Topic Leader(s)
- Rohit Singh RathaurGirish L 30 Minutes
AI/ML for NFV Usecases
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30m, Rohit Singh Rathaur Girish L AI has the potential in creating value in terms of enhanced workload availability and improved performance and efficiency for NFV use-cases. This work aims to build machine-Learning models and Tools that can be used by Telcos (typically by the operations team in Telcos). Each of these models aims to solve a single problem within a particular category. For example, the first category we have chosen is Failure prediction, and we have created 6 models - failure prediction of VMs. Containers, Nodes, Network-Links, Applications, and middleware services. Now, we have created a model for the Failure Prediction of VMs. This project also aims to define a set of data models for each of the decision-making problems, that will help both providers and consumers of the data to collaborate. A failure prediction system could be deployed to help the NFV system avoid unexpected failure in advance. The main purpose of the session is to demonstrate failure prediction models and also we will present different AI/ML use cases for NFV.
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