12 results about "Network performance analysis" patented technology

In one implementation, a method herein comprises: determining a given time during which a computer network is unstable in response to a topology event within the computer network; causing, in response to the computer network being unstable, a measurement analysis process to perform network performance analysis on the computer network based on the computer network being unstable during the given time; and causing, in response to determining that the computer network is otherwise in a stable state, the measurement analysis process to perform network performance analysis on the computer network based on the computer network being stable.

To store network performance data for later retrieval, performance data files corresponding to a test cycle are retrieved, reformatted into unified data files according to a predetermined unified file format and a set of predefined unified category identifiers, and stored in a query database. The reformatting can match predefined unified category identifiers with data category identifiers in the performance data files, and the corresponding data values ​​can be stored sequentially in the unified data files or used to increment counter values ​​in similarly stored aggregated counter files. In addition, configuration data files for network cells can be stored less frequently than the frequency of the test cycles. Later retrieval can retrieve both the unified data files and the configuration data files corresponding to a selected time frame and network portion, and merge or aggregate the data appropriately for performance indicator calculations.

The invention discloses a performance analysis and management method of a 5G network. The method comprises the following steps: 1, modeling a data flow arrival process by using an arrival curve; 2, modeling the service capability by using a service curve; 3, judging whether a plurality of network nodes are connected in series, and if so, entering step 4; otherwise, judging whether a plurality of data streams share the same network node, if so, entering the step 5, and if not, entering the step 6; 4, calculating a total service curve of a series path, and entering step 7; 5, calculating a residual service curve provided for a single data stream, and entering step 7; 6, acquiring a service curve when a single data stream flows through a single network node, and entering step 7; 7, calculating an end-to-end performance boundary when the data stream flows through the network node based on the arrival curve and the service curve; and 8, applying the performance boundary to planning, resource management or service quality assurance decision of the 5G network. According to the invention, flow management, service quality guarantee and network performance analysis of the 5G network are realized.

An apparatus and method for network performance analysis are provided. The device is configured to receive network data. The device then parses the received network data into a data set, the data set comprising a topology of the network. The device is also configured to determine one or more performance metrics for the network based on the data set, based on a mean time to failure (MTBF), and based on a time required to repair a fault in the network. Further, the apparatus is configured to determine a performance of the network based on the one or more performance metrics.

The invention provides an optical fiber network performance evaluation method and system based on transfer learning, and the method comprises the steps: firstly extracting the performance knowledge of a source domain optical fiber network in different operation scenes, constructing a source domain performance knowledge graph containing a performance event, parameter and state association relation, and then collecting the real-time operation performance characteristics of a target domain optical fiber network, performing layer-by-layer mapping with a source domain knowledge graph to obtain a mapped performance knowledge graph, fusing the mapped knowledge graph into a target domain evaluation model through feature coding, interlayer injection and parameter adaptation to generate a transfer learning evaluation model, and inputting performance data of the target domain optical fiber network in a preset time period into the transfer learning evaluation model to obtain a transfer learning evaluation result. And finally, based on the performance evaluation result, generating a target domain optical fiber network performance analysis report containing performance current situation description, problem attribution and an adjustment scheme, thereby effectively improving the operation efficiency and reliability of the optical fiber network.

To store network performance data for later retrieval, performance data files corresponding to a test cycle are retrieved, reformatted into unified data files according to a predetermined unified file format and a set of predefined unified category identifiers, and stored in a query database. The reformatting can match predefined unified category identifiers with data category identifiers in the performance data files, and the corresponding data values ​​can be stored sequentially in the unified data files or used to increment counter values ​​in similarly stored aggregated counter files. In addition, configuration data files for network cells can be stored less frequently than the frequency of the test cycles. Later retrieval can retrieve both the unified data files and the configuration data files corresponding to a selected time frame and network portion, and merge or aggregate the data appropriately for performance indicator calculations.

The invention provides a 5G network system and method for industrial control requirements. The system comprises a first 5G terminal, a second 5G terminal, a timestamp generator, a PLC master station, a PLC slave station and a network data analysis computer. Two 5G terminals configured to transmit and receive industrial control data messages in a 5G network; the timestamp generator is respectively connected with the two 5G terminals, the PLC master station, the PLC slave station and the network data analysis computer through a plurality of Ethernet ports, and is configured to load timestamps and mirror data in an industrial control data message transmission process; the PLC master station and the PLC slave station are configured to generate and receive control instructions and state data; and the network data analysis computer is configured to collect mirror image data and execute time delay calculation, data storage, multi-dimensional performance analysis and industrial control system influence evaluation. According to the system, high-precision 5G network performance analysis oriented to industrial control is realized.

The present disclosure provides a network performance analysis method, device, equipment and medium, wherein the network performance analysis method comprises: obtaining a plurality of to-be-processed minimization of drive test (MDT) data of a target terminal; performing processing on the plurality of to-be-processed MDT data in at least one dimension to obtain at least one target MDT data, wherein the dimension comprises any one of the following: a time advance (TA) dimension, an angle of arrival (AOA) dimension, a power headroom report (PHR) dimension, a height information dimension of the target terminal, and a latitude and longitude dimension of the target terminal; and analyzing a network performance index based on the at least one target MDT data, thereby solving the technical problem that the collected MDT data in the prior art is not accurate enough, thereby affecting the network performance analysis effect.

The invention relates to the technical field of network infrastructure, and discloses a network infrastructure element automatic detection and identification method, which comprises the following steps: acquiring network delay and network broadband at the current moment, determining reference network delay and reference network broadband, and determining a facility element detection and identification model; predicting a future moment of the network infrastructure based on the facility element detection and identification model to obtain an initial detection and identification result; collecting feature parameter values corresponding to a plurality of historical moments to obtain a feature parameter value group, and determining a parameter fluctuation confidence coefficient; analyzing the parameter fluctuation confidence coefficient set to obtain a single-parameter fluctuation coefficient; and adjusting the initial detection and identification result based on the multi-parameter fluctuation coefficient to obtain a target detection and identification result of the network infrastructure, fusing the multi-parameter fluctuation characteristics, ensuring the detection and identification precision and comprehensiveness of the network infrastructure, and further improving the accuracy and adaptability of network performance analysis. And the operation reliability and safety of the network infrastructure are ensured.

Apparatuses, methods, and systems are disclosed for domain name system determination. One method includes transmitting, from a first network function, first instructions to a second network function. The first instructions indicate forwarding DNS requests received from an application in a first device to the first network function. The method includes receiving, from the second network function, a first DNS request received from an application in the first device based on the first instructions. The DNS request includes a FQDN. The method includes determining to use network analytics from a third network function to determine an application server for the FQDN. The method includes transmitting a first request to the third network function. The first request includes: a request for data network performance analytics; the FQDN; a device identity of the first device; and / or a current location of the first device.

A wireless communication method of a policy control function (PCF) entity is provided. The method may include receiving, over a communication interface, an application group data transmission (AGDT) policy control creation message triggered by an application function (AF) entity associated with an application service provider (ASP), the AGDT policy control creation message indicating a set of operating conditions of the AGDT for a set of user equipments (UEs), the set of operating conditions including a set of quality of service (QoS) requirements. The method may include obtaining, by at least one processor, a set of AGDT policies associated with the ASP from a unified data repository (UDR) entity. The method may include obtaining, by the at least one processor, a set of network performance analytics from a Network Data Function Analysis (NWDAF) entity based on a set of operating conditions indicated in an AGDT policy control creation message from the ASP.

The invention discloses a method for analyzing cellular network performance under strong electromagnetic pulse attack, and relates to the technical field of wireless communication network performance analysis. The network performance analysis method utilizes a stochastic geometry theory to analyze cellular network coverage probability and regional spectrum efficiency under strong electromagnetic pulse attack. Considering the condition that the strong electromagnetic pulse attack range is limited and part of base stations in the attack area are randomly damaged; constructing a spatial distribution model of cellular network surviving base stations under strong electromagnetic pulse attack based on a stochastic geometry theory; defining an influence area and an influence radius of the strong electromagnetic pulse attack; deriving an estimation formula of the network coverage probability and the regional spectrum efficiency, and calculating the coverage probability and the regional spectrum efficiency of the cellular network in the strong electromagnetic pulse influence region under different base station damage probabilities; the specific influence of the initial distribution density of the base station and the strong electromagnetic pulse attack radius on the influence radius and the specific influence of the damage probability of the base station on the network coverage performance and the regional spectrum efficiency can be determined.