Anuket Project

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Overview

Project NameEnter the name of the project
Target Release NameNile
Project Lifecycle StateIncubation

Scope

This project 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.

Requirements

CategoryJira ReferenceDescription
ModelTBA
  1. Existing: Sridhar Rao  Rohit Singh Rathaur Abhishek Jangid Yichen Li - Failure Predictions (FP) Models: We have developed Neural Network models for predicting failures in Virtual Machines (VMs) used in Network Function Virtualisation (NFV) by analysing VNF data. The data used to build these models are provided by Orange Labs, and the VMs are based on project Clearwater. 
  2. Ongoing: TBA Sridhar Rao  Rohit Singh Rathaur Abhishek Jangid Yichen Li 
ToolsTBA
  1. Existing: TBA Sridhar Rao Lei Huang 
  2. Ongoing:

(1) NICIP platform (gitlab) Yan Yang Lei Huang 

(2) Others Sridhar Rao  

Framework

TBA

Upstream: TBA Sridhar Rao 

Thoth:

  1. Collaboration with Mindspore Lei Huang 
  2. Kubeflow/Acumos Sridhar Rao 
Researchhttps://jira.anuket.io/browse/THOTH-24NICIP research paper Lei Huang 
NICIPhttps://jira.anuket.io/browse/THOTH-17
  1. Collect network intelligence scenario requirements from operators, publish network intelligence scenarios and research reports in collaboration with ITU-T 13 project Beth Cohen Mehmet Toy Lei Huang 
  2. Publish at least one network intelligence scenario competition problem on NICIP platform Lei Huang 
  3. Publish at least one open network operation and maintenance data set on the network intelligent collaborative innovation project platform Lei Huang 
  4. Create NICIP project specific page on LFN website(like 5G BP), and publicize project through Webinar and other meeting, including LFN DTF, ONES,etc. Lei Huang 
  5. Jointly promote R&D with external open source communities such as LF AI Lei Huang


Release Artifacts

NameDescription

Format (Container, Compressed File, etc.)

ML-Models
  1. Failure Prediction Model
  2. Log-Analysis
  1. Jupyter notebook
  2. Python Application (Adaptable to ML-Framework)
  3. Containerized ML-Model (Kubernetes based ML-Framework).
ToolsData ExtractionPython Application - Jupyter Notebook
Research Studies

AI/ML problems in NFV, OSS Frameworks

AI/ML & Kubernetes in NFV

.md files and/or pdf files.
ML-FrameworkUpstream ML framework projectIntegration Code.

Architecture

High level architecture diagram

Insert diagram or link.

Internal Dependencies

None

External Dependencies

None

Test and Verification

Describe how the project will be tested and verified.

Risks

List any risks and a plan to mitigate each risk.

Risk DescriptionMitigation Plan
DevelopersInterns
TestbedRequest for Intel POD-18
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