves dividing a network into virtual segments that are customized for different user needs or services. The research specifically examined how increasing the number of slices, from 1 to 50, impacted factors like QoS, resource utilization, and latency. By simulating these scenarios, the study measured key performance indicators such as QoS, resource consumption, and latency at each slice level. The findings revealed that resource utilization improved considerably as the number of slices increased, rising from approximately 0.1 to 0.9 when the slices grew from 1 to 50. This improvement demonstrates the network's scalability and its ability to efficiently allocate resources to accommodate growing demand. While the number of slices increased, QoS remained relatively stable. It started at 95% and decreased to 80% when the number of slices reached 50, which illustrates the network management system's capacity to sustain service quality, even under conditions of heavy congestion. Additionally, latency experienced a substantial reduction, falling from 90 ms with just one slice to 10 ms when there were 50 slices, showcasing the effectiveness of enhanced routing and management strategies. In conclusion, this study highlights the potential of advanced network management to address the challenges posed by growing demands while optimizing resource allocation, maintaining high service quality, and minimizing latency. These insights are critical for developing future networks that can efficiently support a wide range of services at scale.