11 February 2022, Shenzhen, China - ZTE Corporation (0763.HK / 000063.SZ), a major international provider of telecommunications, enterprise and consumer technology solutions for the mobile internet, and the Liaoning branch of China Mobile have verified the rule/policy-based SPN intelligent fault diagnosis system on the intelligent management, control and analysis platform ZENIC ONE (UME) and deployed it across Liaoning province in China.
The system, jointly developed by ZTE and China Mobile, orchestrates the policies for the diagnosis flow through innovative flexible programming of fault diagnosis rules. Thereby, the intelligent management and control system can quickly respond to and meet the requirements of O&M staff to implement minute-level fault location.
In traditional PTN/SPN network operation, it is difficult to develop alarm-relativeness rules, so the location of substantial faults depends on the experience of senior O&M engineers. The diagnosis usually takes several hours with low efficiency. ZTE has found a new way of fault diagnosis to flexibly orchestrate diagnosis rules and policies in accordance with service scenarios to improve the efficiency of fault diagnosis and location.
Based on the cloud native and microservice architecture of the ZENIC ONE (UME), ZTE integrates the SPN intelligent fault diagnosis system onto the ZENIC ONE (UME) as an independent tool. This system uses the knowledge graph to build the diagnosis rules and develop the diagnosis process through a series of atomized diagnosis rules, which can be independently programmed by Drools. At the same time, the system adopts the jBPM workflow graphs and flexibly orchestrate rules and policies for different service scenarios, thereby enabling one-touch fast fault diagnosis and location of 4G and 5G base stations backhaul services.
ZTE and China Mobile have verified the fault diagnosis function of the system in 4G and 5G base station backhaul service interruption and packet loss scenarios on the existing network in Liaoning province. The faults are successfully located through backtracking and review of faults history. The fault location time is shortened from hours to minutes, and the graphical diagnosis policies and flows are completed by one touch. The system significantly reduces the O&M difficulty in existing network and highly improves the O&M efficiency.
Moving forward, ZTE and China Mobile will continue using AI technologies to promote system self-learning and enrich application scenarios such as mobile APP. On this basis, both parties will further implement closed-loop management from fault diagnosis to automatic service recovery, and push the Autonomous Networks to evolve its service guarantee capability from L2 to L3.