Data processing method and device, equipment and storage medium

Abstract

The invention provides a data processing method and device, equipment and a storage medium. The method comprises the steps that data information of all ports of network equipment is acquired; according to the data information of all the ports, a first port set matched with the first monitoring parameter is determined, and the first port set comprises one or more ports in all the ports of the network equipment; according to a preset monitoring mode corresponding to the first monitoring parameter, obtaining a plurality of first data volumes of the to-be-monitored data corresponding to the first monitoring parameter corresponding to all ports in the first port set, so as to obtain a first monitoring data volume queue corresponding to the first monitoring parameter; and according to the first monitoring data volume queue, determining a first monitoring result of the to-be-monitored data corresponding to the first monitoring parameter, so that flexible monitoring of the port data based on different monitoring parameters can be realized.

Description

[0001] This application claims priority to Chinese Patent Application No. 202410603394.3, filed on May 15, 2024, entitled “Data Traffic Acquisition Method”, the entire contents of which are incorporated herein by reference. Technical Field

[0002] This application relates to the field of communication network technology, specifically to a data processing method, apparatus, device, and storage medium. Background Technology

[0003] With the development of communication technology, the monitoring and management of data in networks has become increasingly important. Network data monitoring refers to the capture, analysis, and statistics of data in the network to understand its operational status, traffic patterns, and security situation.

[0004] In related technologies, data monitoring of network devices is usually based on the monitoring of a single data stream. For example, sampling techniques are used to target a specific data stream. Fixed-interval sampling or adaptive sampling methods are employed to selectively sample the corresponding data packets based on the size and changes of the stream, and the monitoring of the data stream is completed based on the sampling results.

[0005] However, existing technologies lack flexibility and cannot effectively monitor the performance of complex network devices. Summary of the Invention

[0006] This application provides a data processing method, apparatus, device, and storage medium, thereby solving the problem that existing monitoring methods are inflexible and unable to monitor the performance of complex network devices.

[0007] Firstly, this application provides a data processing method, including:

[0008] Obtain data information for all ports of the network device;

[0009] Based on the data information of all ports, a first set of ports matching the first monitoring parameter is determined, wherein the first set of ports includes one or more ports from all ports of the network device;

[0010] According to the preset monitoring method corresponding to the first monitoring parameter, obtain multiple first data quantities of all ports in the first port set corresponding to the data to be monitored corresponding to the first monitoring parameter, so as to obtain the first monitoring data quantity queue corresponding to the first monitoring parameter.

[0011] Based on the first monitoring data queue, determine the first monitoring result of the data to be monitored corresponding to the first monitoring parameter.

[0012] The data processing method provided in this application can process data from multi-port network devices. For all ports of the network device, it automatically and flexibly matches one or more ports corresponding to the data to be monitored based on the configured first monitoring parameter and the data information of all ports. By processing the data of the matched one or more ports, the monitoring of the data to be monitored is achieved. Since the first monitoring parameter can be flexibly configured, data processing based on the first monitoring parameter can not only monitor a single data stream, but also monitor a single port, multiple ports, or all ports of the network device. This enables flexible monitoring at different levels for a single data stream, multiple data streams, or all data streams of the network device, improving monitoring flexibility and enhancing the performance of complex network devices.

[0013] Optionally, before determining the first set of ports matching the first monitoring parameter, the method further includes:

[0014] Obtain the parameters to be monitored, which include the first monitoring parameter; wherein, the parameters to be monitored include one or more of device-level monitoring parameters, service type-level monitoring parameters, and data flow-level monitoring parameters;

[0015] The first monitoring parameter is a device-level monitoring parameter, a service type-level monitoring parameter, or a data stream-level monitoring parameter.

[0016] This application enables data monitoring of network devices at the device level, service type level, and data flow level. Specifically, the device-level monitoring parameters correspond to all ports of the network device, the service type-level monitoring parameters correspond to multiple ports of the network device, and the data flow-level monitoring parameters correspond to a specific data flow of the network device. This can meet the monitoring needs of different levels, provide monitoring results at different levels, and enable comprehensive analysis of network devices based on the monitoring results at different levels, thereby improving the performance of network devices.

[0017] Optionally, the device-level monitoring parameters include monitoring parameters determined based on the total ingress bandwidth and / or monitoring parameters determined based on the total egress bandwidth; the service type-level monitoring parameters include service type-level monitoring parameters determined based on multicast and / or service type-level monitoring parameters determined based on unicast; the data flow-level monitoring parameters include one or more of the following: data flow-level monitoring parameters determined based on the destination egress port, data flow-level monitoring parameters determined based on port hierarchical quality of service, data flow-level monitoring parameters determined based on quality of service queues, data flow-level monitoring parameters determined based on priority, data flow-level monitoring parameters determined based on fourth-generation network protocols, and data flow-level monitoring parameters determined based on sixth-generation network protocols.

[0018] Optionally, determining the first set of ports matching the first monitoring parameter based on the data information of all ports includes:

[0019] If the first monitoring parameter is a device-level monitoring parameter, then all ports of the network device are determined as a first port set matching the first monitoring parameter; if the first monitoring parameter is a service type-level monitoring parameter, then a first port set matching the first monitoring parameter is determined based on the data information of all ports, wherein the data of each port in the first port set includes the data of the service type corresponding to the first monitoring parameter; if the first monitoring parameter is a data flow-level monitoring parameter, then a first port set matching the first monitoring parameter is determined based on the data information of all ports, wherein the data of each port in the first port set includes the data flow corresponding to the first monitoring parameter.

[0020] Here, based on different levels of monitoring parameters, this application provides different types of port configuration methods. For device-level monitoring parameters, the corresponding first port set is determined to be all ports in the network device. For service type-level monitoring parameters, the corresponding first port set is determined to be all ports through which the data of the corresponding service type passes. For data flow-level monitoring parameters, the port is determined according to the data flow. Through the above methods, the ports to be monitored corresponding to each level of monitoring parameters can be accurately determined, and the data to be monitored can be accurately collected through the ports to be monitored, thereby improving the accuracy of data processing and data monitoring of network devices.

[0021] Optionally, obtaining the parameter to be monitored includes:

[0022] The parameter configuration interface is displayed in response to the user's first action;

[0023] In response to a second operation by the user on the parameter configuration interface, a parameter configuration instruction is obtained, wherein the parameter configuration instruction includes the parameter to be monitored.

[0024] This application provides users with a flexible configuration method. Users can configure the parameters to be monitored at different levels on the parameter configuration interface according to their own needs. Based on the user-configured parameters, multi-level monitoring of network devices can be achieved, which improves the performance of network devices and enhances the user experience.

[0025] Optionally, the method further includes:

[0026] Based on the data information of all ports, a second port set matching the second monitoring parameter is determined, the second port set including one or more ports from all ports; according to the preset monitoring method corresponding to the second monitoring parameter, multiple second data volumes of the data to be monitored corresponding to the second monitoring parameter for all ports in the second port set are obtained to obtain the second monitoring data volume queue corresponding to the second monitoring parameter; based on the second monitoring data volume queue, the second monitoring result of the data to be monitored corresponding to the second monitoring parameter is determined.

[0027] Here, while performing data monitoring based on the first monitoring parameter, this application can also perform data monitoring at the same or different levels as the first monitoring parameter based on the configured second monitoring parameter, realizing multi-level data monitoring, further improving the flexibility and efficiency of data monitoring, meeting a variety of processing needs, and improving the performance of network devices.

[0028] Optionally, the parameter to be monitored may further include the second monitoring parameter;

[0029] The second monitoring parameter is a device-level monitoring parameter, a service type-level monitoring parameter, or a data stream-level monitoring parameter.

[0030] Optionally, the preset monitoring method corresponding to the first monitoring parameter may include a preset sampling time period, a preset sampling frequency, a preset sampling period, or a preset sampling duration.

[0031] Here, when collecting data from the port, this application can sample and process data based on a preset sampling time period, a preset sampling frequency, a preset sampling period, or a preset sampling duration, thereby achieving uniformity in the amount of collected data and facilitating efficient and accurate data processing.

[0032] Optionally, the first monitoring data queue is stored in the storage unit of the network device, wherein the storage unit is the static random access memory of a field-programmable gate array chip.

[0033] In this application, the data is stored in static random-access memory (SRAM). SRAM has the characteristics of high-speed access, low latency, low power consumption and simple and reliable performance. It can save the data stored inside without the need for refresh circuit. Without relying on the computer's processing power, it can realize the real-time processing of a large amount of network traffic, improve the data read and write speed in the network and improve the system's processing efficiency.

[0034] Optionally, determining the first monitoring result of the data to be monitored corresponding to the first monitoring parameter based on the first monitoring data queue includes:

[0035] Extract the first monitoring data queue corresponding to the first monitoring parameter in each preset sampling time period from the storage unit; calculate the total data volume corresponding to the first monitoring parameter in each preset sampling time period based on the first monitoring data queue corresponding to the first monitoring parameter in each preset sampling time period; determine the monitoring result of the data to be monitored corresponding to the first monitoring parameter based on the total data volume corresponding to the first monitoring parameter in each preset sampling time period.

[0036] Here, this application supports the calculation of data from multiple ports. Data statistics can be achieved based on the data volume queues corresponding to each port, which is simple to calculate and improves the efficiency of data processing.

[0037] Optionally, determining the monitoring result of the data to be monitored corresponding to the first monitoring parameter based on the total data volume corresponding to the first monitoring parameter in each preset sampling time period includes:

[0038] If the first monitoring parameter is a device-level monitoring parameter, then based on the total data volume corresponding to the first monitoring parameter in each preset sampling time period, a first monitoring result of the network device corresponding to the data to be monitored corresponding to the first monitoring parameter is determined; if the first monitoring parameter is a service type-level monitoring parameter, then based on the total data volume corresponding to the first monitoring parameter in each preset sampling time period, a second monitoring result of the data to be monitored corresponding to the service type of the first monitoring parameter is determined; if the first monitoring parameter is a data stream-level monitoring parameter, then based on the total data volume corresponding to the first monitoring parameter in each preset sampling time period, a third monitoring result of the data stream to be monitored corresponding to the first monitoring parameter is determined.

[0039] This application enables data statistics for different monitoring levels based on all ports corresponding to each monitoring level, thereby providing accurate monitoring results for different levels of data monitoring and ensuring the performance of network devices.

[0040] Secondly, this application provides a data processing apparatus, comprising:

[0041] The first acquisition module is used to acquire data information from all ports of the network device;

[0042] The first determining module is used to determine a first set of ports that matches the first monitoring parameter based on the data information of all ports. The first set of ports includes one or more ports from all ports of the network device.

[0043] The first acquisition module is used to acquire multiple first data volumes of the data to be monitored corresponding to the first monitoring parameter in the first port set according to the preset monitoring method corresponding to the first monitoring parameter, so as to obtain the first monitoring data volume queue corresponding to the first monitoring parameter.

[0044] The first processing module is used to determine the first monitoring result of the data to be monitored corresponding to the first monitoring parameter based on the first monitoring data volume queue.

[0045] Optionally, before the first determining module determines the first set of ports matching the first monitoring parameter, the above-mentioned device further includes:

[0046] The second acquisition module is used to acquire the parameters to be monitored, the parameters to be monitored including the first monitoring parameter; wherein, the parameters to be monitored include one or more of device-level monitoring parameters, service type-level monitoring parameters, and data stream-level monitoring parameters; the first monitoring parameter is a device-level monitoring parameter, or a service type-level monitoring parameter, or a data stream-level monitoring parameter.

[0047] Optionally, the device-level monitoring parameters include monitoring parameters determined based on the total ingress bandwidth and / or monitoring parameters determined based on the total egress bandwidth; the service type-level monitoring...

[0048] The parameters include service type-level monitoring parameters determined based on multicast and / or service type-level monitoring parameters determined based on unicast; the data flow-level monitoring parameters include one or more of the following: data flow-level monitoring parameters determined based on the destination output port, data flow-level monitoring parameters determined based on port hierarchical quality of service, data flow-level monitoring parameters determined based on quality of service queues, data flow-level monitoring parameters determined based on priority, data flow-level monitoring parameters determined based on fourth-generation network protocols, and data flow-level monitoring parameters determined based on sixth-generation network protocols.

[0049] Optionally, the first determining module is specifically used for:

[0050] If the first monitoring parameter is a device-level monitoring parameter, then all ports of the network device are determined as a first port set matching the first monitoring parameter; if the first monitoring parameter is a service type-level monitoring parameter, then a first port set matching the first monitoring parameter is determined based on the data information of all ports, wherein the data of each port in the first port set includes the data of the service type corresponding to the first monitoring parameter; if the first monitoring parameter is a data flow-level monitoring parameter, then a first port set matching the first monitoring parameter is determined based on the data information of all ports, wherein the data of each port in the first port set includes the data flow corresponding to the first monitoring parameter.

[0051] Optionally, the second acquisition module is specifically used for:

[0052] The parameter configuration interface is displayed in response to the user's first action;

[0053] In response to a second operation by the user on the parameter configuration interface, a parameter configuration instruction is obtained, wherein the parameter configuration instruction includes the parameter to be monitored.

[0054] Optionally, the above-mentioned device further includes:

[0055] The second determining module is used to determine a second set of ports that matches the second monitoring parameter based on the data information of all ports. The second set of ports includes one or more ports from all ports.

[0056] The second acquisition module is used to acquire multiple second data volumes of all ports in the second port set corresponding to the data to be monitored corresponding to the second monitoring parameter in accordance with the preset monitoring method corresponding to the second monitoring parameter, so as to obtain the second monitoring data volume queue corresponding to the second monitoring parameter.

[0057] The second processing module is used to determine the second monitoring result of the data to be monitored corresponding to the second monitoring parameter based on the second monitoring data volume queue.

[0058] Optionally, the parameter to be monitored may further include the second monitoring parameter; the second monitoring parameter may be a device-level monitoring parameter, a service type-level monitoring parameter, or a data stream-level monitoring parameter.

[0059] Optionally, the preset monitoring method corresponding to the first monitoring parameter may include a preset sampling time period, a preset sampling frequency, a preset sampling period, or a preset sampling duration.

[0060] Optionally, the first monitoring data queue is stored in the storage unit of the network device, wherein the storage unit is the static random access memory of a field-programmable gate array chip.

[0061] Optionally, the first processing module is specifically used for:

[0062] Extract the first monitoring data queue corresponding to the first monitoring parameter in each preset sampling time period from the storage unit; calculate the total data volume corresponding to the first monitoring parameter in each preset sampling time period based on the first monitoring data queue corresponding to the first monitoring parameter in each preset sampling time period; determine the monitoring result of the data to be monitored corresponding to the first monitoring parameter based on the total data volume corresponding to the first monitoring parameter in each preset sampling time period.

[0063] Optionally, the first processing module is further specifically used for:

[0064] If the first monitoring parameter is a device-level monitoring parameter, then based on the total data volume corresponding to the first monitoring parameter in each preset sampling time period, a first monitoring result of the network device corresponding to the data to be monitored corresponding to the first monitoring parameter is determined; if the first monitoring parameter is a service type-level monitoring parameter, then based on the total data volume corresponding to the first monitoring parameter in each preset sampling time period, a second monitoring result of the data to be monitored corresponding to the service type of the first monitoring parameter is determined; if the first monitoring parameter is a data stream-level monitoring parameter, then based on the total data volume corresponding to the first monitoring parameter in each preset sampling time period, a third monitoring result of the data stream to be monitored corresponding to the first monitoring parameter is determined.

[0065] Thirdly, this application provides a data processing device, comprising: at least one processor and a memory;

[0066] The memory stores computer-executed instructions;

[0067] The at least one processor executes computer execution instructions stored in the memory, causing the at least one processor to perform the data processing method as described in the first aspect and various possible designs of the first aspect.

[0068] Fourthly, the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the data processing method described in the first aspect and various possible designs of the first aspect.

[0069] Fifthly, the present invention provides a computer program product, including a computer program that, when executed by a processor, implements the data processing method described in the first aspect and various possible designs of the first aspect.

[0070] The data processing method, apparatus, device, and storage medium provided in this application, wherein the method automatically and flexibly matches one or more ports corresponding to the data to be monitored based on the configured first monitoring parameters and the data information of all ports for all ports of a network device. By processing the data of the matched one or more ports, the monitoring of the data to be monitored is realized. Since the first monitoring parameters can be flexibly configured, data processing based on the first monitoring parameters can not only monitor a single data stream, but also monitor a single port, multiple ports, or all ports of the network device. This enables flexible monitoring of different levels of a single data stream, multiple data streams, or all data streams of the network device, improving monitoring flexibility and enhancing the performance of complex network devices. Attached Figure Description

[0071] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0072] Figure 1 This is a schematic diagram of the structure of a data processing system provided in an embodiment of this application;

[0073] Figure 2 A flowchart illustrating a method for acquiring data traffic provided in an embodiment of this application;

[0074] Figure 3 A flowchart illustrating the flow matching and parsing method of a data traffic acquisition method provided in this application embodiment;

[0075] Figure 4 A schematic flowchart illustrating the data traffic acquisition and data storage method provided in this application embodiment;

[0076] Figure 5 A schematic flowchart illustrating the data collection and data storage method for another data traffic acquisition method provided in this application embodiment;

[0077] Figure 6 A flowchart illustrating another data traffic acquisition method provided in this application embodiment;

[0078] Figure 7 This application provides a schematic diagram of the internal structure of a data traffic acquisition module according to an embodiment of the present application.

[0079] Figure 8 A flowchart illustrating a data processing method provided in an embodiment of this application;

[0080] Figure 9 A flowchart illustrating another data processing method provided in an embodiment of this application;

[0081] Figure 10 A schematic diagram of a first monitoring parameter configuration interface provided in an embodiment of this application;

[0082] Figure 11 A schematic diagram of a second monitoring parameter configuration interface provided in an embodiment of this application;

[0083] Figure 12 This is a schematic diagram of the structure of a data processing device provided in an embodiment of this application;

[0084] Figure 13 A block diagram of a data traffic acquisition device provided in an embodiment of this application.

[0085] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0086] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application.

[0087] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of the relevant data must comply with relevant laws, regulations and standards, and corresponding operation entry points are provided for users to choose to authorize or refuse.

[0088] Related technologies for data statistics on network devices include sampling techniques, distributed system design, and hardware acceleration design. However, these solutions can only monitor a single data stream. In complex switching networks, traffic balancing and forwarding methods are diverse, including flow-based forwarding and packet or block-based forwarding. In packet-based or block-based forwarding, a single flow often passes through multiple links. Therefore, monitoring the bandwidth and traffic statistics of a specific flow on an intermediate forwarding device link directly affects the performance of the network device. The aforementioned solutions lack monitoring flexibility and cannot meet the performance requirements for flexible monitoring of network devices in complex switching networks.

[0089] To address the aforementioned issues, embodiments of this application provide a data processing method, apparatus, device, and medium. This method automatically matches one or more ports corresponding to the data to be monitored based on configured first monitoring parameters and data information from all ports of a network device. By processing the data from the matched one or more ports, diversified monitoring of the data to be monitored can be achieved.

[0090] Optionally, Figure 1 This is a schematic diagram of the structure of a data processing system provided in an embodiment of this application, such as... Figure 1 As shown, the device includes a data processing device 101 and a network device 102.

[0091] The data processing device 101 and the network device 102 can be connected for communication.

[0092] Optionally, network device 102 includes n ports. n is a positive integer greater than 1, and the number of n is determined according to the port settings in network device 102, which can be determined based on actual conditions. Data processing device 101 can acquire and collect data, data streams, and / or configuration information from any port.

[0093] Optionally, the data processing device 101 uses an FPGA as its core processing unit. The FPGA has high-speed processing and parallel computing capabilities, enabling it to process large amounts of network traffic in real time, meeting users' demands for high real-time performance. Simultaneously, it can accurately calculate the data usage of each port within a specified time period, improving the accuracy of data statistics.

[0094] Optionally, the data in the embodiments of this application can be traffic data, such as traffic bandwidth usage.

[0095] Optionally, adopt Figure 1 The FPGA-based data processing device 101 supports multi-port traffic bandwidth calculation, effectively improving or resolving performance bottlenecks in traffic processing under high bandwidth conditions. It can monitor the traffic bandwidth usage of each port in real time, performing bandwidth monitoring and statistical calculations for network device 102 to help users better manage and utilize network resources. It also supports flexible configuration of monitoring and statistical flow types, allowing monitoring and statistical calculations for high-bandwidth services or data flows based on user needs. It monitors the bandwidth usage of matching flows in real time, enabling users to conduct monitoring from different dimensions and levels (device level, service level, data flow level), promptly detect network traffic anomalies, and take appropriate measures.

[0096] The data traffic acquisition methods provided in the exemplary embodiments of this application can be applied to transmission nodes in a switching network to obtain the number of transmission nodes' traffic. This can be applied, for example, in areas such as network traffic monitoring, network security management, and communication system optimization.

[0097] The data acquisition methods provided by the exemplary embodiments of this application enable real-time monitoring of the traffic bandwidth usage of each port of a transmission node in a switching network, helping users to better manage and utilize network resources. Secondly, this application can monitor the bandwidth usage of matched flows in real time, promptly detecting network traffic anomalies, which has significant application value in the field of network security management. Finally, this application supports multi-port traffic bandwidth calculation, effectively improving or resolving performance bottlenecks in traffic processing under multi-port, high-bandwidth conditions.

[0098] The exemplary embodiments of this application propose an FPGA-based traffic monitoring method and system that supports multi-port traffic bandwidth calculation, effectively improves or solves the performance bottleneck problem of traffic processing under multi-port high bandwidth, and can monitor the traffic bandwidth usage of each port in real time, thereby helping users to better manage and utilize network resources; it supports flexible configuration of monitoring and statistical flow types, and can monitor the bandwidth usage of matching flows in real time, so that users can promptly detect abnormal network traffic and take corresponding measures.

[0099] Here, the monitoring and statistical stream types correspond to different levels of the parameters to be monitored.

[0100] Optionally, based on the monitoring and calculation of data volume, statistics on traffic bandwidth usage can be achieved.

[0101] Optionally, Figure 2 A flowchart illustrating a method for acquiring data traffic provided in an embodiment of this application is shown below. Figure 2 As shown, the data traffic acquisition method may include the following steps: matching and parsing, traffic collection, storage of collected data, calculation of traffic information, and providing alarm prompts to users. Each step is described in detail below.

[0102] Matching and parsing: First, users can configure the traffic types to be monitored based on network transmission needs. The system (e.g., FPGA) will monitor traffic matching the user-configured traffic types to meet specific traffic monitoring requirements. Configuring matching traffic types includes data streams with total ingress bandwidth, data streams with total egress bandwidth, data streams based on destination egress ports, data streams based on port HQoS / QoS queues, data streams based on port priority, multicast / unicast data streams, IPv4 / IPv6 data streams, etc. Then, based on the user configuration, the matching flow types are parsed out. Utilizing the FPGA's parallel processing capabilities and high-speed data transmission capabilities, real-time processing of large amounts of network traffic is achieved.

[0103] The traffic types to be monitored correspond to different levels of monitoring parameters. Users can configure the traffic types to be monitored based on the configuration of the monitoring parameters.

[0104] Optionally, user-configured parameters to be monitored can be received through the parameter configuration interface.

[0105] Optionally, the parameters to be monitored include one or more of the following: device-level monitoring parameters, service type-level monitoring parameters, and data flow-level monitoring parameters.

[0106] Traffic Acquisition: Traffic is collected in parallel on each port for matched flows, and the amount of data within a time period Δt is calculated. The length of the Δt time period can be flexibly configured, in units such as µs / ms / s. Parallel processing of traffic acquisition across ports allows for rapid network traffic statistics and maximizes the bandwidth available for acquisition.

[0107] Wherein, △t is a preset sampling time period, which can be determined according to the actual situation, and the embodiments of this application do not impose specific restrictions.

[0108] Optionally, the matched flow can correspond to multiple ports or a single port, and port matching can be achieved based on different traffic types to be monitored.

[0109] Data storage: Store the amount of data collected for each port within a time period of Δt.

[0110] In some embodiments, data volume statistics and storage can be performed on each port within multiple Δt time periods. The number of multiple Δt time periods can be configured by the user (e.g., 1K (1000), 2K (2000), 8K (8000), etc., depending on the hardware resources. This application embodiment does not make any special limitation on this).

[0111] In some embodiments, data volume statistics can be stored on the SRAM corresponding to the port on the FPGA, which can greatly improve the data read and write speed, thereby improving the system's processing efficiency. At the same time, since SRAM memory is relatively inexpensive, integrating it onto the business FPGA chip can effectively reduce the cost of network traffic monitoring equipment.

[0112] Traffic information calculation: The system supports multi-port traffic bandwidth calculation, calculating the traffic information of the matched flow within a time interval Δt based on the data stored in SRAM on each port. For example, bandwidth (converted to Gbit / s).

[0113] In one embodiment, the bandwidth information may include at least one of the maximum bandwidth, average bandwidth, and minimum bandwidth.

[0114] By leveraging the parallel statistics, parallel storage, and rapid computation capabilities of FPGAs, real-time processing of massive amounts of network traffic can be achieved without relying on the processing power of a computer's CPU.

[0115] Provide alarm information to users: The system can monitor the bandwidth usage of the matched flow in real time and display the monitored bandwidth value and the statistical values ​​of each Δt for users to perform traffic analysis.

[0116] In one embodiment, a traffic expectation value can be set. Based on the system configuration, such as real-time monitoring of the traffic value of the matching flow deviating from the expected threshold, an alarm can be triggered to the user, enabling the user to promptly detect abnormal network traffic and take appropriate measures.

[0117] like Figure 2 As shown, firstly, the user configures the types of traffic to be monitored through the system interface, such as data streams based on total ingress bandwidth, data streams based on total egress bandwidth, data streams based on destination egress port, data streams based on port HQoS / QoS queues, data streams based on port priority, multicast / unicast data streams, IPv4 / IPv6 data streams, etc. After receiving the user's configuration, the system selects the traffic matching the expected traffic for monitoring based on the configuration. For example, if the user configures total ingress bandwidth, the system will select all traffic entering the network device for monitoring.

[0118] Combination Figure 2 See Figure 3 In one embodiment, when the port of the transmission node receives a data stream, it determines whether monitoring is enabled, that is, whether the function of monitoring traffic is started. If it is determined that the function of monitoring traffic is started, the matching type of the monitored flow type is obtained, and it is confirmed whether the received data stream matches the configured matching type. When it is determined that the flow type of the received data stream matches the configured matching type, traffic collection is performed to perform data traffic statistics.

[0119] Traffic is collected from the matched flows, and the amount of data within a time interval Δt is calculated. The time interval Δt can be flexibly configured by the user, for example, in µs / ms / s. Simultaneously, parallel processing is used on each port, enabling rapid network traffic statistics and maximizing the bandwidth for data collection. For example, with a system clock of 300MHz, a processing performance of 300MPPS can be achieved, and based on a 256B packet length, a single port can achieve a data collection bandwidth of 662.4Gbit / s.

[0120] Each port processes data in parallel, storing the data collected within each Δt time interval. Here, the data is stored in the FPGA's on-chip SRAM, and the storage capacity is user-configurable, such as 1K, 2K, 8K, etc., depending on hardware resources. Because each port stores data independently, data read and write speeds are significantly improved, thereby enhancing the system's processing efficiency.

[0121] The system receives sub-data streams corresponding to multiple ports, where each sub-data stream belongs to the same data stream. The system uses a field-programmable gate array (FPGA) to collect the data volume of the sub-data stream corresponding to each port within multiple preset time periods, resulting in multiple data volume queues corresponding to multiple ports. The system also uses the FPGA to calculate the flow information of the data stream within the preset time periods based on the multiple data volume queues.

[0122] like Figure 4 As shown, the system supports multi-port traffic bandwidth calculation. Based on the data stored in SRAM for each port, it calculates the bandwidth of the matched flow within the time period Δt, including the MAX value (maximum value), average value, and Min value (minimum value) for user reference.

[0123] In one embodiment, the number of ports P is 10, and the depth D (the number of traffic information items stored in each SRAM within a time interval Δt) under each port is 1K. A matched single data stream is hashed to the 10 ports for transmission, and the collected values ​​(collected traffic information) stored on each port within 1K Δt time intervals are S1 to S1K respectively; therefore, the 1K collected values ​​for this stream within 1K Δt time intervals are as follows:

[0124] {{P1_S1+P2_S1+…+P10_S1}, {P1_S2+P2_S2+…+P10_S2},…, {P1_S1k+P2_S1k+…+P10_S1k}}

[0125] Wherein, P1_S1 is the value collected by port P1 during the first Δt time interval, P2_S1 is the value collected by port P2 during the first Δt time interval, and P1_S2 is the value collected by port P1 during the second Δt time interval. P1_S1 + P2_S1 + ... + P10_S1 = S1, and so on.

[0126] In the above formula, {P1_S1+P2_S1+…+P10_S1} can be simplified to {S1, S2, …, S1k}. Then, the maximum bandwidth, minimum bandwidth, and average bandwidth of this flow calculated in units of Δt within a time interval of 1K*Δt are as follows:

[0127] Max({T1, T2, ..., T1k})

[0128] Min({T1, T2, ..., T1k})

[0129] Avg({T1, T2, ..., T1k})

[0130] Among them, Max(·) is the maximum value function, Min(·) is the minimum value function, and Avg(·) is the average value function.

[0131] In this way, real-time processing of large amounts of network traffic can be achieved without relying on the processing power of the computer's CPU.

[0132] like Figure 5 As shown, the system can monitor the bandwidth usage of matched flows in real time and display the monitored bandwidth values ​​and statistical values ​​of various Δt values ​​for users to perform traffic analysis. It can monitor and perform statistical calculations for high-bandwidth services or data flows according to user needs, providing a clear understanding of target traffic bandwidth and sudden spikes. Simultaneously, the system supports setting expected bandwidth values. For example, if the expected bandwidth deviation of matched flows is detected in real time, it can alert the user, enabling timely detection of network traffic anomalies and prompt implementation of appropriate measures. Furthermore, it can monitor and perform statistical calculations of network device bandwidth, allowing users to conduct monitoring from different dimensions and levels (device level, service level, data flow level).

[0133] Figure 6 This application provides a data traffic acquisition method, which specifically includes the following steps.

[0134] Step S500: Receive sub-data streams corresponding to multiple ports through multiple ports, wherein the sub-data streams belong to the same data stream.

[0135] Optionally, these multiple ports constitute a port set.

[0136] Step S520: The data volume of the sub-data stream corresponding to each port is collected by the field programmable gate array (FPGA) in multiple preset time periods to obtain multiple data volume queues corresponding to multiple ports.

[0137] Step S540: Calculate the data flow information within a preset time period using FPGA based on multiple data queues.

[0138] Optionally, the traffic information of the data stream during a preset time period can be calculated by using the obtained port set, where all ports correspond to multiple data volumes of the data stream.

[0139] Optionally, traffic information includes: whether the network device has reached the bandwidth target, or whether the network device has packet loss, or whether the data corresponding to multicast or unicast has reached the bandwidth target, or whether the data corresponding to multicast or unicast has packet loss, or whether a certain data stream has reached the bandwidth target, or whether a certain data stream has packet loss.

[0140] Figure 7 This is a schematic diagram of the structure of a data traffic acquisition device 600 provided in an embodiment of this application. The data traffic acquisition device 600 includes:

[0141] The receiving module 610 is configured to receive data packets, wherein the data packets are one of one or more data packets included in a logical frame, the logical frame also includes a logical frame end identifier, and the data packets include an equalization sequence number field.

[0142] The acquisition module 620 is configured to adjust the value in the balanced sequence number field of the data packet according to the logical frame end identifier.

[0143] The computing module 630 is configured to calculate the flow information of the data stream within a preset time period based on multiple data queues via an FPGA.

[0144] Optionally, Figure 8 This is a flowchart illustrating a data processing method provided in an embodiment of this application. The execution entity of this embodiment can be... Figure 1 The data processing system in the data processing system, or the data processing device 101 in the data processing system, can be determined according to the actual application scenario.

[0145] like Figure 8 As shown, the method includes the following steps:

[0146] S801: Obtain data information for all ports of the network device.

[0147] Optionally, the data information may be port attribute information, including port name, port type, port number, port number range, and at least one of the services supported by the port, and may also include port connection information.

[0148] Optionally, the data information can be the service type of the port's data.

[0149] Optionally, the data information can be configuration information for the data streams of the port, such as the five-tuple information for each data stream of the port, including one or more of the following: source Internet Protocol address, source port, destination IP address, destination port, and transport layer protocol.

[0150] S802: Based on the data information of all ports, determine the first set of ports that match the first monitoring parameter.

[0151] The first port set includes one or more ports from all ports of the network device.

[0152] Optionally, the first monitoring parameter can be a device-level monitoring parameter, a service type-level monitoring parameter, or a data stream-level monitoring parameter.

[0153] Optionally, the first monitoring parameter is matched with the data information, and the ports that match the first monitoring parameter are added to the first port set.

[0154] By determining the first set of ports, data monitoring of multiple ports can be achieved simultaneously, and the ports to be monitored can be flexibly configured according to the configuration of the first monitoring parameters.

[0155] Optionally, users can configure the data to be monitored according to their own needs by configuring the first monitoring parameter. The system will select the data that matches the expected data for monitoring based on the user's configuration, thereby meeting the user's personalized needs.

[0156] S803: According to the preset monitoring method corresponding to the first monitoring parameter, obtain multiple first data quantities of all ports in the first port set that correspond to the data to be monitored corresponding to the first monitoring parameter, so as to obtain the first monitoring data quantity queue corresponding to the first monitoring parameter.

[0157] S804: Based on the first monitoring data queue, determine the first monitoring result of the data to be monitored corresponding to the first monitoring parameter.

[0158] The data processing method provided in this application can process data from multi-port network devices. For all ports of the network device, it automatically and flexibly matches one or more ports corresponding to the data to be monitored based on the configured first monitoring parameter and the data information of all ports. By processing the data of the matched one or more ports, the monitoring of the data to be monitored is achieved. Since the first monitoring parameter can be flexibly configured, data processing based on the first monitoring parameter can not only monitor a single data stream, but also monitor a single port, multiple ports, or all ports of the network device. This enables flexible monitoring of different levels of single data streams, multiple data streams, or all data streams of the network device, improving monitoring flexibility and enhancing the performance of complex network devices.

[0159] Optionally, embodiments of this application can also simultaneously achieve multi-level data monitoring. Accordingly, the above method further includes: determining a second port set matching the second monitoring parameter based on the data information of all ports, wherein the second port set includes one or more ports among all ports; obtaining multiple second data volumes of the data to be monitored corresponding to the second monitoring parameter for all ports in the second port set according to a preset monitoring method corresponding to the second monitoring parameter, so as to obtain a second monitoring data volume queue corresponding to the second monitoring parameter; and determining a second monitoring result of the data to be monitored corresponding to the second monitoring parameter based on the second monitoring data volume queue.

[0160] Optionally, the parameters to be monitored may also include a second monitoring parameter; the second monitoring parameter may be a device-level monitoring parameter, a service type-level monitoring parameter, or a data stream-level monitoring parameter. The second monitoring parameter can be at the same level as the first monitoring parameter; for example, if the first monitoring parameter is a device-level monitoring parameter, such as the device's total ingress bandwidth, the second monitoring parameter may also be a device-level monitoring parameter, such as the device's total egress bandwidth. Alternatively, the second monitoring parameter may be at a different level from the first monitoring parameter; for example, if the first monitoring parameter is a device-level monitoring parameter, such as the device's total ingress bandwidth, the second monitoring parameter may be a service type-level monitoring parameter, such as a multicast data stream.

[0161] Optionally, the above method further includes: determining a third port set matching the third monitoring parameter based on the data information of all ports, wherein the third port set includes one or more ports among all ports; obtaining multiple third data volumes in the third port set corresponding to the data to be monitored by all ports corresponding to the third monitoring parameter according to the preset monitoring method corresponding to the third monitoring parameter, so as to obtain a third monitoring data volume queue corresponding to the third monitoring parameter; and determining the third monitoring result of the data to be monitored corresponding to the third monitoring parameter based on the third monitoring data volume queue.

[0162] Optionally, the parameters to be monitored may also include a third monitoring parameter; the third monitoring parameter may be a device-level monitoring parameter, a service type-level monitoring parameter, or a data flow-level monitoring parameter. The third monitoring parameter may be at the same level or a different level from the first monitoring parameter; the third monitoring parameter may also be at the same level or a different level from the second monitoring parameter.

[0163] In one possible implementation, the second monitoring parameter, the third monitoring parameter, and the first monitoring parameter are all at the same monitoring level, such as data stream-level monitoring parameters. In another possible implementation, the second monitoring parameter, the third monitoring parameter, and the first monitoring parameter each correspond to different monitoring levels. In this embodiment, while performing data monitoring based on the first monitoring parameter, it is also possible to perform data monitoring at the same or different levels as the first monitoring parameter based on the configured second monitoring parameter, thus realizing multi-level data monitoring. This further improves the flexibility and efficiency of data monitoring, meets diverse processing needs, and enhances the performance of network devices.

[0164] In some embodiments, the present application can realize multi-port data monitoring according to user needs, and accordingly, Figure 9 A flowchart illustrating another data processing method provided in this application embodiment is shown below. Figure 9 As shown, the method includes the following steps:

[0165] S901: Obtain the parameters to be monitored.

[0166] The parameters to be monitored include the first monitoring parameter.

[0167] The parameters to be monitored include one or more of the following: device-level monitoring parameters, service type-level monitoring parameters, and data flow-level monitoring parameters.

[0168] Optionally, the device-level monitoring parameters include monitoring parameters determined based on the total ingress bandwidth and / or monitoring parameters determined based on the total egress bandwidth. By matching the device-level monitoring parameters, embodiments of this application can monitor whether network devices have reached their bandwidth targets and can also be used to detect packet loss.

[0169] Optionally, the service type-level monitoring parameters include service type-level monitoring parameters determined based on multicast and / or service type-level monitoring parameters determined based on unicast. By matching the service type-level monitoring parameters, embodiments of this application can monitor whether the data corresponding to multicast or unicast reaches the bandwidth target, and can also be used to detect whether there is packet loss in the data corresponding to multicast or unicast.

[0170] Optionally, data flow-level monitoring parameters include one or more of the following: data flow-level monitoring parameters determined based on the destination outgoing port; data flow-level monitoring parameters determined based on port hierarchical quality of service (HQOS); data flow-level monitoring parameters determined based on quality of service (QoS) queues; data flow-level monitoring parameters determined based on priority; data flow-level monitoring parameters determined based on Internet Protocol version 4 (V4); and data flow-level monitoring parameters determined based on Internet Protocol version 6 (V6). Based on the destination outgoing port / port HQOS / QoS queue / priority / V4 / V6, it is possible to monitor specific data flows with high accuracy and flexibility, providing different monitoring methods for different monitoring needs.

[0171] Specifically, based on the above method, the embodiments of this application can simultaneously monitor device-level monitoring parameters, service type-level monitoring parameters, and data flow-level monitoring parameters, effectively solving the data processing performance problem under multi-port and high bandwidth conditions. It can achieve comprehensive monitoring of data from complex network devices, improve network performance, and help users better manage and utilize network resources.

[0172] Optionally, the parameters to be monitored may also include a second monitoring parameter, and further, a third monitoring parameter.

[0173] Optionally, the number of the first monitoring parameters can be one or more.

[0174] Optionally, obtaining the parameters to be monitored includes: obtaining the parameters to be monitored input by the user through a preset configuration interface; or receiving the parameters to be monitored sent by the user's terminal device.

[0175] Optionally, the parameters to be monitored are obtained, including:

[0176] In response to the user's first operation, the parameter configuration interface is displayed; in response to the user's second operation on the parameter configuration interface, the parameter configuration instruction is obtained, wherein the parameter configuration instruction includes the parameter to be monitored.

[0177] This application provides users with a flexible configuration method. Users can configure the parameters to be monitored at different levels on the parameter configuration interface according to their own needs. Based on the user-configured parameters, multi-level monitoring of network devices can be achieved, which improves the performance of network devices and enhances the user experience.

[0178] Optionally, obtaining the parameter to be monitored includes: displaying a first monitoring parameter configuration interface in response to a first user operation; and obtaining a first monitoring parameter configuration instruction in response to a second user operation on the first monitoring parameter configuration interface.

[0179] The first monitoring parameter configuration instruction includes different levels of parameters to be monitored.

[0180] In some embodiments, the first operation can be a single click, double click, long press, voice input, or other similar operation.

[0181] In some embodiments, the first operation can be a selection operation, which can be achieved by clicking or inputting information.

[0182] Exemplary, Figure 10 A schematic diagram of a first monitoring parameter configuration interface provided in an embodiment of this application is shown below. Figure 10 As shown, users can enter the first monitoring parameter configuration command through the input box on the first monitoring parameter configuration interface.

[0183] In this application embodiment, users are provided with a flexible configuration method. Users can configure multiple levels of monitoring parameters at one time on the first monitoring parameter configuration interface according to their own needs. Based on the monitoring parameters configured by the user, multi-level monitoring of network devices can be realized, which improves the performance of network devices and enhances the user experience.

[0184] Optionally, acquiring the parameters to be monitored includes: in response to a third user operation, displaying a second monitoring parameter configuration interface, wherein the second monitoring parameter configuration interface includes operation boxes corresponding to all monitoring parameters; and in response to a fourth user operation on at least one operation box, acquiring one or more second monitoring parameter configuration instructions.

[0185] Each second monitoring parameter configuration instruction includes a level of parameters to be monitored.

[0186] In some embodiments, the third operation can be a single click, double click, long press, voice input, or other similar operations.

[0187] In some embodiments, the fourth operation can be a selection operation, which can be achieved by clicking or inputting information.

[0188] Exemplary, Figure 11 A schematic diagram of a second monitoring parameter configuration interface provided in an embodiment of this application is shown below. Figure 11 As shown, users can configure the second monitoring parameter configuration instructions through the configuration box in the second monitoring parameter configuration interface.

[0189] Understandable, Figure 10 and Figure 10 For illustrative purposes only, the embodiments of this application do not impose specific limitations on the specific form of the interface.

[0190] In this embodiment, a second monitoring parameter configuration interface is provided to the user. This interface includes operation boxes corresponding to all monitoring parameters. Users can configure different levels of monitoring parameters by operating different operation boxes on the second monitoring parameter configuration interface to meet different types of monitoring needs, thereby improving the flexibility of data processing and enhancing the user experience.

[0191] S902: Obtain data information for all ports of the network device.

[0192] The execution order of steps S901 and S902 can be determined according to the actual situation. Step S901 can be executed first, or step S902 can be executed first, or they can be executed simultaneously.

[0193] S903: Based on the data information of all ports, determine the first set of ports that matches the first monitoring parameter.

[0194] The first port set includes one or more ports from all ports of the network device.

[0195] Optionally, users can configure the data to be monitored through the monitoring parameter configuration interface described above, such as total ingress bandwidth, total egress bandwidth, based on destination egress port / port HQOS / QOS queue / priority / , multicast / unicast, V4 / V6, etc. After receiving the user's configuration, the system selects the data matching the expected configuration for monitoring. For example, if the user configures the total ingress bandwidth, the system will select all data entering the network device for monitoring.

[0196] S904: According to the preset monitoring method corresponding to the first monitoring parameter, obtain multiple first data quantities of all ports in the first port set that correspond to the data to be monitored corresponding to the first monitoring parameter, so as to obtain the first monitoring data quantity queue corresponding to the first monitoring parameter.

[0197] S905: Based on the first monitoring data queue, determine the first monitoring result of the data to be monitored corresponding to the first monitoring parameter.

[0198] In this application embodiment, data monitoring of network devices can be achieved at the device level, service type level, and data flow level. Specifically, the device-level monitoring parameters correspond to all ports of the network device, the service type-level monitoring parameters correspond to multiple ports of the network device, and the data flow-level monitoring parameters correspond to a specific data flow of the network device. This can meet the monitoring needs of different levels, provide monitoring results of different levels, and enable comprehensive analysis of network devices based on the monitoring results of different levels, thereby improving the performance of network devices.

[0199] The following explains step S903:

[0200] Optionally, based on the data information from all ports, a first set of ports matching the first monitoring parameter is determined, including:

[0201] If the first monitoring parameter is a device-level monitoring parameter, then all ports of the network device are determined as the first port set that matches the first monitoring parameter.

[0202] If the first monitoring parameter is a service type-level monitoring parameter, then a first set of ports matching the first monitoring parameter is determined based on the data information of all ports. The data for each port in the first set includes data corresponding to the service type of the first monitoring parameter.

[0203] If the first monitoring parameter is a data flow-level monitoring parameter, then based on the data information of all ports, a first port set matching the first monitoring parameter is determined. The data of each port in the first port set includes the data flow corresponding to the first monitoring parameter. Since traffic balancing and forwarding methods are diverse, including flow-based forwarding and packet or block-based forwarding, a data flow may correspond to multiple ports. Therefore, the first port set corresponding to a data flow-level monitoring parameter may include one or more ports.

[0204] Here, based on different levels of monitoring parameters, this application embodiment provides different types of port configuration methods. For device-level monitoring parameters, the corresponding first port set is determined to be all ports in the network device. For service type-level monitoring parameters, the corresponding first port set is determined to be all ports through which the data of the corresponding service type passes. For data flow-level monitoring parameters, the port is determined according to the data flow. Through the above methods, the port to be monitored corresponding to each level of monitoring parameter can be accurately determined, and the data to be monitored can be accurately collected through the port to be monitored, thereby improving the accuracy of data processing and data monitoring of network devices.

[0205] The following explains steps S803, S804, S904, and S905:

[0206] Optionally, the preset monitoring method corresponding to the first monitoring parameter may include a preset sampling time period, a preset sampling frequency, a preset sampling period, or a preset sampling duration.

[0207] The preset sampling time period, preset sampling frequency, preset sampling period, or preset sampling duration can all be determined according to the actual situation, and this application embodiment does not impose specific restrictions.

[0208] Here, when collecting data from the port, this application can sample and process data based on a preset sampling time period, a preset sampling frequency, a preset sampling period, or a preset sampling duration, thereby achieving uniformity in the amount of collected data and facilitating efficient and accurate data processing.

[0209] In one possible implementation, the first set of ports is collected, and each port corresponds to multiple first data volumes of the data to be monitored for the first monitoring parameter. Specifically, this involves counting the data volume within a time interval Δt. Here, Δt is a preset sampling time interval, and its size can be flexibly configured by the user, for example, in units of us / ms / s. Simultaneously, each port employs parallel processing, enabling rapid statistical analysis of network traffic and maximizing the acquisition bandwidth. Specifically, taking a system clock of 300MHz as an example, a processing performance of 300MPPS can be achieved, and based on a 256B packet length, a single port can achieve a data acquisition bandwidth of 662.4Gbit / s.

[0210] Optionally, the first monitoring data queue is stored in the storage unit of the network device, which is the static random access memory of a field-programmable gate array chip.

[0211] In this application, the data is stored in SRAM, which has the characteristics of high-speed access, low latency, low power consumption and simple and reliable performance. It can save the data stored inside without the need for refresh circuit. Without relying on the computer's processing power, it can realize the real-time processing of a large amount of network traffic, improve the reading and writing speed of data in the network and improve the processing efficiency of the system.

[0212] Optionally, the data collected within each Δt time period can be stored. The storage quantity is user-configurable (e.g., 1K, 2K, 8K, etc., set according to hardware resources). The data is stored using on-chip SRAM on the FPGA, which can significantly improve data read and write speed, thereby increasing system processing efficiency. Furthermore, since SRAM memory is relatively inexpensive, integrating it onto the business FPGA chip can effectively reduce the cost of network traffic monitoring equipment.

[0213] In one possible implementation, the traffic of all ports is used as the data to be monitored, for example, see [link to relevant documentation]. Figure 4 As shown, for n ports, matching and parsing can be performed using the first monitoring parameter. If all ports are successfully matched and parsed, traffic collection is performed to obtain a data volume queue, and statistics are performed according to the preset sampling time period. Finally, n sets of Δt statistical values ​​can be obtained, that is, n data volume queues, where n is any positive integer.

[0214] Optionally, based on the first monitoring data queue, the first monitoring result of the data to be monitored corresponding to the first monitoring parameter is determined, including:

[0215] Extract the first monitoring data queue corresponding to the first monitoring parameter in each preset sampling time period from the storage unit; calculate the total data volume corresponding to the first monitoring parameter in each preset sampling time period based on the first monitoring data queue corresponding to the first monitoring parameter in each preset sampling time period; determine the monitoring result of the data to be monitored corresponding to the first monitoring parameter based on the total data volume corresponding to the first monitoring parameter in each preset sampling time period.

[0216] Here, this application supports the calculation of data from multiple ports. Data statistics can be achieved based on the data volume queues corresponding to each port, which is simple to calculate and improves the efficiency of data processing.

[0217] Optionally, based on the total data volume corresponding to the first monitoring parameter in each preset sampling time period, the monitoring result of the data to be monitored corresponding to the first monitoring parameter is determined, including:

[0218] If the first monitoring parameter is a device-level monitoring parameter, then the first monitoring result of the network device corresponding to the data to be monitored corresponding to the first monitoring parameter is determined based on the total amount of data corresponding to the first monitoring parameter in each preset sampling time period.

[0219] If the first monitoring parameter is a service type-level monitoring parameter, then based on the total data volume corresponding to the first monitoring parameter in each preset sampling time period, the second monitoring result of the data to be monitored for the service type corresponding to the first monitoring parameter is determined. This second monitoring result can analyze whether the data corresponding to the service type meets the preset load balancing logic / forwarding routing.

[0220] If the first monitoring parameter is a data stream-level monitoring parameter, then based on the total data volume corresponding to the first monitoring parameter in each preset sampling time period, the third monitoring result of the data stream to be monitored corresponding to the first monitoring parameter is determined. This third monitoring result can analyze whether the data stream meets the preset load balancing logic / forwarding routing.

[0221] In this embodiment, based on all ports corresponding to each monitoring level, data statistics for different monitoring levels can be realized, thereby providing accurate monitoring results for data monitoring at different levels and ensuring the performance of network devices.

[0222] In one possible implementation, embodiments of this application calculate traffic information in the data volume queue to determine the usage status of network devices.

[0223] Optionally, the traffic information includes at least one of maximum bandwidth, minimum bandwidth, and average bandwidth.

[0224] Optionally, the maximum value among the total data volume corresponding to multiple preset sampling time periods is determined as the maximum bandwidth; and / or, the minimum value among the total data volume corresponding to multiple preset sampling time periods is determined as the minimum bandwidth; and / or, the average value among the total data volume corresponding to multiple preset sampling time periods is determined as the average bandwidth.

[0225] The embodiments of this application can calculate the bandwidth data to be monitored, including at least one of the maximum bandwidth, minimum bandwidth and average bandwidth. The calculation method is simple and fast, and it realizes efficient and accurate statistics on the bandwidth of the data stream.

[0226] In one possible implementation, the specific method for calculating traffic information is as follows:

[0227] The system supports multi-port traffic bandwidth calculation. Based on the data stored in SRAM on each port, it calculates the bandwidth of the matched flow within a time interval Δt, converts it to Gbit / s, and provides MAX, average, and Min values ​​for user reference. Assuming the number of ports P is 10, the storage depth D under each port is 1K, and the matched single flow is hashed and transmitted across 10 ports, with each port storing collected values ​​S1 to S1K over 1K time intervals Δt; then, for this flow, the 1K statistical values ​​collected over 1K time intervals Δt are:

[0228] {{P1_S1+P2_S1+…+P10_S1}, {P1_S2+P2_S2+…+P10_S2},…, {P1_S1k+P2_S1k+…+P10_S1k}}

[0229] Simplifying the above statistics to {T1, T2, ..., T1k}, the maximum bandwidth, minimum bandwidth, and average bandwidth of this flow in 1K*Δt time intervals, calculated in units of Δt, are as follows:

[0230] Max({T1, T2, ..., T1k})

[0231] Min({T1, T2, ..., T1k})

[0232] Avg({T1, T2, ..., T1k})

[0233] In this way, real-time processing of large amounts of network traffic can be achieved without relying on computer processing power.

[0234] Optionally, it also includes: comparing the traffic information with a preset traffic information threshold range; if the traffic information is not within the preset traffic information threshold range, then outputting an alarm message.

[0235] It is understood that the preset traffic information threshold here can be determined according to the actual situation, and this application embodiment does not impose specific restrictions on it.

[0236] Optionally, alarm prompts can be output by sending information to the user's terminal device, or by displaying an interface, sound information, etc.

[0237] Optionally, the system can monitor the bandwidth usage of the first set of matched ports in real time, and display the monitored bandwidth values ​​and statistical values ​​of each Δt for users to perform traffic analysis. This allows for a direct understanding of target traffic bandwidth and sudden events. Simultaneously, the system can also support setting expected bandwidth values. For example, if the expected bandwidth offset of the matched flow is detected in real time, an alert can be issued to the user, enabling them to promptly detect abnormal network traffic and take appropriate measures.

[0238] Here, the embodiments of this application can monitor the usage of network device traffic information in real time, support preset traffic information thresholds, monitor in real time whether the matched data deviates from the preset traffic information thresholds, and alert the user, so that the user can promptly detect abnormal data traffic and take corresponding measures, further improving the user experience. Through timely alerts, the security and reliability of the network are improved.

[0239] Figure 12 This is a schematic diagram of the structure of a data processing device provided in an embodiment of this application, as shown below. Figure 12 As shown, the apparatus in this embodiment includes: a first acquisition module 1201, a first determination module 1202, a first acquisition module 1203, and a first processing module 1204. The data processing device here can be the aforementioned data processing equipment itself, or the processor or processing unit of the data processing equipment. It should be noted that the division of the first acquisition module 1201, the first determination module 1202, the first acquisition module 1203, and the first processing module 1204 is only a logical functional division; physically, they can be integrated or independent.

[0240] The first acquisition module 1201 is used to acquire data information of all ports of the network device;

[0241] The first determining module 1202 is used to determine a first port set that matches the first monitoring parameter based on the data information of all ports. The first port set includes one or more ports from all ports of the network device.

[0242] The first acquisition module 1203 is used to acquire multiple first data quantities of the data to be monitored corresponding to the first monitoring parameter in the first port set according to the preset monitoring method corresponding to the first monitoring parameter, so as to obtain the first monitoring data quantity queue corresponding to the first monitoring parameter.

[0243] The first processing module 1204 is used to determine the first monitoring result of the data to be monitored corresponding to the first monitoring parameter based on the first monitoring data volume queue.

[0244] Optionally, before the first determining module 1202 determines the first port set matching the first monitoring parameter, the above device further includes: a second acquiring module, used to acquire the parameter to be monitored, the parameter to be monitored including the first monitoring parameter; wherein, the parameter to be monitored includes one or more of device-level monitoring parameters, service type-level monitoring parameters, and data stream-level monitoring parameters; the first monitoring parameter is a device-level monitoring parameter, or a service type-level monitoring parameter, or a data stream-level monitoring parameter.

[0245] Optionally, device-level monitoring parameters include monitoring parameters determined based on total ingress bandwidth and / or total egress bandwidth; service type-level monitoring parameters include service type-level monitoring parameters determined based on multicast and / or unicast; data flow-level monitoring parameters include one or more of the following: data flow-level monitoring parameters determined based on destination egress port, data flow-level monitoring parameters determined based on port hierarchical quality of service, data flow-level monitoring parameters determined based on quality of service queues, data flow-level monitoring parameters determined based on priority, data flow-level monitoring parameters determined based on fourth-generation network protocols, and data flow-level monitoring parameters determined based on sixth-generation network protocols.

[0246] Optionally, the first determining module 1202 is specifically used for: if the first monitoring parameter is a device-level monitoring parameter, then determining all ports of the network device as a first port set matching the first monitoring parameter; if the first monitoring parameter is a service type-level monitoring parameter, then determining a first port set matching the first monitoring parameter based on the data information of all ports, wherein the data of each port in the first port set includes the data of the service type corresponding to the first monitoring parameter; if the first monitoring parameter is a data flow-level monitoring parameter, then determining a first port set matching the first monitoring parameter based on the data information of all ports, wherein the data of each port in the first port set includes the data flow corresponding to the first monitoring parameter.

[0247] Optionally, the second acquisition module is specifically used to: display the parameter configuration interface in response to the user's first operation;

[0248] In response to the user's second operation on the parameter configuration interface, a parameter configuration instruction is obtained, which includes the parameter to be monitored.

[0249] Optionally, the above device further includes: a second determining module, configured to determine a second port set matching the second monitoring parameter based on the data information of all ports, wherein the second port set includes one or more ports among all ports; a second acquisition module, configured to acquire multiple second data quantities of the data to be monitored corresponding to the second monitoring parameter for all ports in the second port set according to a preset monitoring method corresponding to the second monitoring parameter, so as to obtain a second monitoring data quantity queue corresponding to the second monitoring parameter; and a second processing module, configured to determine the second monitoring result of the data to be monitored corresponding to the second monitoring parameter based on the second monitoring data quantity queue.

[0250] Optionally, the preset monitoring method corresponding to the first monitoring parameter may include a preset sampling time period, a preset sampling frequency, a preset sampling period, or a preset sampling duration.

[0251] Optionally, the first monitoring data queue is stored in the storage unit of the network device, which is the static random access memory of a field-programmable gate array chip.

[0252] Optionally, the first processing module 1204 is specifically used to: extract the first monitoring data queue corresponding to the first monitoring parameter in each preset sampling time period from the storage unit; calculate the total data volume corresponding to the first monitoring parameter in each preset sampling time period based on the first monitoring data queue corresponding to the first monitoring parameter in each preset sampling time period; and determine the monitoring result of the data to be monitored corresponding to the first monitoring parameter based on the total data volume corresponding to the first monitoring parameter in each preset sampling time period.

[0253] Optionally, the first processing module 1204 is further configured to: if the first monitoring parameter is a device-level monitoring parameter, determine a first monitoring result of the network device corresponding to the data to be monitored corresponding to the first monitoring parameter based on the total data volume corresponding to the first monitoring parameter in each preset sampling time period; if the first monitoring parameter is a service type-level monitoring parameter, determine a second monitoring result of the data to be monitored corresponding to the service type of the first monitoring parameter based on the total data volume corresponding to the first monitoring parameter in each preset sampling time period; if the first monitoring parameter is a data stream-level monitoring parameter, determine a third monitoring result of the data stream to be monitored corresponding to the first monitoring parameter based on the total data volume corresponding to the first monitoring parameter in each preset sampling time period.

[0254] This application provides a data traffic acquisition device, including: a processor and a transceiver;

[0255] The processor is used to call computer programs and coordinate with the transceiver to implement the actions performed by the data traffic acquisition device in the above method embodiments.

[0256] For example, Figure 13 This is a block diagram of a data traffic acquisition device provided in an embodiment of this application. Figure 13 As shown, the data traffic acquisition device 700 includes a processor 701 and a memory 702. The steps in the above method embodiments are executed under the control of the processor 701.

[0257] Optionally, the data traffic acquisition device 700 may also include a memory 703, a communication bus 704, and a communication interface 705.

[0258] The processor 701 can be an FPGA processing circuit.

[0259] The communication bus 704 may include a path for transmitting information between the aforementioned components.

[0260] The memory 703 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital versatile optical discs, Blu-ray discs, etc.), magnetic disks or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto. The memory 703 may exist independently and be connected to the processor 701 via a communication bus 704. The memory 703 may also be integrated with the processor 701.

[0261] The memory 703 stores program code for executing the scheme of this application, and its execution is controlled by the processor 701. The processor 701 executes the program code stored in the memory 703. The program code may include one or more software modules.

[0262] The communication interface 705 uses transceiver 702 to communicate with other devices or communication networks, such as Ethernet, Radio Access Network (RAN), WLAN, etc.

[0263] In a specific implementation, as one example, the data traffic acquisition device may include multiple processors.

[0264] Each of these processors can be a single-core (single-CPU) processor or a multi-core (multi-CPU) processor. Here, "processor" can refer to one or more devices, circuits, and / or processing cores used to process data (such as computer program instructions).

[0265] It should be noted that the electronic device provided in this application embodiment can implement all the method steps implemented in the above method embodiment and can achieve the same technical effect. Here, the parts and beneficial effects that are the same as those in the method embodiment will not be described in detail.

[0266] This application also provides a computer-readable storage medium storing computer-executable instructions for causing a computer to perform a data traffic acquisition method or a data processing method as described in the above embodiments.

[0267] This application also provides a computer program product, which, when invoked by a computer, causes the computer to execute a data traffic acquisition method or a data processing method as described in the above embodiments.

[0268] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0269] This application is described with reference to flowchart illustrations and / or block diagrams of the methods, apparatus (systems), and computer program products according to this application. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0270] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The functions specified in one or more boxes. These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable apparatus for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0271] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0272] The units described in the embodiments of this disclosure can be implemented in software or in hardware. The name of a unit does not necessarily limit the unit itself; for example, the first acquisition unit can also be described as "a unit that acquires at least two Internet Protocol addresses".

[0273] The functions described above in this document can be performed, at least in part, by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: Field Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), Application Standard Products (ASSPs), System-on-Chip (SoCs), Complex Programmable Logic Devices (CPLDs), and so on.

[0274] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0275] This application also provides a data processing device that can be used to execute the technical solutions in the above-described method embodiments of this application. Its implementation principle and technical effect are similar, and will not be repeated here.

[0276] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, or indirect coupling or communication connection between apparatuses or units, and may be electrical, mechanical, or other forms.

[0277] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0278] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0279] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A data processing method, characterized in that, include: Obtain data information for all ports of the network device; Based on the data information of all ports, a first set of ports matching the first monitoring parameter is determined, wherein the first set of ports includes one or more ports from all ports of the network device; According to the preset monitoring method corresponding to the first monitoring parameter, obtain multiple first data quantities of all ports in the first port set corresponding to the data to be monitored corresponding to the first monitoring parameter, so as to obtain the first monitoring data quantity queue corresponding to the first monitoring parameter. Based on the first monitoring data queue, determine the first monitoring result of the data to be monitored corresponding to the first monitoring parameter.

2. The method according to claim 1, characterized in that, Before determining the first set of ports that matches the first monitoring parameter, the method further includes: Obtain the parameter to be monitored, wherein the parameter to be monitored includes the first monitoring parameter; The parameters to be monitored include one or more of the following: device-level monitoring parameters, service type-level monitoring parameters, and data stream-level monitoring parameters. The first monitoring parameter is a device-level monitoring parameter, a service type-level monitoring parameter, or a data stream-level monitoring parameter.

3. The method according to claim 2, characterized in that, The device-level monitoring parameters include monitoring parameters determined based on the total inlet bandwidth and / or monitoring parameters determined based on the total outlet bandwidth; The service type-level monitoring parameters include service type-level monitoring parameters determined based on multicast and / or service type-level monitoring parameters determined based on unicast. The data flow level monitoring parameters include one or more of the following: data flow level monitoring parameters determined based on the destination output port, data flow level monitoring parameters determined based on port hierarchical quality of service, data flow level monitoring parameters determined based on quality of service queues, data flow level monitoring parameters determined based on priority, data flow level monitoring parameters determined based on fourth-generation network protocols, and data flow level monitoring parameters determined based on sixth-generation network protocols.

4. The method according to claim 2 or 3, characterized in that, The step of determining the first set of ports that matches the first monitoring parameter based on the data information of all ports includes: If the first monitoring parameter is a device-level monitoring parameter, then all ports of the network device are determined as the first port set that matches the first monitoring parameter; If the first monitoring parameter is a business type-level monitoring parameter, then a first set of ports matching the first monitoring parameter is determined based on the data information of all ports, wherein the data of each port in the first set of ports includes the data of the business type corresponding to the first monitoring parameter; If the first monitoring parameter is a data stream-level monitoring parameter, then a first set of ports matching the first monitoring parameter is determined based on the data information of all ports, wherein the data of each port in the first set of ports includes the data stream corresponding to the first monitoring parameter.

5. The method according to claim 2 or 3, characterized in that, The acquisition of the parameters to be monitored includes: The parameter configuration interface is displayed in response to the user's first action; In response to a second operation by the user on the parameter configuration interface, a parameter configuration instruction is obtained, wherein the parameter configuration instruction includes the parameter to be monitored.

6. The method according to claim 2 or 3, characterized in that, The method further includes: Based on the data information from all the ports, a second set of ports matching the second monitoring parameter is determined, wherein the second set of ports includes one or more ports from all the ports; According to the preset monitoring method corresponding to the second monitoring parameter, obtain multiple second data quantities of all ports in the second port set that correspond to the data to be monitored corresponding to the second monitoring parameter, so as to obtain the second monitoring data quantity queue corresponding to the second monitoring parameter; Based on the second monitoring data queue, determine the second monitoring result of the data to be monitored corresponding to the second monitoring parameter.

7. The method according to claim 6, characterized in that, The parameter to be monitored also includes the second monitoring parameter; The second monitoring parameter is a device-level monitoring parameter, a service type-level monitoring parameter, or a data stream-level monitoring parameter.

8. The method according to any one of claims 1 to 7, characterized in that, The preset monitoring methods corresponding to the first monitoring parameter include preset sampling time period, preset sampling frequency, preset sampling period, or preset sampling duration.

9. The method according to claim 8, characterized in that, The first monitoring data queue is stored in the storage unit of the network device, which is the static random access memory of a field-programmable gate array (FPGA) chip.

10. The method according to claim 9, characterized in that, The step of determining the first monitoring result of the data to be monitored corresponding to the first monitoring parameter based on the first monitoring data volume queue includes: Extract the first monitoring parameter from the storage unit and extract the first monitoring data queue corresponding to each preset sampling time period; Based on the first monitoring parameter and the first monitoring data queue corresponding to each preset sampling time period, calculate the total data volume corresponding to the first monitoring parameter in each preset sampling time period; Based on the total amount of data corresponding to the first monitoring parameter in each preset sampling time period, the monitoring result of the data to be monitored corresponding to the first monitoring parameter is determined.

11. The method according to claim 10, characterized in that, The step of determining the monitoring result of the data to be monitored corresponding to the first monitoring parameter based on the total data volume corresponding to the first monitoring parameter in each preset sampling time period includes: If the first monitoring parameter is a device-level monitoring parameter, then based on the total amount of data corresponding to the first monitoring parameter in each preset sampling time period, the first monitoring result of the network device corresponding to the data to be monitored corresponding to the first monitoring parameter is determined; If the first monitoring parameter is a business type-level monitoring parameter, then the second monitoring result of the data to be monitored for the business type corresponding to the first monitoring parameter is determined based on the total amount of data corresponding to the first monitoring parameter in each preset sampling time period. If the first monitoring parameter is a data stream-level monitoring parameter, then the third monitoring result of the data stream to be monitored corresponding to the first monitoring parameter is determined based on the total amount of data corresponding to the first monitoring parameter in each preset sampling time period.

12. A data processing apparatus, characterized in that, include: The first acquisition module is used to acquire data information from all ports of the network device; The first determining module is used to determine a first set of ports that matches the first monitoring parameter based on the data information of all ports. The first set of ports includes one or more ports from all ports of the network device. The first acquisition module is used to acquire multiple first data volumes of the data to be monitored corresponding to the first monitoring parameter in the first port set according to the preset monitoring method corresponding to the first monitoring parameter, so as to obtain the first monitoring data volume queue corresponding to the first monitoring parameter. The processing module is used to determine the first monitoring result of the data to be monitored corresponding to the first monitoring parameter based on the first monitoring data volume queue.

13. A data processing device, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1 to 11.

14. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1 to 11.

15. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 11.

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