An Overview on Application of Machine Learning Techniques in Optical Networks

Understand

Today's telecommunication networks have become sources of enormous amounts of widely heterogeneous data.

• This information can be retrieved from network traffic traces, network alarms, signal quality indicators, users' behavioral data, etc.
• Advanced mathematical tools are required to extract meaningful information from these data and take decisions pertaining to the proper functioning of the networks from the network-generated data.
• Among these mathematical tools, Machine Learning (ML) is regarded as one of the most promising methodological approaches to perform network-data analysis and enable automated network self-configuration and fault management.