All-Cloud is the Future of Enterprise Campus Network

All-Cloud network Architecture helps global enterprises to enable digital transformation in campus network, multi-region branch, and IoT scenarios. Technologies continue to develop and innovate at an unprecedented rate, enterprise services will change rapidly, and network systems will change accordingly. We believe that these trends will change enterprise networks.

Cloud-based Enterprise Network Management Extends from Small-Sized Branch Campuses to Medium- and Large-Sized Campuses

Medium- and large-sized campuses with large networks and complex services want to use cloud management solutions to reduce operating expense (OPEX). Medium- and large-sized enterprise networks will support unified cloud-based management. In the enterprise campus network management solution, some specific problems will be solved to allow various traditional network devices (such as high-end wired network devices and independent wireless controllers) to support cloud-based management. This solution meets high-performance large-scale networking requirements, and supports large-scale Wi-Fi roaming. It also meets requirements of medium- and large-sized campuses for diversified user authentication and policy management, and ensures an excellent user experience. An intelligent operations and maintenance (O&M) platform is provided to support O&M of large-scale complex networks. Proactive security discovery and network security association are supported for detecting and eliminating security risks in a timely manner, meeting security requirements of networks with high specifications.

Next-Generation Artificial Intelligence (AI) Predictive Network O&M

Manual and passive O&M is replaced by intelligent and predictive O&M, greatly reducing the labor cost.

Next-generation network O&M will support automatic closed-loop network monitoring, problem analysis, and fault rectification, achieving intelligent and proactive O&M. In terms of network monitoring, multi-dimensional information can be collected in seconds, and user, application, and network profiles will be provided to support problem analysis. In terms of problem analysis, faults can be detected in a timely manner based on the scenario-specific expert experience fault tree and AI learning, and root causes can be identified based on correlation analysis of users, applications, and networks. Networks can then be automatically and dynamically optimized based on enhanced learning and network association.

Breakthroughs Will Be Made in Automatic Service Provisioning

The system can automatically identify graphical and service-based instructions or intentions without requiring network languages, automatically invoke virtualized and network resources, and overcome underlying technical differences to implement rapid and automatic service rollout. The work on the underlying physical network that was previously carried out manually is automatically completed by the system, improving efficiency and accuracy. As services vary between companies, the system can deliver standard application programming interfaces (APIs) to interconnect with service modules of different companies and accommodate varying service requirements. In 2018, as technologies become more mature, automatic service provisioning will have a qualitative breakthrough. Automation systems that meet customer requirements will stand out and benefit customers.

AI Becomes the Key Technology to Defend Against Unknown Threats

Single-point defense will transition to entire-network defense, and passive defense to active defense. All security information on a network will be collected and uploaded to the security and policy analysis center of the network. The center analyzes security information of the entire network and verifies the information and multiple phenomena to identify network security threats and security events. Additionally, the center generates countermeasures based on the analysis results and implements proactive defense. During this process, machine learning is of great significance. It must be able to dynamically discover network security events and provide the correlation analysis capability, offering accurate and effective generated defense measures and a low false positive rate. That is, machine learning has the characteristics of AI, and network security no longer depends on manual operations. In the next few years, networks will still have to mitigate attacks. However, network security will become predictable, enabling proactive defense.

Converged High-Performance Wi-Fi Networks Will Be Able to Support Enterprise and IoT Industry Applications

Traditional wireless campus networks will be redesigned. With the aid of innovative campus cloud-based IoT solutions, enterprises can quickly deploy an enterprise campus IoT network, provide robust wired networks, and deliver high-speed wireless network access. It is expected that 802.11ax APs will be put into commercial use in a few pioneering enterprises in 2018. In addition, the ultra-broadband network using 802.11ax APs will support IoT applications, such as energy consumption management of office buildings, electronic shelf label (ESL) access in retail stores, key asset tracing, and intelligent conference rooms. As an open network, the ultra-broadband network will help enterprises quickly integrate existing ecosystem partners and accelerate the digitization of their business.

 

Author's Bio

George  Zhao

George Zhao

Director, OSS & Ecosystem at Huawei Technologies Co., Ltd.

George has 25 years of working experience in networking, software architecture and has been an open source evangelist for the past 4 years. He currently is director of open source and ecosystem at Huawei Technologies Co., Ltd. George starts to participate in ONUG working groups since April 2016.

George received a bachelor in E.E. from McGill University and master’s on computer engineering from the University of Toronto.