Experiential Networked Intelligence

Our Experiential Networked Intelligence Industry Specification Group (ENI ISG) is defining a Cognitive Network Management architecture, using Artificial Intelligence (AI) techniques and context-aware policies to adjust offered services based on changes in user needs, environmental conditions and business goals. 

The use of Artificial Intelligence techniques in the network management system should solve some of the problems of future network deployment and operation.

Our ISG on Experiential Networked Intelligence (ENI) develops standards for a Cognitive Network Management system with the aim to introduce a metric for the optimization and adjustment of the operator experience over time by taking advantage of machine learning and reasoning. We employ the ‘monitor-analyse-plan-execute’ control model which enables the system to adjust the offered services based on changes in user needs, environmental conditions and business goals.

The policy modelling will encompass open intelligent functionality for network configuration and management. We provide inputs and objectives to support the industry’s progress in intelligent policy-based management.

The introduction of technologies such as SDN, NFV and network slicing means that networks are becoming more flexible and powerful. These technologies transfer much of the complexity in a network from hardware to software, from the network itself to its management and operation. ENI will make the deployment of SDN and NFV more intelligent and efficient and will assist the management and orchestration of the network.

ENI has specified a set of use cases and the derived requirements for a generic technology independent architecture of a network supervisory assistant system based on the ‘observe-orient-decide-act’ control loop model. This model can assist decision-making systems, such as network control and management systems, to adjust services and resources offered based on changes in user needs, environmental conditions and business goals.

A gap analysis of work on context-aware and policy-based standards is being considered, working with other Standards Developing Organizations to reuse existing standardized solutions for legacy and evolving network functions wherever possible. Adding closed-loop AI mechanisms based on context-aware, metadata-driven policies to more quickly recognize and incorporate new and changed knowledge, and hence, make actionable decisions, in day-to-day-operations. Security and a closed loop learning policy-model are subjects to be addressed shortly.

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News, comments and opinions from ETSI’s ENI Industry Specification Group

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In September and October 2018, the ETSI ENI ISG has presented its achievements in two forums, a joint Network Intelligence Forum by ETSI ENI and CCSA TC610 (Formerly China SDN/NFV Industry Alliance) in Beijing, China, and SDN/NFV World Congress in Hague, Netherlands.

ENI SDN NFV 2018 2

During the Network Intelligence Forum, there were 12 presentations from the ISG members and leadership on network intelligence. These were presented by the Chair and Vice Chair of ENI, member operators including China Telecom, China Mobile, China Unicom, as well as vendors (Including: Huawei, ZTE, Intel, AsiaInfo Technologies, etc.) and Tsinghua University. The demonstration of the first ENI PoC project was presented by the PoC members including China Telecom, Huawei, Intel, which is the world’s first demo of an intelligent transport network slicing prototype system based on AI technology.ENI SDN NFV 2018

In the SDN/NFV World Congress, a special workshop was held focusing on ENI. During this workshop, the Chair, Technical Manager and assistant Rapporteur of ENI gave three presentations on recent progress, use cases and PoC & Demonstrations.

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ETSI ISG ENI Chairman, Aria’s Head of Research and ISG ENI Technical manager Outline ETSI ENI’s AI Use Cases, System Architecture and the China Telecom Led Proof of concept at SDN NFV World Congress in The Hague.

Over the last few years, Layer123’s SDN NFV World Congress has emerged as the best place to assess the mood and state of progressive thinking in telecom operations. So it was fitting that this year’s program included a progress report from the Experiential Networked Intelligence (ENI) Industry Specification Group (ISG) team developing a reference model for the use of AI in telecom operations.


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