Synthetic Observability Data Generation using GANs | AI/ML IN 5G CHALLENGE

Obtaining real-world dataset for AI/ML model development and testing for NFV use cases is extremely difficult for those who are not actively working in this domain for a telco. This difficulty arises due to the nature of business – stringent policies and rules under which the telecom companies have to adhere to. Even the infrastructure metrics, which is the focus of this work, and which may not include any sensitive information, is very difficult to obtain from the real-world NFV environments. This challenge (ITU-T) – generating observability data using GANs, is the first step towards overcoming this difficulty. This talk will elaborate on the problem, explain in detail the dataset, and discuss why GANs can help to solve this problem.

Speakers:
Kai Lu, Researcher, China Mobile Research Institute
Sridhar K. N. Rao, Architect (Networking and Edge), Linux Foundation
Lei Huang, Researcher in AI and Intelligent Operation R&D Center, China Mobile Research Institute

Moderators:
Vishnu Ram OV, Independent Research Consultant, International Telecommunication Union (ITU)

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The views and opinions expressed are those of the panelists and do not reflect the official policy of the ITU.