Machine Intelligence at the NOC

Network Operations Centers – the centralized monitoring and control stations for telecom networks – primarily deal with fault management and performance management to maintain network efficiency and customer satisfaction. The already high degree of automation in Ericsson’s NOCs is being enhanced using machine intelligence technologies – advanced analytics, deep learning, machine reasoning – to drive intelligent network operations that will enable emerging 5G systems to be highly perform ant while also being easy to use.

Incident Management is an area where we already use expert systems-based frameworks. However, the constantly changing nature of networks – both from a technology and from a deployment point of view – make it very challenging to maintain the human-written rules in such expert systems. Automated processing of incidents in a data driven domain agnostic manner, without the need for expert rules would help significantly enhance automation in NOCs. As an example, a fault in one node can lead to cascading faults in other nodes, resulting in a slew of alarms. Machine learning techniques enable us to discover co-occurring patterns in such a stream of alarms, and other events, which helps to quickly identify the root cause in most fault scenarios. This frees up the NOC operations teams, so they can focus on more complex challenges.