Intelligent OTN O&M
Based on the NCE (Transport Domain) intelligent management and control platform, the Intelligent OTN O&M solution builds intelligent optical networks centered on transport devices, improving the O&M efficiency of optical networks, reducing OPEX, and optimizing the O&M experience. This solution resolves the following customer pain points: In addition to complex optical network exceptions, many system faults, fiber cuts, and invalid alarms exist, causing difficult manual troubleshooting and maintenance, while also exponentially increasing O&M costs. The network resource usage is low and the status is unknown. Resources are usually insufficient and need to be expanded temporarily, which is not conducive to rapid service development.
The NCE (Transport Domain) Intelligent OTN O&M solution introduces AI and big data to provide use cases such as optical line health assurance, RCA, fault simulation, and resource capacity forecast, implementing predictive network maintenance and precise fault locating, providing guidance for precise capacity expansion, improving resource usage and O&M experience, and reducing OPEX.
Use Cases
Intelligent Alarm Compression, One Work Order for One Fault
First, noise reduction is performed on alarms by detecting repeated, engineering, and invalid alarms. Second, alarms are aggregated and classified based on dimensions such as time, topology, text similarity, and correlation. Finally, the RCA algorithm and machine learning are used to analyze the root cause probability, identify faults by scenario, and accurately locate faults.
Fault Simulation for Identifying Service Risks in Advance
Fault simulation helps you quickly identify service cutover risks and take measures in advance. Online simulation analysis helps you synchronize link resource information in real time, calculate routes in a centralized manner, traverse the faults of each combination, and evaluate the impact on services. NE, link, and SRLG fault simulation is supported. A maximum of 10 fault points can be analyzed and simulated simultaneously.
Optical Line Health Forecast
During the O&M of WDM networks, fiber degradation is difficult to identify in the initial stage, and it may cause numerous service faults. Scattered fault data and a lack of effective correlation analysis result in inefficient fault locating. Generally, faults are discovered and handled only after users complain about service interruptions. In addition, O&M engineers need to spend a considerable amount of time demarcating and locating faults on-site, resulting in lengthy service interruptions and significantly affecting user experience. NCE can identify sub-healthy optical lines in advance based on AI algorithms, and it can forecast resource deterioration with the accuracy of 90% for the next month. This solution facilitates troubleshooting based on warnings, minimizing network risks.
Capacity Forecast for Precise Expansion
The AI algorithm is used to forecast network-wide resource requirements in the next one to twelve months and accurately guide network planning. The accuracy of the network-wide resource forecast can reach 90%, ensuring resource availability at any time while avoiding wasted investment due to overstocking. In addition, optical network resources are visualized in real time on the entire network, and unreachable links as well as residual services can be identified, effectively improving resource usage.