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Sl. No.ContributorContributionDurationCertificate of Appreciation/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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Sl. No.Activity by Intern/Researcher(s)                                                              WeekComment / Support from Advisor (s)               
1

Understand the state of art - Publications and OS projects

Analyze the Gaps.

Create a 1-Page report based on the analysis.

Identify for the problems in NFV for which the techniques are still not good enough.

1.5

Share the State of the art survey.

Provide initial gap - analysis.

2

Deploy the ML Framework (Tentative: LFN Acumos).

  • Document the usage workflow
  • Try any existing model.
1.5

Provide access to the server(s).

Intel Pod?

3

Collect, analyze and document the implementation of 3 existing models for NFV.

Collect the data.

1Provide the 3 models to use.
4

Deploy the models on the framework (2)

Collect the data (contd).

1None.
5Test and optimize the models - If possible.2Suggestion Suggestions for optimization approaches.
6Study ML technique for Synthetic time-series data generation (STSDG)1Suggest the right technique
7Implement the technique for STSDG2
8Test and optimize STSDG1
9Knowledge Transfer, Handoff (Buffer)1

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