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A novel cognitive network for AI-driven automation

The ETSI group on Experiential Networked Intelligence (ISG ENI) has just published a White Paper describing the design of a novel cognitive network. This White Paper explains how the ETSI ENI novel system architecture (based on ETSI GS ENI-005) intelligently manages, predicts, adjusts and optimises network behaviour using cognition management, thereby enhancing the operator experience.

“As technology becomes increasingly complex, managing telecommunication infrastructure grows in complexity. Operators need data-driven, context-aware tools to help them make the right decisions at the right time,” outlines Ray Forbes, Chair of the ETSI ISG ENI. “The ETSI ENI system is a set of hierarchical closed control loops based on extensions to the Observe-Orient-Decide-Act model. These extensions enable the ENI Cognitive Architecture to adapt its behaviour according to changes in user needs, business goals, and environmental conditions. As an example, the ENI system could reconfigure a set of 5G slices to meet changing service needs,” he adds.

Cognition is the process of acquiring and understanding data and information in order to produce new data, information, and knowledge. A cognitive system uses cognitive processes to understand how past behaviour, coupled with currently ingested contextual data and information, affects the goals that the ENI System is trying to achieve. The ENI Cognitive Management system models human decision-making processes to better comprehend the relevance and meaning of ingested data. Cognitive management enables the ENI System to experientially learn to improve its operation and performance. It also describes how cognitive management enables automation and produces autonomic behaviour.

Key takeaways of the White Paper include:

  • Exploration of the ENI cognition model,
  • Examination of multiple facets of the cognition process, including context awareness, situation awareness and the formal cognition process (perception, comprehension, and action),
  • Similarity between human cognition and ENI cognition, and the use of reactive, deliberative and reflective processes to implement ENI cognition.

The White Paper also describes some of the relevant technical details of the ENI System, as well as a number of recent innovative Proof of Concept projects.

CT Bureau

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