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Intent-driven slice management in autonomous network - Phase IV

URN C24.0.638
Topics Autonomous networks, Network slicing, Service orchestration

Implementing intent-driven grammar and machine learning to balance competing slice management expectations.

This catalyst will enhance the current standard/APIs to capture the slice profile and use automated ML mapping to capture all necessary information to manage the slice. (i.e., mapping of intent to a slice). To solve this problem we propose implementing a POC for slice management that (1) defines the necessary APIs to manage the slice across multiple networks, and (2) defines the necessary APIs to allow an ML algorithm to balance multiple TR290A Intents simultaneously. The proposed POC will be built in a sandbox with API calls to network functions stubbed out. To enhance the current standard/APIs to capture the slice profile and all necessary information via automated ML mapping to manage the slice (i.e., Mapping of intent to a slice). This includes dynamic orchestration. The final results of this phase of the work will be the ability to provision, operate, and maintain a slice using the Intent grammar in an autonomous network environment.


Explore the previous phases of this project

Intent-driven autonomous networks for smart mobility - Phase I

Intent-driven autonomous networks - Phase II

Intent-driven autonomous networks - Phase III

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Team members

Amdocs Management Limited logo
AriaNetworks logo
EITC  (DU) logo
Infosys logo
Verizon Communications logo

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