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Huawei Launches iMaster NCE, an Autonomous Network Management and Control System for the Enterprise Market

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[Shanghai, China, September 18, 2019] During HUAWEI CONNECT 2019, Huawei officially launched the industry's first autonomous network management and control system iMaster NCE. This innovative system integrates management, control, and analysis to help enterprise networks smoothly transition from the SDN era to the autonomous driving era.

An intelligent world is gaining momentum. AI, the driver of an intelligent world, will gradually extend to various industries and become integral in every aspect of the worldwide economy.

According to Huawei GIV 2025, the AI penetration rate will reach 97% in large enterprises by 2025. The application of AI is growing rapidly in the enterprise network field. By injecting intelligence into the network, AI not only enables the enterprise network to have a high degree of automation, but also equips the network with intelligent capabilities such as service intent understanding, optimal network recommendation, change risk assessment, and closed-loop troubleshooting. AI lays the foundation for autonomous enterprise networks, facilitating the digital transformation and efficient operations of enterprises.

Delivering network-layer AI for Huawei intelligent IP networks, iMaster NCE is an intelligent management and control system for enterprise networks. This system adopts a platform-based software design concept and seamlessly combines AI, big data, and cloud computing technologies. It integrates traditional network management functions, SDN control functions, and network data analysis functions based on service intents.

With the AI engine, iMaster NCE automatically recommends optimal networks based on service intents. This facilitates enterprise network planning, design, and deployment, reduces network deployment costs, and accelerates service rollout. In small- and medium-sized campus network scenarios such as stores and hotels, iMaster NCE automatically generates the network topology, brings devices online, and provisions services based on industry scenarios and service requirements specified by customers. This shortens network deployment from 3 days to 0.5 days.

Based on big data analytics, iMaster NCE uses AI-based network simulation technology to continuously evaluate the impact of changes and proactively analyze faults 24 hours a day, 7 days a week. This not only ensures real-time service experience, but also allows enterprise applications to be rapidly changed, recovered, and located. In data center network scenarios, iMaster NCE uses AI-based intelligent fault injection and analysis, enabled by continuous learning, to detect faults within 1 minute, locate faults within 3 minutes, and rectify faults within 5 minutes. In campus wireless network scenarios, iMaster NCE uses machine learning algorithms to intelligently adjust channels, bandwidth, and power based on analysis of historical traffic statistics collected through Telemetry. In comparison tests conducted by Tolly, a leading global provider of testing and third-party validation and certification services, iMaster NCE delivered a 50% improvement in the overall performance of a wireless network after optimization.

The Huawei developer ecosystem, combining a wealth of graphical development tools and online sandbox environments, more than 500 APIs, and a growing library of video courses (more than 10 to date), supports agile innovation and development of applications by ecosystem partners and helps enterprise customers quickly obtain end-to-end business solutions.

Huawei is committed to building an autonomous network that "leaves complexity to itself and brings simplicity to customers". To date in the SDN market, Huawei has worked together with more than 6,000 enterprises worldwide and delivered more than 850 commercial projects. With the launch of iMaster NCE for the enterprise market, Huawei will better serve global enterprise customers and help them continuously improve service experience and network operations efficiency.