CN114301818A - Service flow detection method, device, system, terminal and storage medium - Google Patents
Service flow detection method, device, system, terminal and storage medium Download PDFInfo
- Publication number
- CN114301818A CN114301818A CN202011004521.6A CN202011004521A CN114301818A CN 114301818 A CN114301818 A CN 114301818A CN 202011004521 A CN202011004521 A CN 202011004521A CN 114301818 A CN114301818 A CN 114301818A
- Authority
- CN
- China
- Prior art keywords
- flow
- information
- service
- service flow
- band detection
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000001514 detection method Methods 0.000 title claims abstract description 141
- 238000000034 method Methods 0.000 claims abstract description 26
- 238000012986 modification Methods 0.000 claims description 8
- 230000004048 modification Effects 0.000 claims description 8
- 238000004590 computer program Methods 0.000 claims description 6
- 238000004891 communication Methods 0.000 abstract description 6
- 230000008569 process Effects 0.000 abstract description 5
- 238000012423 maintenance Methods 0.000 description 14
- 238000007405 data analysis Methods 0.000 description 12
- 238000007726 management method Methods 0.000 description 11
- 238000005516 engineering process Methods 0.000 description 7
- 230000006870 function Effects 0.000 description 4
- 238000012544 monitoring process Methods 0.000 description 4
- 238000010586 diagram Methods 0.000 description 3
- 238000013461 design Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 230000002093 peripheral effect Effects 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 238000005070 sampling Methods 0.000 description 2
- 230000002159 abnormal effect Effects 0.000 description 1
- 230000032683 aging Effects 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 230000002452 interceptive effect Effects 0.000 description 1
- 238000000691 measurement method Methods 0.000 description 1
- 238000010295 mobile communication Methods 0.000 description 1
- 230000006855 networking Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 230000001960 triggered effect Effects 0.000 description 1
- 238000013024 troubleshooting Methods 0.000 description 1
Images
Landscapes
- Data Exchanges In Wide-Area Networks (AREA)
Abstract
The embodiment of the invention relates to the technical field of communication, and discloses a service flow detection method, a device, a system, a terminal and a storage medium. The service flow detection method in the embodiment includes: determining a service flow to be detected in a target network according to the relevant information of the service flow; searching IP flow information of a service flow to be detected in a pre-generated association model, and configuring an in-band detection task aiming at the service flow to be detected according to the IP flow information; the correlation model is used for describing the corresponding relation between the relevant information of the service flow in the target network and the IP flow information; and executing the in-band detection task and acquiring performance data acquired according to the in-band detection task. By the technical means, the configuration process of the in-band detection task for the service flow in the network is simplified, the automatic configuration of the in-band detection task is realized, and the performance and the quality detection efficiency of the service flow are improved.
Description
Technical Field
The present disclosure relates to the field of communications technologies, and in particular, to a method, an apparatus, a system, a terminal, and a storage medium for detecting a service flow.
Background
With the development of communication technology, wireless mobile communication has moved into the 5G (5th Generation mobile networks) era. The new communication technology brings higher bandwidth, lower time delay and more flexible connection mode. In a 5G network, a more accurate and reliable network Maintenance means can be provided by adopting an in-band OAM (Operations, Administration, and Maintenance) detection technology. When the network quality index changes, the network quality index can be sensed in time, so that the response speed of network fault location is improved, and the time for fault processing is shortened. In-band OAM is an on-stream measurement technique based on real traffic flow. Based on the flow following detection principle, the in-band OAM provides the capability of detecting the service packet loss and the time delay of real service flow end to end and point by point, can quickly sense the related faults of the network performance, and carries out accurate delimitation and troubleshooting, thereby being an important means for the operation and maintenance of the future 5G mobile bearer network.
However, the detection object of the current in-band OAM detection task is a traffic flow, and the configuration method is complicated when the in-band detection task is established. When the in-band OAM detection sessions of the service flows need to be deployed in batch, a large amount of labor is required to complete the configuration of the detection sessions.
Disclosure of Invention
The embodiments of the present application mainly aim to provide a method, a system, a terminal, and a storage medium for detecting a service flow, which can automatically configure an in-band detection task for the service flow, improve task deployment efficiency, and reduce labor cost.
In order to achieve the above object, an embodiment of the present application provides a method for detecting a service flow, including: determining a service flow to be detected according to the relevant information of the service flow; searching IP flow information of a service flow to be detected in a pre-generated association model, and configuring an in-band detection task aiming at the service flow to be detected according to the IP flow information; the correlation model is used for describing the corresponding relation between the relevant information of the service flow in the target network and the IP flow information; and executing the in-band detection task and acquiring performance data acquired according to the in-band detection task.
In order to achieve the above object, an embodiment of the present application further provides a device for detecting a service flow, including: the determining module is used for determining the service flow to be detected according to the relevant information of the service flow; the query module is used for searching the IP flow information of the service flow to be detected in the pre-generated association model; the correlation model is used for describing the corresponding relation between the relevant information of the service flow in the target network and the IP flow information; the configuration module is used for configuring an in-band detection task aiming at the service flow to be detected according to the IP flow information; and the execution module is used for executing the in-band detection task and acquiring the performance data acquired according to the in-band detection task.
In order to achieve the above object, an embodiment of the present application further provides a terminal, including: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the traffic flow detection method as described above.
To achieve the above object, an embodiment of the present application further provides a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the method for detecting a traffic flow is implemented.
The service flow detection method determines the service flow to be detected in all service flows of a target network according to the relevant information of the service flow, then finds out the IP flow information of the service flow to be detected in a pre-generated correlation model for describing the corresponding relation between the relevant information of the service flow in the target network and the IP flow information, and completes the configuration of an in-band detection task of the service flow to be detected according to the IP flow information, so that the automatic configuration of the in-band detection task is realized, the configuration of batch tasks can be automatically completed, and the deployment efficiency of the in-band detection task is improved.
Drawings
Fig. 1 is a flow chart of a traffic flow detection method according to a first embodiment of the present invention;
FIG. 2 is a flow chart of a correlation model generation method according to a first embodiment of the present invention;
fig. 3 is a flow chart of a traffic flow detection method according to a second embodiment of the present invention;
fig. 4 is a schematic structural diagram of a traffic flow detection system according to a third embodiment of the present invention;
fig. 5 is a schematic structural diagram of a traffic flow detection apparatus according to a fourth embodiment of the present invention;
fig. 6 is a schematic structural diagram of a terminal according to a fifth embodiment of the present invention.
Detailed Description
To make the objects, technical solutions and advantages of the embodiments of the present application clearer, the embodiments of the present application will be described in detail below with reference to the accompanying drawings. However, it will be appreciated by those of ordinary skill in the art that in the examples of the present application, numerous technical details are set forth in order to provide a better understanding of the present application. However, the technical solution claimed in the present application can be implemented without these technical details and various changes and modifications based on the following embodiments. The following embodiments are divided for convenience of description, and should not constitute any limitation to the specific implementation manner of the present application, and the embodiments may be mutually incorporated and referred to without contradiction.
A first embodiment of the present invention relates to a method for detecting a service flow, including: determining a service flow to be detected according to the relevant information of the service flow; searching IP flow information of a service flow to be detected in a pre-generated association model, and configuring an in-band detection task aiming at the service flow to be detected according to the IP flow information; the correlation model is used for describing the corresponding relation between the relevant information of the service flow in the target network and the IP flow information; and executing the in-band detection task and acquiring performance data acquired by the in-band detection task. The execution subject of this embodiment is a terminal that performs in-band detection task deployment.
The present embodiment is further explained with reference to the accompanying drawings, and a method for detecting a service flow in the present embodiment is shown in fig. 1, and includes:
Specifically, the present embodiment is applied to a network that needs to perform quality of service monitoring, that is, the target network mentioned in the present embodiment. In the target network, the related information of the traffic flow includes: the service name of the service flow attribution, the identification of the service flow, the identification of the access equipment at the bearing side of the service flow, the identification of the access interface, the network element node and the network element interface which are related to the service flow, and the like. The related information of the service flows can be obtained by inquiring through a network management system in the target network.
In one example, when a terminal deploying an in-band detection task receives relevant information of an input service flow, a corresponding service flow is inquired in a network management system according to the relevant information of the service flow and is used as the service flow to be detected. In addition, the terminal deploying the in-band detection task can also automatically select the service flow obtained by inquiry based on a preset rule.
Further, when the terminal deployed by the in-band detection task receives the relevant information of the input service flow, the service flow corresponding to the relevant information of the service flow is searched in the association model according to the relevant information of the service flow, and then the selected service flow is determined as the service flow to be detected in the corresponding service flow according to the received selection instruction for the service flow. That is, after querying the corresponding service flow, the terminal may display all the service flows obtained by the query to the user, and the user specifically selects the service flow to be detected.
In practical application, when a user designates a related service, or a network element subinterface on a terminal deploying an in-band detection task, the terminal queries and generates all service flows under the service, or all services and service flows corresponding to the network element subinterface through a pre-generated association model. The pre-generated association model is used for describing the corresponding relation between the relevant information of the service flow in the target network and the IP flow information. After a user determines the service flow to be detected through the terminal, the IP flow information corresponding to the service flow to be detected is searched through the association model.
And 102, searching the IP flow information of the service flow to be detected in a pre-generated association model.
Specifically, in the related art, when an in-band detection task for a service flow is configured, parameters such as a network element node, a source interface, a source IP address, a destination interface, a destination IP address, and a priority corresponding to the service flow need to be specified. The information is required to be inquired through a network management system and then relevant parameters are manually filled in to complete the configuration of the task.
In one example, the association model is generated by a data acquisition end and a terminal for data analysis in a target network according to an IP flow information acquisition task and task-related parameters, and the IP flow information acquisition task and the task-related parameters are issued by a terminal deploying an in-band detection task. The generation mode of the association model is shown in fig. 2, and includes:
Specifically, the generation of the association model is completed by a data acquisition terminal and a terminal for data analysis in the target network. When a user needs to establish a correlation model, an IP flow information acquisition task and parameters related to the task are issued to a data acquisition terminal through a terminal for task deployment. The issuing, starting and stopping of the tasks are all controlled by a terminal used for task deployment. The collection of the IP flow information can be performed through the NetFlow function, the collected data is mainly the IP flow information related to the service flow, and the parameters related to the task determine the collection object, the collection protocol, the sampling rate, the collection period, and the like of the IP flow information.
When the IP flow information is acquired through the NetFlow function, the set parameters comprise an acquisition period, start time, acquisition time, a flow sampling rate, flow convergence time, a monitoring port, a task type and the like. In practical applications, the collection period is generally calculated in units of days or weeks, and attributes of an instant or timed task can be added to the task according to the time when the task starts.
Specifically, the bearer device of the target network includes an access side device and a core side device in the target network. And after receiving the service flow acquisition task and the instruction for starting the task execution, the data acquisition end starts to acquire the IP flow information of all service flows in the target network according to the parameters carried in the acquisition task. Because the collected relevant data of the IP flow information is the original data, the data needs to be analyzed and pre-counted to obtain the IP flow information related to the service flow, and the unique corresponding service flow is identified by a quintuple, which includes: source IP address, source port number, destination IP address, destination port number, protocol number, priority (Differentiated Services Code Point). Pre-statistics refers to analyzing the collected traffic flow to obtain preliminary traffic characteristics.
Specifically, after the data acquisition end completes the task of acquiring the IP flow information and performs analysis and pre-statistics on the original data, the pre-statistical IP flow information is sent to the terminal for data analysis. The related information of the service flow includes: the system comprises a first access device at a bearing side, a first access interface, a second access device at the bearing side, a second access interface, an L3VPN service identifier, creation time, updating time and the like.
In practical application, a terminal for data analysis can acquire a source IP address corresponding to each service flow through a network management system, query an L3VPN service routing table, match a target network segment of a virtual routing interface, and acquire a first access device and a first access interface on a bearer side corresponding to the source IP address of the service flow; and meanwhile, acquiring the L3VPN service information to which the service flow belongs. Similarly, the network management system may also obtain a destination IP address corresponding to each service flow, query the L3VPN service routing table, match the target network segment of the virtual routing interface, and obtain the second access device and the second access interface on the bearer side corresponding to the destination IP address of the service flow.
And step 204, the data analysis end generates a correlation model according to the relevant information of all the service flows.
Specifically, the establishing of the associated information of the service flow related information and the IP flow information for each service flow, that is, the associated information of the bearer side access device, the access interface, and the service includes: the system comprises a source IP address, first access equipment on a bearing side, a first access interface, a source port number, a destination IP address, second access equipment on the bearing side, a second access interface, a destination port number, a protocol number, a priority (DSCP), an L3VPN service identifier, creation time, updating time and the like. And then generating a final association model according to the association information and the IP flow information.
Further, the data analysis terminal can also obtain data related to the performance of each service flow through a network management system of the target network. The method comprises the steps of taking parameters such as jitter, time delay, packet loss rate and flow rate of a service flow as indexes, extracting performance and quality characteristics of the service flow according to performance-related historical data from time dimensions such as seconds, minutes, moments, hours, days, weeks and months, index types such as mean values or peak values, and different time periods such as busy hours, idle hours and holidays, and can be used as current service characteristics of the service flow and predict the change trend of the service characteristics in the future. Therefore, the IP information and the service characteristics of the service are associated with the service flow by collecting and analyzing all the service IP flow information and the service characteristics in the target network, and the binding of the detection object and the service characteristics is realized.
In one example, based on the established association model, the service characteristics of the objects such as network element nodes, network element subinterfaces, services, etc. in the target network, including performance and quality indicators, are known to the user, and the system can automatically display the matched service flows according to the relevant information of the service flows input by the user. Therefore, when a user deploys the in-band detection task, the user can purposefully input the characteristics of the service in a specific area range, that is, the terminal automatically screens out the corresponding service flow in the specific range for the user to deploy the in-band detection task, so as to realize the target area of interest, such as: the deployment of in-band detection tasks is carried out in areas with high activity, areas with obvious tidal effect, areas with possible flow bottlenecks and the like, and the monitoring of the performance and quality data of the service flow can be carried out more intelligently.
And 103, configuring an in-band detection task aiming at the service flow to be detected according to the IP flow information.
Specifically, in the related art, when an in-band detection task for a service flow is configured in an actual networking structure, parameters such as a network element node, a source interface, a source IP address, a destination interface, a destination IP address, and a priority corresponding to the service flow need to be specified. The IP address of the core side device is allocated through the IP address pool, and the specific IP address of the core side device is not known or is difficult to be known initially, because the IP information is necessary information, and the parameters of the downstream in-band detection task cannot be configured at this time. By adopting the technical means in the embodiment, the detectable IP flow information can be automatically identified after the network element node is selected without paying attention to the specific IP address to be configured. The process of parameter configuration of the in-band detection task is automatically completed without manual operation. When the batch in-band detection tasks are configured, the terminal for in-band detection task deployment can automatically fill all parameters of the in-band detection tasks aiming at all service flows to be detected, so that the automatic configuration of the in-band detection tasks is realized.
Based on the service flow detection method in this embodiment, in an actual application, when a user inputs related information of a service flow through a terminal deploying an in-band detection task, such as a network element name or a network element name and a specific network element interface, if 15 matched service flows are queried in an association model through the network element name or the specific network element interface, the 15 service flows are all displayed in an interactive interface through the terminal deploying the in-band detection task for the user to refer to; and meanwhile, synchronously acquiring an IP flow information quintuple corresponding to the network element name or the specific network element interface in the background. At this time, if the user has preset the rule of in-band detection task deployment, the service flow to be detected is automatically selected, the in-band detection task for the service flow to be detected is configured according to the IP flow information quintuple, and parameters required by configuration are filled in. If the user does not preset the rule of in-band detection task deployment, after the user inputs an instruction for selecting the in-band detection task, the in-band detection task for the service flow to be detected is configured according to the IP flow information, and parameters required by configuration are filled.
And 104, executing the in-band detection task and acquiring performance data acquired by the in-band detection task.
Specifically, the terminal for in-band detection task deployment executes the configured in-band detection task, monitors and records performance data of the corresponding service flow, and identifies a fault related to network performance, and positions and eliminates faults when the performance data of the service flow is found to be abnormal.
Compared with the related art in the field, the service flow detection method in this embodiment pre-establishes an association model for describing a correspondence between the related information of the service flow in the target network and the IP flow information, and realizes association between the detection object and the service characteristics and the IP flow information. When an in-band detection task for the service flow is established, IP information corresponding to the service flow is inquired according to the association model, and the configuration of the in-band detection task is automatically completed. Under the scene of batch in-band detection task deployment, the configuration of the in-band detection task can be completed quickly without manual intervention. The in-band detection technology can be applied in richer scenes, the deployment efficiency is higher, and meanwhile, the task deployment and maintenance cost can be reduced.
It should be noted that the above examples in the present embodiment are only for easy understanding, and do not limit the technical scheme of the present invention.
A second embodiment of the present invention relates to a method for detecting a service flow, and the second embodiment is substantially the same as the first embodiment, and mainly differs from the first embodiment in that: in this embodiment, after the association model is stored in the database, when the IP flow information is changed, that is, when the newly acquired IP flow information is different from the IP flow information existing in the current association model, the IP flow information is modified and the association model is updated according to the modified IP flow information. In addition, after the in-band detection task is executed, if the in-band detection task established for the IP flow information before modification exists, the in-band detection task established for the modified IP flow information is modified or deleted.
The present embodiment is further explained with reference to the accompanying drawings, and a method for detecting a service flow in the present embodiment is shown in fig. 3, and includes:
And 303, configuring an in-band detection task aiming at the service flow to be detected according to the IP flow information.
And step 304, executing the in-band detection task and acquiring performance data acquired by the in-band detection task.
Specifically, in this embodiment, after the association model is generated, if a new IP flow information collection task is received, and in the collection process, when it is found that newly collected IP flow information is inconsistent with existing IP flow information, the IP flow information is modified into the newly collected IP flow information, and then data in the association model is modified according to the new IP flow information, so as to generate a new association model. And completing the maintenance of the association model.
In addition, the terminal deploying the in-band detection task can also obtain the relevant information of the service flow through the network management system, so as to monitor the relevant information of the service flow in the target network in real time. When the access equipment, the access interface and the service information of the bearing side are modified and deleted, the system synchronously modifies or deletes the corresponding service flow and the related information in the access equipment, the access interface and the service association model of the bearing side, and simultaneously checks whether an in-band OAM detection session constructed aiming at the information exists in the system, if so, modifies or deletes the corresponding in-band detection task. Meanwhile, after the service flow is aged, when the associated information of the service flow, the access equipment at the bearing side, the access interface and the service is deleted, whether an in-band detection task constructed aiming at the service flow exists in the system is simultaneously checked, and if the in-band detection task exists, the in-band detection task is deleted together, so that the intelligent updating and maintenance of the in-band detection task are realized.
In the related art, the maintenance of the in-band detection task is static, when the service changes, the detected service flow also changes at the same time, and if the service flow being detected does not exist, the user can only analyze whether the service flow does not exist, and then decide whether to update the original in-band detection task. When the number of in-band detection tasks reaches a certain scale, the related technology obviously cannot meet the basic operation and maintenance requirements. Therefore, the technical means for in-band detection task maintenance mentioned in this embodiment can more intelligently identify dead traffic flows and update them in time.
Further, after the IP flow information or the related information of the service flow in the association model is changed, the currently running in-band detection task is queried in real time, and whether an in-band detection task established for the service flow corresponding to the IP flow information or the related information of the service flow before modification exists is searched. If the in-band detection task established for the service flow corresponding to the IP flow information or the related information of the service flow before modification currently exists, deleting the corresponding in-band detection task, or redeploying the modified in-band detection task after modifying the configuration parameters of the corresponding in-band detection task. The in-band detection task can be monitored in real time, so that the in-band detection task can be found and reported to a maintenance user in time when the in-band detection task is dead, the manual participation degree is reduced, and the intelligent updating and maintenance of the in-band detection task to a certain degree are realized.
In a specific implementation, when the bearer side access device, the access interface, and the service information are modified and deleted, the terminal deploying the in-band detection task synchronously modifies or deletes the corresponding in-band detection task and the related information of the service flow in the service association model such as the bearer side access device and the access interface.
In addition, when the access equipment, the access interface and the service information of the bearing side are increased, a service flow real-time acquisition task of a specified monitoring port can be manually triggered by maintenance personnel, and the associated information of the service flow, the access equipment, the access interface and the service flow of the bearing side is generated according to the acquired service flow; or when waiting for the timing collection of the service flow, the associated information of the newly added service flow, the access equipment at the bearing side, the access interface and the service is generated.
After acquiring IP flow information according to a newly received IP flow information acquisition task, a data acquisition end uniquely identifies a service flow according to a quintuple (a source IP address, a source port number, a destination IP address, a destination port number and a protocol number), and establishes an association model of the service flow, a bearing side access device, an access interface and the service for the newly added service flow; and for the existing service flow, modifying the updating time in the association information of the service flow, the bearing side access equipment, the access interface and the service into the time for maintaining the relationship. And when the time difference between the updating time and the current time in the associated information exceeds the set relationship aging time, deleting the associated information of the service flow, the bearing side access equipment, the access interface and the service.
Compared with the related technology in the field, after the in-band detection task is deployed, the state of the in-band detection task is continuously monitored, and whether a dead task exists is actively inquired when the IP flow information is updated; and simultaneously, when new IP flow information is acquired, the association between the newly added service flow and the service flow related information and the IP flow information is increased. The in-band detection task can be monitored in real time, so that the in-band detection task can be found and reported to a maintenance user in time when a zombie occurs in the in-band detection task, the manual participation degree is reduced, and the intelligent updating and maintenance of the in-band detection task to a certain degree are realized.
It should be noted that the above examples in the present embodiment are only for easy understanding, and do not limit the technical scheme of the present invention.
The steps of the above methods are divided for clarity, and the implementation may be combined into one step or split some steps, and the steps are divided into multiple steps, so long as the same logical relationship is included, which are all within the protection scope of the present patent; it is within the scope of the patent to add insignificant modifications to the algorithms or processes or to introduce insignificant design changes to the core design without changing the algorithms or processes.
A third embodiment of the present invention relates to a traffic flow detection apparatus, as shown in fig. 3, including:
a determining module 401, configured to determine a service flow to be detected according to relevant information of the service flow;
the query module 402 is configured to search, in a pre-generated association model, IP flow information of a service flow to be detected; the correlation model is used for describing the corresponding relation between the relevant information of the service flow in the target network and the IP flow information;
a configuration module 403, configured to configure an in-band detection task for the detected service flow according to the IP flow information;
the execution module 404 is configured to execute the in-band detection task and obtain performance data acquired according to the in-band detection task.
It should be noted that each module involved in this implementation is a logical module, and in practical applications, one logical unit may be one physical unit, may be a part of one physical unit, and may also be implemented by a combination of multiple physical units. In addition, in order to highlight the innovative part of the present invention, a unit which is not so closely related to solve the technical problem proposed by the present invention is not introduced in the present embodiment, but this does not indicate that there is no other unit in the present embodiment.
A fourth embodiment of the present invention relates to a traffic flow detection system, as shown in fig. 5, including: the data acquisition end 502 and the data analysis end 503 are the service flow detection device 501 in the third embodiment, and both the data acquisition end 502 and the data analysis end 503 are in communication connection with the service flow detection device 501; the data acquisition end 502 is further in communication connection with a bearer device of a target network.
The service flow detection apparatus 501 further includes: and the indicating module is used for indicating the data acquisition end to acquire the IP flow information of all the service flows in the target network from the bearing equipment of the target network.
The data acquisition end 502 is configured to acquire IP flow information of all service flows in the target network from a load device of the target network, and send the acquired IP flow information to the data analysis end.
The data analysis end 503 is configured to query, according to the IP flow information, relevant information of all service flows in the network management system of the target network, generate an association model according to the relevant information of all service flows, and store the association model in a local database for the query module of the service flow detection apparatus to retrieve.
In one example, the service flow detection apparatus 501 is further configured to modify or delete the in-band detection task established for the modified IP flow information when it is found that the in-band detection task established for the IP flow information before modification currently exists.
In another example, the traffic flow detection device 501 is further configured to receive related information of an incoming traffic flow; searching a service flow corresponding to the relevant information of the service flow in the association model according to the relevant information of the service flow; and determining the selected service flow as the service flow to be detected in the corresponding service flow according to the received selection instruction.
In another example, the traffic flow detection apparatus 501 is further configured to search, according to the network element information, a traffic flow corresponding to the network element information in the association model.
In one example, the data analysis end 503 is further configured to modify the IP flow information and update the association model according to the modified IP flow information when there is a difference between the newly acquired IP flow information and the existing IP flow information.
It should be noted that each module involved in this implementation is a logical module, and in practical applications, one logical unit may be one physical unit, may be a part of one physical unit, and may also be implemented by a combination of multiple physical units. In addition, in order to highlight the innovative part of the present invention, a unit which is not so closely related to solve the technical problem proposed by the present invention is not introduced in the present embodiment, but this does not indicate that there is no other unit in the present embodiment.
A fifth embodiment of the present invention is directed to a terminal, as shown in fig. 6, including: at least one processor 601; and a memory 602 communicatively coupled to the at least one processor 601; the memory 602 stores instructions executable by the at least one processor 601, and the instructions are executed by the at least one processor 601 to enable the at least one processor 601 to execute the traffic flow detection method in the first or second embodiment.
Where the memory 602 and the processor 601 are coupled by a bus, the bus may comprise any number of interconnected buses and bridges that couple one or more of the various circuits of the processor 601 and the memory 602 together. The bus may also connect various other circuits such as peripherals, voltage regulators, power management circuits, and the like, which are well known in the art, and therefore, will not be described any further herein. A bus interface provides an interface between the bus and the transceiver. The transceiver may be one element or a plurality of elements, such as a plurality of receivers and transmitters, providing a means for communicating with various other apparatus over a transmission medium. The data processed by the processor 601 is transmitted over a wireless medium via an antenna, which further receives the data and transmits the data to the processor 601. The processor 601 is responsible for managing the bus and general processing and may also provide various functions including timing, peripheral interfaces, voltage regulation, power management, and other control functions. While memory 602 may be used to store data used by processor 601 in performing operations.
A sixth embodiment of the present invention relates to a computer-readable storage medium storing a computer program. The computer program realizes the above-described method embodiments when executed by a processor.
That is, as can be understood by those skilled in the art, all or part of the steps in the method for implementing the embodiments described above may be implemented by a program instructing related hardware, where the program is stored in a storage medium and includes several instructions to enable a device (which may be a single chip, a chip, or the like) or a processor (processor) to execute all or part of the steps of the method described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
It will be understood by those of ordinary skill in the art that the foregoing embodiments are specific embodiments for practicing the invention, and that various changes in form and details may be made therein without departing from the spirit and scope of the invention in practice.
Claims (10)
1. A method for detecting service flow is characterized by comprising the following steps:
determining a service flow to be detected in a target network according to the relevant information of the service flow;
searching the IP flow information of the service flow to be detected in a pre-generated association model; the correlation model is used for describing the corresponding relation between the relevant information of the service flow in the target network and the IP flow information;
configuring an in-band detection task aiming at the service flow to be detected according to the IP flow information;
and executing the in-band detection task and acquiring performance data acquired according to the in-band detection task.
2. The traffic flow detection method according to claim 1, wherein the association model is generated by:
acquiring IP flow information of all service flows in the target network from a bearing device of the target network;
inquiring the related information of all the service flows in a network management system of the target network according to the IP flow information;
and generating the association model according to the relevant information of all the service flows, and storing the association model in a database.
3. The method according to claim 2, wherein before determining the traffic flow to be detected in the target network according to the related information of the traffic flow, the method further comprises:
issuing an IP flow information acquisition task to a data acquisition end, and indicating the data acquisition end to acquire IP flow information of all service flows in the target network from a bearing device of the target network; the IP flow information acquisition task comprises an acquisition period;
after the executing the in-band detection task, further comprising:
if the IP flow information of all the service flows which is periodically collected has changed IP flow information, the changed IP flow information is modified and the correlation model is updated according to the modified IP flow information.
4. The traffic flow detection method according to claim 3, further comprising, after said storing said association model in a database:
and if the in-band detection task established for the IP flow information before modification currently exists, modifying or deleting the in-band detection task established for the modified IP flow information.
5. The method according to claim 1, wherein before determining the service flow to be detected according to the related information of the service flow, the method further comprises:
receiving relevant information of an input service flow;
the determining the service flow to be detected in the target network according to the relevant information of the service flow includes:
searching a service flow matched with the relevant information of the input service flow in a target network in the correlation model;
and determining the selected service flow as the service flow to be detected in the matched service flows according to the received selection instruction.
6. The method according to claim 5, wherein the related information of the service flow includes network element information and/or service characteristics;
the searching for the service flow corresponding to the relevant information of the service flow in the association model according to the relevant information of the service flow includes:
and searching the service flow matched with the input network element information and/or service characteristics in the association model.
7. The traffic flow detection method according to any one of claims 1 to 6, wherein the IP flow information is expressed in a quintuple form, and comprises: source IP address, source port number, destination IP address, destination port number, protocol number.
8. A traffic flow detection apparatus, comprising:
the determining module is used for determining the service flow to be detected in the target network according to the relevant information of the service flow;
the query module is used for searching the IP flow information of the service flow to be detected in a pre-generated association model; the correlation model is used for describing the corresponding relation between the relevant information of the service flow in the target network and the IP flow information;
the configuration module is used for configuring an in-band detection task aiming at the service flow to be detected according to the IP flow information;
and the execution module is used for executing the in-band detection task and acquiring performance data acquired according to the in-band detection task.
9. A terminal, comprising: at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform a traffic flow detection method according to any one of claims 1 to 7.
10. A computer-readable storage medium storing a computer program, wherein the computer program is executed by a processor to implement the traffic flow detection method according to any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011004521.6A CN114301818A (en) | 2020-09-22 | 2020-09-22 | Service flow detection method, device, system, terminal and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011004521.6A CN114301818A (en) | 2020-09-22 | 2020-09-22 | Service flow detection method, device, system, terminal and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114301818A true CN114301818A (en) | 2022-04-08 |
Family
ID=80964181
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011004521.6A Pending CN114301818A (en) | 2020-09-22 | 2020-09-22 | Service flow detection method, device, system, terminal and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114301818A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115022200A (en) * | 2022-05-23 | 2022-09-06 | 中国电信股份有限公司 | Detection method, system, node and computer readable storage medium |
| CN115174449A (en) * | 2022-05-30 | 2022-10-11 | 杭州初灵信息技术股份有限公司 | Method, system, device and storage medium for transmitting detection information along with stream |
| WO2024088064A1 (en) * | 2022-10-28 | 2024-05-02 | 中兴通讯股份有限公司 | In-band operation, administration and maintenance (oam) measurement method and system |
-
2020
- 2020-09-22 CN CN202011004521.6A patent/CN114301818A/en active Pending
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115022200A (en) * | 2022-05-23 | 2022-09-06 | 中国电信股份有限公司 | Detection method, system, node and computer readable storage medium |
| CN115174449A (en) * | 2022-05-30 | 2022-10-11 | 杭州初灵信息技术股份有限公司 | Method, system, device and storage medium for transmitting detection information along with stream |
| CN115174449B (en) * | 2022-05-30 | 2024-03-26 | 杭州初灵信息技术股份有限公司 | Method, system, device and storage medium for transmitting stream-following detection information |
| WO2024088064A1 (en) * | 2022-10-28 | 2024-05-02 | 中兴通讯股份有限公司 | In-band operation, administration and maintenance (oam) measurement method and system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN114301818A (en) | Service flow detection method, device, system, terminal and storage medium | |
| CN101631053B (en) | EAPS ring-network topology monitoring method and system | |
| JP5840788B2 (en) | Method, apparatus and communication network for root cause analysis | |
| JP3510658B2 (en) | Network analysis method | |
| CN104125087B (en) | A kind of alarm information processing method and device | |
| CN112187512B (en) | Port automatic expansion method, device and equipment based on flow monitoring | |
| EP3958508A1 (en) | Data processing method and device, storage medium and electronic device | |
| CN107204894A (en) | The monitoring method and device of network servicequality | |
| CN111865736B (en) | Equipment control method and device | |
| CN108924007B (en) | Big data acquisition and storage system and method of communication operation information | |
| CN101242302A (en) | Data synchronization method, device and system | |
| CN116980284B (en) | Optical cable fiber distribution box operation and maintenance information transmission method and system based on Internet of things | |
| CN104283802A (en) | Neighbor discovery method and device | |
| CN103812688A (en) | Alarm determining method and device | |
| CN107784009A (en) | Data query, data query processing method and processing device | |
| CN113810229A (en) | IOAM quality performance data analysis method and device based on time sequence scheduling | |
| CN114338373A (en) | Network element configuration data storage method and device, electronic equipment and storage medium | |
| CN106603722B (en) | Management equipment determining method and device | |
| CN117478582A (en) | Oil field production equipment state monitoring and optimizing method based on intelligent link management system | |
| CN112486656B (en) | Method for realizing wireless ionization wire task scheduling and data downloading | |
| CN101917699B (en) | Random reported signaling tracking method and device based on users | |
| CN112488491B (en) | Petri network-based train control vehicle-mounted equipment access process reliability evaluation method | |
| CN114448868A (en) | Path scheduling method, device and equipment based on segmented routing strategy | |
| CN118139088B (en) | Equipment management platform based on 5G network | |
| CN106488489B (en) | Method and device for recovering user service data |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |