Some embodiments of the invention provide novel methods for using probabilistic filters to keep track of data message flows that are processed at an element (e.g., forwarding element or middlebox service element) of a network. In some embodiments, the method iteratively switches between two probabilistic filters as the active and backup filters as a way of maintaining and refreshing its active probabilistic filter without the need for maintaining time values for removing outdated records from its active filter.

Some embodiments of the invention provide novel methods for using probabilistic filters to keep track of data message flows that are processed at an element (e.g., forwarding element or middlebox service element) of a network. In some embodiments, the method iteratively switches between two probabilistic filters as the active and backup filters as a way of maintaining and refreshing its active probabilistic filter without the need for maintaining time values for removing outdated records from its active filter.

Some embodiments of the invention provide novel methods for using probabilistic filters to keep track of data message flows that are processed at an element (e.g., forwarding element or middlebox service element) of a network. In some embodiments, the method iteratively switches between two probabilistic filters as the active and backup filters as a way of maintaining and refreshing its active probabilistic filter without the need for maintaining time values for removing outdated records from its active filter.

Some embodiments of the invention provide novel methods for using probabilistic filters to keep track of data message flows that are processed at an element (e.g., forwarding element or middlebox service element) of a network. In some embodiments, the method iteratively switches between two probabilistic filters as the active and backup filters as a way of maintaining and refreshing its active probabilistic filter without the need for maintaining time values for removing outdated records from its active filter.

Responsive to matching a site prefix to IPv6 network traffic from clients, the traffic as intended, and responsive to not matching the site prefix, classifying the corresponding traffic as unintended. An initial rate of packet occurrence and predict load caused by intended traffic and predicting load caused by unintended traffic is calculated, based on an initial rate of packet occurrence. The predicted traffic loads are fed back by configuring behavior of network modules according to the predictions of intended traffic load and unintended traffic load. Packet processing traffic at the network modules is based on traffic classification from the outcome of the AI-neuron.

Responsive to matching a site prefix to IPv6 network traffic from clients, the traffic as intended, and responsive to not matching the site prefix, classifying the corresponding traffic as unintended. An initial rate of packet occurrence and predict load caused by intended traffic and predicting load caused by unintended traffic is calculated, based on an initial rate of packet occurrence. The predicted traffic loads are fed back by configuring behavior of network modules according to the predictions of intended traffic load and unintended traffic load. Packet processing traffic at the network modules is based on traffic classification from the outcome of the AI-neuron.

There is provided a method and system for communication network management. There is provided an active TE architecture and procedure that rely on the epistemic uncertainty obtained from traffic forecasting models. According to embodiments, the traffic forecasting models can predict the mean of the network traffic demand and can extract one or more of the features relating epistemic uncertainty and the aleatoric uncertainty. According to embodiments, the epistemic uncertainty is used to vary the sampling frequency of network statistics in TE applications, for specific times or specific flows. A time-window can be used to predict network traffic can be varied (e.g. increased or decreased) to adjust the epistemic uncertainty.

A method for operating a time-sensitive network, TSN, having a first, high-importance segment and a second, low-importance segment, includes remapping, using TSN per-port priority regeneration, priority labels attached to data streams received on the first port and the second port to updated priority labels; splitting the data streams into a “preempting” class and a “preemptable” class based on a mapping from updated priority labels to classes; and forwarding the data streams from a border network element to at least one next-hop network element. When congestion is present on a link to the next-hop network element, the forwarding of “preempting” data streams takes precedence over the forwarding of “preemptable” data streams.

A method for operating a time-sensitive network, TSN, having a first, high-importance segment and a second, low-importance segment, includes remapping, using TSN per-port priority regeneration, priority labels attached to data streams received on the first port and the second port to updated priority labels; splitting the data streams into a “preempting” class and a “preemptable” class based on a mapping from updated priority labels to classes; and forwarding the data streams from a border network element to at least one next-hop network element. When congestion is present on a link to the next-hop network element, the forwarding of “preempting” data streams takes precedence over the forwarding of “preemptable” data streams.

A system can receive an indication associated with establishing a transmission control protocol (TCP) connection. The system can determine, based on the indication, information that identifies a user device associated with the TCP connection. The system can determine, based on the information that identifies the user device, a predicted congestion level of a base station associated with the TCP connection. The system can select, based on the predicted congestion level, a congestion control algorithm to be implemented for the TCP connection. The system can cause the TCP connection to be established and implement the congestion control algorithm for the TCP connection.