Introduction

Advisors

Accepted: Rohit Singh Rathaur

Sl. No.

Contributor

Contribution

Duration

Certificate of Appreciation/Contribution

1

Girish L

Survey of:

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

1 Month

Phase	Time
1	30 November 2021

Running ML-Framework with at least 3 existing models for NFV.
Generate Synthetic Data using ML.
Identify 3 problems for which ML can be applied in NFV - For which no acceptable models exist.
Identify the ML technique that can be used for these problems.

12 weeks, if the Intern is working Full-time.

Sl. No.	Activity by Intern/Researcher(s)	Week	Comment / Support from Advisor (s)
1	Understand the state of art - Publications and OS projects Analyze the Gaps. Create 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 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 server(s). Intel Pod?
3	Collect, analyze and document implementation of 3 existing models for NFV. Collect the data.	1	Provide the 3 models to use.
4	Deploy the models on the framework (2) Collect the data (contd).	1	None.
5	Test and optimize the models - If possible.	2	Suggestion for optimization approaches.
6	Study ML technique for Synthetic time-series data generation (STSDG)	1	Suggest the right technique
7	Implement the technique for STSDG	2
8	Test and optimize STSDG	1
9	Knowledge Transfer, Handoff (Buffer)	1