Artificial Intelligence Framework for Network Management
draft-pedro-nmrg-ai-framework-04

Abstract

The adoption of artificial intelligence (AI) in network management (NM) solutions is the way to resolve many of the complex management problems arising from the adoption of NFV and SDN technologies. The AINEMA framework, as discussed in this document, includes the functions, capabilities, and components that MUST be provided by AI modules and models to be successfully applied to NM. This is enhanced by the consideration of seamless integration of different services, including the ability of having multiple AI models working in parallel, as well as the ability of complex reasoning and event processing. In addition, disparate sources of information are put together without increasing complexity, through the definition of a control and management service bus. It allows, for instance, to involve external events in NM operations. Using all available sources of information --- namely, intelligence sources --- allows NM solutions to apply proper intelligence processes that provide explainable results instead of simple AI-based guesses. Such processes are highly based in reasoning and formal and target-based intelligence analysis and decision --- providing evidence-based conclusions and proofs for the decisions --- in the form of AI method outputs with explanations. This will allow computer and network system infrastructures --- and user demands --- to grow in complexity while keeping dependability.

Authors

Pedro Martinez-Julia
Shunsuke Homma
Diego Lopez

(Note: The e-mail addresses provided for the authors of this Internet-Draft may no longer be valid.)