Anuket Project

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Name of the submitter: Sridhar K. N. Rao

Affiliation: LF/LFN/LFN-Anuket/Anuket-Thoth

Contact email: sridharkn@u.nus.edu

Country: India

Title of problem statement: Synthetic Observability Data Generation using GANs.

Description of problem statement : Refer to below table

Is data set available? (public/private): YES. and Public

Would you offer prizes or incentives for winners of this problem statement? :  YES.


CategoryDetails
IdITU-ML5G-PS-SODGANS
TitleSynthetic Observability Data Generation using GANs
Description

Observability data can be any of the following:

  1. Telco-Cloud Infrastructure Metrics (servers)
    1. H/W Level
    2. OS Level
    3. Virtualization Level
  2. Metrics/Statistics from Physical Network Elements.
  3. Application (virtualized Network functions) Metrics
  4. System logs (Servers, Applications, etc.)
  5. Metrics/Statistics from centralized orchestration systems (VIM, SDN-Controller, VNFM, NFVO, etc.)
  6. Metrics/Statistics from other control-plane services

Availability of these data for AI/ML researchers, who are not part of the Telco, is very difficult. To solve this availability issue, one approach is to generate synthetic observability data. In this project, we propose to generate this synthetic observability data using GANs.  For this first round only Telco-Cloud Infrastructure Metrics will be considered.

Challenge Track/Theme
Evaluation criteria
  1. Submission of the GANs implementation as Python (or any other language) program.
  2. Least error from the descriminator.
Data sourceReal-World observability data (Telco-Cloud Infrastructure Metrics) will be provided
ResourcesComputing resources can be provided to those who do not have access to one.
Any controls or
restrictions
Specification/Paper
reference
Contact

Sridhar K. N. Rao

sridharkn@u.nus.edu

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