Embodiments of this disclosure provides an indicator determining method and a related device, to predict KQI results of different services by using a network KPI parameter. The method of the embodiments of this disclosure includes: obtaining to-be-predicted data of a service, where the to-be-predicted data includes a key performance indicator KPI of a network in which the service is located and a type identifier of the service, and the type identifier is indicative of a type of the service; determining, based on the type identifier, a target predictive model in a predictive model set, where the predictive model set includes at least one predictive model, and each predictive model in the predictive model set corresponds to one service type; and determining, based on the target predictive model and the KPI in the to-be-predicted data, a key quality indicator KQI of the service.

An information processing device capable of reducing an amount of data to be monitored in an onboard system is provided. The information processing device obtains a first log from the onboard system, determines whether an abnormality is included in communication data of the first log using the first log, and, in a case where the abnormality is determined to be included in the communication data, outputs first detection results indicating that the abnormality is included in the communication data to the onboard system. The first detection results is output, as a transmission instruction to cause transmission of a second log from the onboard system to the information processing device, with the second log including a larger amount of data than the first log.

The disclosed subject matter is directed towards a clear channel assessment procedure based on a common preamble, such as for use with 3GPP and IEEE 802.11 technologies, or any other radio technology, including for use in the 6 GHz band. Detection of the common preamble is based on detecting known sequences in signal part, which can be detected without decoding the preamble's payload (channel) part to determine an ongoing transmission's duration. If an ongoing transmission is detected, subsequent energy detection monitoring is performed to determine when transmission ends, which can use a different energy detection threshold from what is used in the initial clear channel assessment's energy detection. The technology facilitates the usage of different sampling rates by different radio technologies that work concurrently in the same unlicensed band, by correlating a received preamble with a stored preamble that accounts for deterministic distortions arising from the different sampling rates.

A network monitoring device responds to network status data (whether pushed from the network device or pulled from the network device) to maintain a buffer of saved status data. The network status data is reordered, manipulated, and presented to users of the network monitoring device in order. The monitoring device can provide a status report of the network environment. When network status data is delayed too long, the monitoring device can discard the network status data, or reduce its weighted consideration. The monitoring device attempts to balance accuracy and latency by adjusting wait time for network status data. The monitoring device maintains a record of the amount of network status data it receives and processes from each network device and each network device's ability to provide accurate and complete information to operators and users in a distributed network monitoring environment.

A network visibility appliance automatically and dynamically determines a data traffic sampling policy that it should apply, i.e., a policy for determining which flows the network appliance should forward to one or more tools. The technique can be used to adjust for changes in network traffic to avoid exceeding performance constraints (e.g., maximum throughput) of network analytic tools, while maintaining high efficiency of usage of the tools. In the technique, a policy engine monitors network traffic characteristics in a subscriber throughput table and dynamically determines a sampling policy to apply, so as to decrease and/or increase traffic throughput to a given tool, so that the tool is efficiently used.

Processes and systems described herein are directed to determining efficient sampling rates for metrics generated by various different metric sources of a distributed computing system. In one aspect, processes and systems retrieve the metrics from metric data storage and determine non-constant metrics of the metrics generated by the various metric sources. Processes and systems separately determine an efficient sampling rate for each non-constant metric by constructing a plurality of corresponding reduced metrics, each reduced metric comprising a different subsequence of the corresponding metric. Information loss is computed for each reduced metric. An efficient sampling rate is determined for each metric based on the information losses created by constructing the reduced metrics. The efficient sampling rates are applied to corresponding streams of run-time metric values and may also be used to resample the corresponding metric already stored in metric data storage, reducing storage space for the metrics.

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. The invention is based on before upshifting of a current ABR level to a higher ABR level for one or more client devices, probing the network system with a higher bitrate of the data stream provided by e.g. replicating data in the data stream, and monitoring network conditions during probing. Based on the probing it is determined if the available resources in the network are sufficient to sustain an upshift of ABR-level for the client device.

A data collection apparatus collecting data from a terminal device connected through a communication path, comprising a schedule managing unit determining a schedule transmitting a data acquisition request to the terminal device according to managed timing data, a transmission amount adjusting unit adjusting a transmission amount of the data acquisition request, and a collected data managing unit managing the data collected from the terminal device, in which the schedule managing unit manages a start point time that is a time at which a data collection from each terminal device starts, a collection period that is an interval of the data collection from each terminal device, a retransmission interval that is a time until the data acquisition request is retransmitted when the data collection from the terminal device fails, and a retransmission number that is the number of times to retransmit the data acquisition request as the timing data.

Embodiments of the disclosure pertain to activating in-band OAM based on a triggering event. Aspects of the embodiments are directed to receiving a first notification indicating a problem in a network; triggering a data-collection feature on one or more nodes in the network for subsequent packets that traverse the one or more nodes; evaluating a subsequent packet that includes data augmented by the data collection feature; and determining the problem in the network based on the data augmented to the subsequent packet.

Disclosed herein is a method and apparatus for converting a stream of samples at a first sampling rate to a stream of samples at a second sampling rate. An exemplary method includes measuring the first sampling rate; determining a first upsampling factor from a basis including: the measured first sampling rate, the target value of the second sampling rate, and a resynchronisation error factor, the first upsampling factor being constrained to be an integer power of a predetermined integer value; and deriving, from a reference set of filter coefficients and from a ratio of the first upsampling factor to a reference upsampling factor, a first set of filter coefficients for use in a first interpolation filter, the reference set of filter coefficients being for a reference upsampling factor that is an integer power of the predetermined integer value.