AI/ML Models for NFV Usecases (Research and Develop)
- Lei Huang
- Keguang He
- Casey Cain
Internship Projects/Mentors
Title | AI/ML Models for NFV Usecases (Research and Develop) |
Status | Candidates Selected |
Difficulty | High |
Description
This project aims to develop AI/ML models for NFV-usecases. Any two of the following three problems can be considered.
VNF/CNF resource/performance/failure prediction
NFV log analysis with NLP
Synthetic monitoring and logging data generation using GANs
Problem | Model | Link | Comments |
|---|---|---|---|
Prediction of VNF Resource Demands | RNN, LSTM | ||
NFV log analysis with NLP | BERT | ||
Synthetic monitoring and logging data generation using GANs | GAN,CycleGAN,SeqGAN |
Additional Information
LFN Thoth: https://wiki.anuket.io/display/HOME/Thoth
LFN Acumos: https://www.acumos.org/
TensorFlow Time Series : https://www.tensorflow.org/tutorials/structured_data/time_series
Collectd : https://collectd.org/
Repo: https://github.com/opnfv/thoth
Learning Objectives
ML Techniques: Deep_learning.
ML model development
AI/ML for Telco Usecases.
Expected Outcome
Develop AI/ML model for NFV/Telco Usecases.
Deploy model with Acumos/Kubeflow framework.
Run Acumos/Kubeflow in Anuket Testbeds.
Comprehensive report on applications of AI/ML in Networking(Comparative analysis).
Relation to LF Networking
Anuket Thoth
Education Level
At least undergraduate
Skills
Knowledge of ML and ML-Tools - Tensorflow.
Future plans
This work can be enhanced to more useful and complex AI for NFV usecases in future.
Preferred Hours and Length of Internship
Part-Time
Mentor(s) Names and Contact Info
Click here to apply
Please read all instructions before applying. Include Resume, proof of school enrollment, and participation permission from school/employer
Lei Huang <huangleiyjy@chinamobile.com> (@Lei Huang)
Sridhar Rao <srao@linuxfoundation.org> (@Sridhar Rao)