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AI Powered L4 autonomus Change management with network digital twin

URN C25.0.828
Topics Autonomous networks

Ensure zero accident through AI-empowered change management

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With proliferation of AI/GenAI applications and exponential growth of IP network scale, any configuration errors can affect the entire network, making it increasingly difficult to evaluate the impact of IP network changes on services. As such, it has become one of the major root causes of network faults and accidents in recent years. Since network changes are directly related to service operations, any successful change needs to not only ensure that new services are provisioned smoothly, but also that existing services are not affected and that no problems are introduced. O&M personnel are, therefore, increasingly cautious about making network changes, given that they need to review the solution design as well as evaluate all change impacts, before making any change. Then, after the change, they need to manually monitor the newly changed network onsite for two or three consecutive days, to ensure that the change brings about the desired results. However those traditional verification approaches need to tackle many challenges such as inaccurate checks, unable to cover the entire network with incomprehensive verification, lengthy testing and troubleshooting. Therefore global telecom operators still suffer from network-wide service disruption and major network incidents.

Team members

China Academy of Information and Communications Technology(CAICT) logo
Champion
China Mobile Communications Corporation logo
Champion
China Telecommunications Corporation logo
Champion
China Unicom logo
Champion
China Unitechs Co.,Ltd. logo
Huawei Technologies Co. Ltd logo
ZTE Corporation logo

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