There is provided a method for adaptive bitrate (ABR) adjustments in an IP network before making upshift of ABR level of media streams like video for live Over the Top (OTT) distribution. Example methods may include initiating, at a first time interval, probing of the IP network to determine if a first candidate bitrate is applicable, where the first candidate bitrate is greater than a preset bitrate of a client device data stream, determining that the candidate bitrate is applicable, increasing a transfer bitrate of the client device data stream, and initiating, at a second time interval, probing of the IP network to determine if a second candidate bitrate is applicable, where the second candidate bitrate is greater than the first candidate bitrate.

Systems and methods are provided for managing data proxies. The systems and methods enable a proxy management system to store and manage data proxies that digitally represent real-world objects equipped with sensors. The data proxy of an object is made up of data sampled by the object's sensors and data estimated using the sampled data. The sampling rate at which the data is sampled can be optimized such that it conforms with target quality of data (QoD) requirements and/or target data acquisition costs. The QoD requirements can be based on requirements set by each of the applications associated with an object. The proxy management system can use the sampled data and estimated data to (1) ensure that incoming messages, if executed, would not have negative consequences; and (2) monitor objects to determine if and when they are expected to approach undesirable states, or if they have already reached such undesirable states.

A method and a communication system configured to operate in a network cloud, are provided. The system comprising a plurality of physical network elements and a server, where the latter is configured to operate as a cloud orchestrator which receives information related to key performance indicators (KPIs) collected from the plurality of physical network elements, and determines whether a pre-defined action that relates to a respective physical network element needs to be executed based on a) one or more threshold values stored at the cloud orchestrator and associated with these KPIs, and b) the information collected from the plurality of physical network elements.

A network device includes a plurality of interfaces configured to receive, from a network, packets to be processed by the network device. A load determination circuit of the network device is configured to determine whether a packet traffic load of the network device is above a traffic load threshold, and a dual-mode counter module is configured to (i) determine a count of quanta associated with the received packets using a first counting mode in response to the load determination unit determining that the packet traffic load is above the traffic load threshold, and (ii) determine a count of quanta associated with the received packets using a second counting mode, different than the first counting mode, in response to the load determination unit determining that the packet traffic load is not above the traffic load threshold.

A method of optimizing network traffic visibility resources comprises receiving, by a controller associated with a network traffic visibility system, information indicative of operation of the network traffic visibility system. The method further comprises facilitating, by the controller, control of resources in the network traffic visibility system, according to a configured resource control policy. The facilitating can include providing, by the controller, control signaling to cause maximization of network traffic monitoring fidelity for a plurality of Quality of Service (QoS) classes of network traffic, based on a specified fixed amount of one or more network resources associated with the network traffic visibility system. Alternatively or additionally, the facilitating can include providing, by the controller, control signaling to cause minimization of use of the one or more network resources, based on a specified fixed level of traffic monitoring fidelity associated with the plurality of QoS classes.

A method of monitoring a network is provided that includes receiving a stream of samples having respective network delay values; defining at least one first group of samples having a size defined by a window size; determining respective first network delay characteristics for the first groups based on the network delay values corresponding to the respective samples included in the corresponding group; applying a first test to the first network delay characteristic determined for the respective first groups; adjusting the window size based on a result of the first test associated with the respective first groups; using the adjusted window size, define respective second groups of samples having samples of the stream of samples subsequent to the samples included in the at least one first group; determining a second network delay characteristic for the respective second groups; applying a second test to the second network delay characteristics; and determining whether to generate an alert notification based on a result of at least one of the first and second tests.

For dynamically determining packet sampling rates, a method including setting a packet sampling rate for one or more switch ports, collecting for an interval of time a plurality of statistics for the one or more switch ports, and adjusting the packet sampling rate in response to one or more of the plurality of statistics.

In one embodiment, a supervisory service for a software-defined wide area network (SD-WAN) obtains telemetry data from one or more edge devices in the SD-WAN. The service trains, using the telemetry data as training data, a machine learning-based model to predict tunnel failures in the SD-WAN. The service receives feedback from the one or more edge devices regarding failure predictions made by the trained machine learning-based model. The service retrains the machine learning-based model, based on the received feedback.

In a method of identifying matching packets at different locations in a network, a first plurality of packets is received at a first location in the network, and a first subset thereof is selected in accordance with a filter. A second plurality of packets is received at a second location in the network, and a second subset thereof is selected in accordance with the same filter. Each packet in the first and second subsets is parsed to extract invariant header fields from an outermost IP header inwards, until a minimal set of invariant header fields is obtained for that packet, or until it is determined that a minimal set is not obtainable for that packet. A packet signature is computed from the minimal set for each packet having a minimal set, and the packet signatures arc compared to identify matching packets in the first and second subsets.

The present disclosure provides a system and a method of adjusting data collection frequency. the system includes a server, a gateway and a sensor. The gateway is communicated with the server for data transmission. The sensor is configured to transmit the sensor data to the gateway, wherein the gateway transmits the sensor data to the server based on a first frequency, and is triggered to transmit the sensor data and a historical sensor data based on a second frequency in case the server or the gateway detects an alert event when processing the sensor data, wherein the historical sensor data is related to the alert event, so that the server analyzes the historical sensor data to get a diagnostics on the alert event, wherein the second frequency is higher than the first frequency.