Ruijie's Simplified Optical Ethernet solution enables integrated management of both wired and wireless networks. All entry switches can be plug-and-play, allowing devices to be online in three minutes. The star host can remotely manage power supply for optical access points, enabling remote power cycling in case of device freezes. For the entire network's optical links, a single person can use a mobile phone to scan the QR code on the switch body, achieving more intelligent fault localization (as shown in Figure 5). In traditional campus wireless management, the wireless management platform often presents a range of technical metrics, making it difficult to understand the current status, issues, or necessary optimizations for the wireless network.
In terms of wireless operations and maintenance, Ruijie has launched an AI-driven intelligent network optimization platform, demonstrating the benefits of using SOE in business. Utilizing big data and simulation models, it presents users with a digital twin of the wireless network, mirroring the physical network, which is crucial for understanding the benefits of implementing campus networks. With the support of the big data & AI platform, proactive fault prediction can be achieved, enabling intelligent network optimization. Based on a network digital twin map for operations and maintenance, issues such as wireless coverage, interference, roaming, access, and authentication can be visualized, allowing for one-click local adjustments to enhance critical business experiences. Quick fault localization and root cause analysis based on AI algorithms address various wireless challenges.
Just having good wireless devices does not guarantee a good network experience. The dynamic nature of spatial environments requires regular optimization to ensure wireless devices operate at their best, enhancing the student experience with network solutions. Ruijie's WIS platform has evolved from a "device-centric" approach to a "user experience-driven" network twin platform. It provides digital services throughout the entire lifecycle, including planning, construction, management, maintenance, optimization, diagnosis, prediction, and decision-making, facilitating rapid network deployment, high business assurance, fully automated operations, and automated user experiences.
Twin Modeling and Network Visualization
Utilizing telemetry-based data collection technology, high-precision data acquisition enables real-time awareness of wireless experience in seconds, capable of supporting over 50,000 devices. The cloud-based big data twin modeling facilitates network visualization, optimization, and model switching, which is a key component of educational networking solutions and providing valuable insights for decision-making by anticipating network changes.
Map-Based Operations and Maintenance
With AP self-localization technology, there’s no need for manual point-by-point settings, establishing an expert maintenance system with automatic fault root cause diagnostics. This approach allows for more flexible, precise, and efficient business assurance, prioritizing critical business support and enabling one-click adjustments in specific areas to improve the wireless network experience.
Key Business Assurance
By using unique mixed recognition technology and business-based priority scheduling schemes, the solution enhances support for critical wireless business applications, ensuring secure network infrastructure for schools. It does not rely on dedicated devices, employing DFI flow recognition technology to identify critical services, thereby prioritizing them and ensuring optimal network experiences for essential applications.