A theoretical framework for network monitoring exploiting segment routing counters
Self-driving networks represent the next step of network management techniques in the close future. A fundamental point for such an evolution is the use of Machine Learning based solutions to extract information from data coming from network devices during their activity. In this work we focus on a new type of data, available thanks to the definition of the novel SRv6 paradigm, referred to as SRv6 Traffic Counters (SRTCs). SRTCs provide aggregated measurements related to forwarding operations performed by SRv6 routers.