Abstract: A system for early predicting of impending data overflow situations in data networks, comprising one or more sensors being networked computers that do not provide services, for collecting monitored data regarding network traffic volume from content providers to an Internet Service Provider (ISP) entering or exiting the ISP via peering autonomous systems connected to the ISP via physical links; one or more processors executing one or more deep learning models, being adapted to: identify over the data network being handovers alternative peering links, which are not inherent Private Network Interconnects (PNI) between the content providers and the ISP; determine static or dynamic threshold for dataflow anomaly associated with overflow; for each alternative handover, predict impending overflow situation by applying ML algorithms to the collected data that corresponds to the each alternative handover.

Abstract: A system for early predicting of impending data overflow situations in data networks, comprising one or more sensors being networked computers that do not provide services, for collecting monitored data regarding network traffic volume from content providers to an Internet Service Provider (ISP) entering or exiting the ISP via peering autonomous systems connected to the ISP via physical links; one or more processors executing one or more deep learning models, being adapted to: identify over the data network being handovers alternative peering links, which are not inherent Private Network Interconnects (PNI) between the content providers and the ISP; determine static or dynamic threshold for dataflow anomaly associated with overflow; for each alternative handover, predict impending overflow situation by applying ML algorithms to the collected data that corresponds to the each alternative handover.