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Introduction

AI has potential in creating value in terms of enhanced workload availability and improved performance and efficiency for NFV usecases. 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 single problem within a particular category. For example, the first category we have chosen is Failure prediction, and we aim to create 6 models - failure prediction of VMs. Containers, Nodes,  Network-Links, Applications, and middleware services. This project also aims to define set of data models for each of the decision making problems, that will help both provider and consumer of the data to collaborate.

Name

Thoth

Approach

Decision Driven Data Analytics. 

https://mitsloan.mit.edu/ideas-made-to-matter/decisions-not-data-should-drive-analytics-programs

PTL

Sridhar K. N. Rao (Sridhar Rao)

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Meeting ID: 961 6391 1066
Find your local number: https://zoom.us/u/acEvZCMvjT

Weekly Meeting minutes

04-June-2021


Contributions


Sl. No.ContributorContributionDurationCertificate of Appreciation OR Contribution
1Girish L

Survey of:

  1. Existing works on AI/ML in Networking - works related to NFV - problems, ML-Techniques, Data, etc.
  2. NFV Problems - Event Correlation, VNF Placement, Anomaly Detection, VNF Failure Prediction, and Synthetic Data Generation.
  3. OSS Projects for AI/ML that can be (re)used
1 Month

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