Online real-time measurement method, communication device and storage medium

Abstract

The invention provides an online real-time measurement method, a communication device and a storage medium, relates to the technical field of communication, and can reduce the amount of measured information while meeting the precision requirement of a traffic matrix and ensure real-time adjustment. The method comprises the following steps: acquiring a first traffic matrix corresponding to a current period and first measurement information corresponding to the current period, and processing the first traffic matrix based on the first measurement information to obtain a second traffic matrix corresponding to the current period, and under the condition that an error between the second traffic matrix and a fourth traffic matrix corresponding to a previous period of the current period is within a target precision range, sending first indication information to the traffic matrix demand node, the first measurement information comprises measured flow information of at least one source node-destination node OD pair in the first flow matrix; the first indication information is used for indicating the second traffic matrix, and the fourth traffic matrix is determined based on the traffic information of the plurality of OD pairs in the previous period.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to an online real-time measurement method, a communication device, and a storage medium. Background Art

[0002] Traffic matrices represent traffic information for origin-destination (OD) pairs in communication networks. They are crucial for communication networks because they provide key information for network resilience assessment, congestion analysis, and performance diagnostics.

[0003] Currently, measurement and inference methods (also called estimation methods) are commonly used to determine the traffic matrix. The first solution (i.e., the measurement method) requires a large amount of measurement information and requires support for specific protocol features, such as NetFlow or NetStream protocols. Since such features are rarely enabled in actual networks, the measurement method is rarely used in practical applications. The second solution (i.e., the inference method) can determine the traffic matrix based on network information, where network information includes routing information, network topology characteristics, and the total input / output traffic information (also called load information) of all nodes in the network. However, the traffic matrix obtained by the inference method is not very accurate. Generally, the error between the inferred traffic matrix and the actual traffic matrix is ​​within the range of 20% to 30%, resulting in the inferred traffic matrix being unable to meet the needs of actual applications. This can easily lead to large deviations in business applications such as network resilience assessment, congestion analysis, and performance diagnosis, and cannot meet the needs of actual applications. Summary of the Invention

[0004] In order to solve the above technical problems, the embodiments of the present application provide an online real-time measurement method, a communication device and a storage medium, which can reduce the amount of measured information while meeting the accuracy requirements of the traffic matrix and ensure real-time adjustment.

[0005] In a first aspect, an online real-time measurement method is provided. The method can be executed by a network controller, or by a component of the network controller, such as a processor, chip, or chip system of the network controller, or by a logic module or software that can implement all or part of the network controller. The following description takes the method executed by the network controller as an example. The online real-time measurement method includes: obtaining a first traffic matrix corresponding to the current cycle and first measurement information corresponding to the current cycle, processing the first traffic matrix based on the first measurement information to obtain a second traffic matrix corresponding to the current cycle, and sending first indication information to a traffic matrix demand node when the error between the second traffic matrix and the fourth traffic matrix corresponding to the previous cycle of the current cycle is within a target accuracy range, wherein the first traffic matrix is ​​determined based on at least one of routing information, Simple Network Management Protocol (SNMP) data of multiple nodes, a target accuracy range, network topology information, or network status information, and the first measurement information includes traffic information of at least one source node-destination node (OD) pair measured in the first traffic matrix; the first indication information is used to indicate the second traffic matrix, and the fourth traffic matrix is ​​determined based on traffic information of multiple OD pairs in the previous cycle.

[0006] In an embodiment of the present application, the first measurement information includes the flow information of at least one OD pair measured in the first flow matrix, that is, the first measurement information includes the flow information of at least one OD pair that is actually measured, so that the first measurement information has a higher accuracy, and then the network controller processes the inferred flow matrix (i.e., the first flow matrix) based on the first measurement information to obtain a second flow matrix to improve the accuracy of the processed second flow matrix. However, in order to further ensure that the accuracy of the second flow matrix sent to the flow matrix demand node is within a reasonable range, the network controller can send the second flow matrix to the flow matrix demand node when the error between the second flow matrix and the flow matrix measured in the previous cycle is within the target accuracy range. This not only improves the accuracy of the flow matrix obtained by the flow matrix demand node, but also ensures that the accuracy of the flow matrix obtained by the flow matrix demand node can be within a reasonable range.

[0007] Furthermore, in an embodiment of the present application, the network controller does not need to measure all the traffic information in the network, but only needs to obtain information such as routing information, SNMP data of multiple nodes, target accuracy range, network topology information, network status information, and first measurement information. Since the traffic matrix itself has characteristics such as low rank characteristics, time correlation, and spatial correlation, the network controller can determine the traffic matrix that meets the accuracy requirements through a small amount of information (i.e., routing information, SNMP data of multiple nodes, target accuracy range, network topology information, network status information, and first measurement information). This can reduce the amount of information measured when meeting the accuracy requirements of the traffic matrix. And since information such as routing information, SNMP data of multiple nodes, target accuracy range, network topology information, network status information, and first measurement information is real-time, that is, the information related to determining the traffic matrix recorded in the embodiment of the present application is real-time, so the traffic matrix that meets the accuracy requirements determined based on the above information is also real-time, so if the above information related to determining the traffic matrix changes, the traffic matrix output by the network controller will also be adaptively adjusted in real time.

[0008] In addition, the online real-time measurement method provided in the embodiment of the present application can be executed by a network controller in an existing communication network without being restricted to devices deployed with dedicated hardware, thereby reducing the restrictiveness of the online real-time measurement method provided in the embodiment of the present application and improving the applicability of the online real-time measurement method provided in the embodiment of the present application.

[0009] In conjunction with the first aspect described above, in one possible implementation, the number of OD pairs included in at least one OD pair is less than or equal to a first threshold, i.e., the number of OD pairs to be measured is relatively small. This minimizes the time required to measure the flow information of the OD pairs, thereby minimizing the time required to output the entire flow matrix. In other words, the network controller can quickly determine the final output flow matrix, shortening the time interval between the final output flow matrix and the flow information collection time. This maximizes the real-time performance of the final output flow matrix, making the final output flow matrix more valuable as a reference.

[0010] In combination with the above-mentioned first aspect, in a possible implementation method, obtaining the first measurement information corresponding to the current period includes: sending second indication information to the destination node of each OD pair in at least one OD pair, and receiving third indication information from the destination node of each OD pair, respectively. The second indication information is used to indicate the destination node to measure the traffic information of the corresponding OD pair during the current period, and the third indication information is used to indicate the traffic information of the corresponding OD pair during the current period.

[0011] That is, the network controller can instruct the destination node of each OD pair to measure the traffic information of the corresponding OD pair in the current cycle, and receive the traffic information of the corresponding OD pair in the current cycle sent by the destination node of each OD pair. In this way, the network controller can obtain the traffic information of the corresponding OD pair in the current cycle from the destination node of each OD pair. In other words, the network controller can obtain the first measurement information from the destination node of each OD pair.

[0012] In combination with the above-mentioned first aspect, in a possible implementation method, obtaining the first measurement information corresponding to the current period includes: sending fourth indication information to the source node of each OD pair in at least one OD pair, and receiving fifth indication information from the source node of each OD pair, respectively. The fourth indication information is used to instruct the source node to set a measurement tag for the corresponding OD pair, the measurement tag is used to instruct the destination node in the corresponding OD pair to measure the traffic information of the corresponding OD pair in the current period, and the fifth indication information is used to indicate the traffic information of the corresponding OD pair in the current period.

[0013] That is to say, the network controller can instruct the source node of each OD pair to set a measurement tag for the corresponding OD pair, so that the destination node of each OD pair in the above at least one OD pair can trigger the measurement of the traffic information of the corresponding OD pair in the current period based on the measurement tag, and receive the traffic information of the corresponding OD pair in the current period sent by the source node of each OD pair. In this way, the network controller can indirectly obtain the traffic information of the corresponding OD pair in the current period from the destination node of each OD pair through the source node of each OD pair. That is to say, the network controller can indirectly obtain the first measurement information from the destination node of each OD pair through the source node of each OD pair.

[0014] In combination with the above first aspect, in a possible implementation manner, at least one OD pair is determined based on the first traffic matrix and the target accuracy range.

[0015] That is to say, the network controller determines the at least one OD pair based on the first traffic matrix and the target accuracy range, rather than arbitrarily selecting the at least one OD pair, so that the first measurement information including the traffic information measured at least one OD pair can be more in line with the accuracy requirements, and thus the second traffic matrix determined based on the first measurement information can also be more in line with the accuracy requirements.

[0016] In combination with the above-mentioned first aspect, in a possible implementation method, the method described in the embodiment of the present application also includes: determining the amount of information of each OD pair in the first traffic matrix, and inputting the amount of information and the target accuracy range of each OD pair in the first traffic matrix into the OD pair prediction model to obtain at least one OD pair, wherein the amount of information is used to characterize the traffic of the OD pair indicated by the first traffic matrix, or the amount of information is used to characterize the error between the traffic of the OD pair indicated by the first traffic matrix and the traffic of the OD pair indicated by the fourth traffic matrix corresponding to the previous period.

[0017] That is, the network controller can determine the flow-related information (i.e., the amount of information) of each OD pair in the first flow matrix, and use the information amount and target accuracy range of each OD pair determined above as input to the prediction model, and determine at least one OD pair through the prediction model. Since the algorithm in the prediction model is relatively complex and precise, the accuracy of the at least one OD pair determined by the prediction model is relatively high, so that the accuracy of the first measurement information including the measured flow information of the at least one OD pair is relatively high, and thus the second flow matrix determined based on the first measurement information can also better meet the accuracy requirements.

[0018] In combination with the above-mentioned first aspect, in a possible implementation method, the method described in the embodiment of the present application also includes: determining the amount of information of each OD pair in the first traffic matrix, and determining multiple OD pairs ranked in the top N in terms of information amount among the OD pairs of the first traffic matrix as at least one OD pair, wherein N corresponds to the target accuracy range, N is a positive integer, and the amount of information is used to characterize the traffic of the OD pairs indicated by the first traffic matrix, or the amount of information is used to characterize the error between the traffic of the OD pairs indicated by the first traffic matrix and the traffic of the OD pairs indicated by the fourth traffic matrix corresponding to the previous cycle.

[0019] That is to say, the network controller can determine the traffic-related information (i.e., the amount of information) of each OD pair in the first traffic matrix, and based on the amount of information, determine the multiple OD pairs ranked in the top N as at least one OD pair, and the multiple OD pairs ranked in the top N in terms of information amount have a greater impact on the accuracy of the traffic matrix. In this way, the network controller does not need to rely on the prediction model to determine at least one OD pair that has a greater impact on the accuracy of the traffic matrix, so that the subsequent network controller can better improve the accuracy of the traffic matrix based on the traffic information of at least one OD pair.

[0020] In combination with the above-mentioned first aspect, in a possible implementation method, the method described in the embodiment of the present application also includes: when the error between the second flow matrix and the fourth flow matrix corresponding to the previous period is not within the target accuracy range, obtaining the second measurement information corresponding to the current period, processing the second flow matrix based on the second measurement information, obtaining the third flow matrix corresponding to the current period, and when the error between the third flow matrix and the fourth flow matrix corresponding to the previous period is within the target accuracy range, sending fourth indication information to the flow matrix demand node, the second measurement information includes the flow information of other OD pairs except at least one OD pair in the measured first flow matrix; the fourth indication information is used to indicate the third flow matrix.

[0021] That is to say, the network controller can adjust the traffic matrix in real time based on the information obtained from real-time measurements (for example, the second measurement information, etc.). Specifically, the network controller can process the traffic matrix determined in the previous cycle (for example, the second traffic matrix) multiple times through iterative processing to continuously improve the accuracy of the traffic matrix until the error between the traffic matrix obtained in the current iteration (for example, the third traffic matrix) and the fourth traffic matrix corresponding to the previous cycle is within the target accuracy range, and send the traffic matrix obtained in the current iteration to the traffic matrix demand node. This not only improves the accuracy of the traffic matrix obtained by the traffic matrix demand node, but also ensures that the accuracy of the traffic matrix obtained by the traffic matrix demand node is within a reasonable range.

[0022] In combination with the above-mentioned first aspect, in a possible implementation method, the method described in the embodiment of the present application also includes: determining other OD pairs based on at least one of the first flow matrix, the target accuracy range, or the error between the second flow matrix and the fourth flow matrix flow corresponding to the previous cycle.

[0023] That is to say, the network controller determines the above-mentioned other OD pairs based on at least one of the first traffic matrix, the target accuracy range, or the error between the second traffic matrix and the fourth traffic matrix traffic corresponding to the previous cycle, rather than arbitrarily selecting other OD pairs, so that the second measurement information including the traffic information measured of other OD pairs can be more in line with the accuracy requirements, and thus the third traffic matrix determined based on the second measurement information can also be more in line with the accuracy requirements.

[0024] In a second aspect, a communication device is provided for implementing the various methods described above. The communication device may be the network controller described in the first aspect, or any implementation of the first aspect, or a device comprising the network controller, or a device included in the network controller, such as a chip. The communication device includes modules, units, or means corresponding to the methods described above. The modules, units, or means may be implemented in hardware, software, or by executing corresponding software implementations in hardware. The hardware or software includes one or more modules or units corresponding to the functions described above.

[0025] In some possible designs, the communication device may include a processing module and a transceiver module. The transceiver module, also referred to as a transceiver unit, is configured to implement the transmitting and / or receiving functions described in any of the above aspects and any possible implementations thereof. The transceiver module may be comprised of a transceiver circuit, a transceiver, a transceiver, or a communication interface. The processing module may be configured to implement the processing functions described in any of the above aspects and any possible implementations thereof.

[0026] In some possible designs, the transceiver module includes a sending module and a receiving module, which are respectively used to implement the sending and receiving functions in any of the above aspects and any possible implementation methods.

[0027] In a third aspect, a communication device is provided, comprising: a processor and a memory; the memory is configured to store computer instructions, and when the processor executes the instructions, the communication device performs any of the methods described above. The communication device may be the network controller described in the first aspect or any implementation of the first aspect, or a device including the network controller, or a device included in the network controller, such as a chip.

[0028] In a fourth aspect, a communication device is provided, comprising: a processor and a communication interface; the communication interface is configured to communicate with a module external to the communication device; and the processor is configured to execute a computer program or instruction to cause the communication device to perform the method of any of the aforementioned aspects. The communication device may be the network controller of the first aspect or any implementation of the first aspect, or a device including the network controller, or a device, such as a chip, included in the network controller.

[0029] In a fifth aspect, a communication device is provided, comprising: at least one processor; the processor is configured to execute a computer program or instruction stored in a memory, so that the communication device performs the method of any of the above aspects. The memory may be coupled to the processor, or may be independent of the processor. The communication device may be the network controller of the first aspect or any implementation of the first aspect, or a device including the network controller, or a device included in the network controller, such as a chip.

[0030] In a sixth aspect, a computer-readable storage medium is provided, which stores a computer program or instruction. When the computer program or instruction is run on a communication device, the communication device can execute any of the above aspects or any of its implementation methods.

[0031] In a seventh aspect, a computer program product comprising instructions is provided, which, when executed on a communication device, enables the communication device to execute any of the above aspects or any of its implementation methods.

[0032] In an eighth aspect, a communication device is provided (for example, the communication device may be a chip or a chip system), which includes a processor for implementing the functions involved in any of the above aspects or any of its implementation methods.

[0033] In some possible designs, the communication device includes a memory for storing necessary program instructions and data.

[0034] In some possible designs, when the device is a chip system, it can be composed of a chip or include a chip and other discrete devices.

[0035] It can be understood that when the communication device provided in any one of the second to fifth aspects is a chip, the above-mentioned sending action / function can be understood as output, and the above-mentioned receiving action / function can be understood as input.

[0036] In a ninth aspect, an online real-time measurement method is provided, which includes the method of the first aspect or any implementation thereof.

[0037] Among them, the technical effects brought about by any implementation method of the second to ninth aspects can refer to the technical effects brought about by the corresponding implementation method of the first aspect, and will not be repeated here.

[0038] It should be noted that various possible implementations of any of the above aspects can be combined under the premise that the solutions are not contradictory. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 This is a schematic diagram of the existence probability of OD pairs of different traffic in a network provided by an embodiment of the present application;

[0040] Figure 2 This is a schematic diagram of a node structure of an IP network provided in an embodiment of the present application;

[0041] Figure 3 This is a schematic diagram of a flow change curve of an OD pair provided in an embodiment of the present application;

[0042] Figure 4 This is a schematic diagram of a node structure of another IP network provided in an embodiment of the present application;

[0043] Figure 5 This is a schematic diagram of the structure of a communication system provided by an embodiment of the present application;

[0044] Figure 6 is a structural diagram of another communication system provided in an embodiment of the present application;

[0045] Figure 7 This is a schematic structural diagram of a communication device provided in an embodiment of the present application;

[0046] Figure 8 This is a flow chart of an online real-time measurement method provided by an embodiment of the present application;

[0047] Figure 9 This is a flow chart of another online real-time measurement method provided by an embodiment of the present application;

[0048] Figure 10 This is a flow chart of another online real-time measurement method provided by an embodiment of the present application;

[0049] Figure 11 This is a flow chart of another online real-time measurement method provided by an embodiment of the present application;

[0050] Figure 12 This is a flow chart of another online real-time measurement method provided by an embodiment of the present application;

[0051] Figure 13 It is a structural diagram of another communication device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0052] To facilitate understanding of the technical solutions provided by the embodiments of this application, a brief introduction to the relevant technologies of this application is first given. The brief introduction is as follows:

[0053] 1. Internet Protocol (IP) network

[0054] An IP network refers to a network that communicates based on IP. An IP network has the characteristics of high dynamics, strong volatility, and a large number of OD pairs.

[0055] The large dynamics refers to the large difference in traffic volume between two typical data flows in the communication network. For example, the two types of data flows can be called "elephant flow" and "mouse flow". Figure 1 A schematic diagram showing the probability of data flow of different traffic in the network is shown, Figure 1As shown, the horizontal axis represents the flow value, in gigabits per second (Gbps), and the vertical axis represents the probability. For the data flow of the source node, the probability of the data flow of the source node with a flow rate less than 1 megabit per second (Mbps) is above 50%, that is, the probability of the data flow of the source node with a flow rate less than 1Mbps is higher, that is, the probability of "rat flow" is higher. At the same time, Figure 1 The figure shows that there is a data flow with a source node of 2Gbps in the network, which is called "elephant flow", while the peak flow of the system is 10Gbps. For the data flow of the destination node, the probability of the data flow with a flow of less than 1Mbps is more than 50%, which means that the probability of the data flow with a flow of less than 1Mbps is higher, that is, the probability of "rat flow" is higher. At the same time, Figure 1 It shows that there is a data flow with a destination node whose traffic reaches 2 Gbps in the network, namely, an "elephant flow".

[0056] It can be seen that in this network, the traffic of most data flows is low, that is, the traffic of most data flows is less than 1Mbps, and there are very few data flows with larger traffic. However, once there is a data flow with a traffic greater than 2Gbps (i.e., "elephant flow") in the network, the "elephant flow" will occupy a large amount of transmission bandwidth.

[0057] Strong volatility means that the sum of the traffic values ​​of multiple data volumes in the communication network varies greatly at different times. For example, the sum of the traffic values ​​of multiple data volumes between 19:00 and 22:00 is 8Gbps, while the sum of the traffic values ​​of multiple data volumes between 2:00 and 4:00 is 10Mbps.

[0058] A large number of OD pairs means that a large number of OD pairs exist in the communication network, e.g. Figure 2 A schematic diagram of a node structure of an IP network is shown. Figure 2 As shown, the IP network includes about 100 nodes, and any two nodes in the IP network can form an OD pair, which increases the number of OD pairs in the IP network.

[0059] It should be pointed out that since the current IP network needs to meet the quality of service (QoS) requirements of various types of services, the Internet Engineering Task Force (IETF) usually uses network telemetry technology to provide IP networks with network insights and data required for automated management. For example, network telemetry technology can include remote data generation, collection, association, and consumption, and other technologies. The embodiments of the present application do not impose any restrictions on this.

[0060] 2. Traffic Matrix

[0061] The traffic matrix is ​​used to represent the traffic information of OD pairs in the communication network. The traffic matrix has the characteristics of low rank, temporal correlation, and spatial correlation.

[0062] The low-rank property refers to the low rank of the traffic matrix. In other words, the traffic matrix has fewer rows or columns that provide valid information. Based on this property, the network controller can infer a complete traffic matrix that meets the accuracy requirements of various applications using less measurement data.

[0063] For example, the low-rank property of the traffic matrix can be expressed by the following formula 1:

[0064]

[0065] Among them, X n×m represents a flow matrix with n rows and m columns, where n is the number of OD pairs and m is the number of acquisition time points.

[0066] Time correlation can also be called periodicity, which means that the traffic matrix changes periodically. Since the traffic information of each OD pair involved in the traffic matrix changes periodically, the traffic matrix also changes periodically.

[0067] For example, the flow change of OD pair is used as an example to illustrate. Figure 3 The flow rate variation curve diagram of OD pair is shown. Figure 3 The OD versus flow rate curve within a week is shown. Figure 3 As shown, the horizontal axis represents time, and the vertical axis represents traffic flow (in Mbps). The traffic change curve for OD pair 1 on Monday is roughly the same as the traffic change curve for OD pair 1 on any other day of the week. In other words, the traffic change curve for OD pair 1 is roughly the same every day. In this example, the traffic information for OD pair 1 changes periodically, with a period of one day (i.e., 24 hours).

[0068] Spatial correlation means that within the same time period, the change curves of multiple flow matrices that are geographically close to each other are roughly the same. Since the change curves of multiple OD pairs that are geographically close to each other are roughly the same, the change curves of multiple flow matrices that are geographically close to each other are roughly the same.

[0069] For example, the flow change of OD pair is used as an example to illustrate. Figure 3 The flow change curves of two OD pairs (i.e., OD pair 1 and OD pair 2) that are geographically close to each other within a week are also shown. Figure 3 As shown, the flow rate variation curve of OD pair 1 within one week is roughly the same as the flow rate variation curve of OD pair 2 within one week.

[0070] As mentioned above regarding "IP networks," IP networks are characterized by high dynamics, strong volatility, and a large number of OD pairs. Therefore, IP networks need to have high resilience to counteract the interference (e.g., internal and external interference) caused by these characteristics, thereby ensuring the continuity of network services as much as possible. However, current protocols stipulate that evaluating network resilience or setting target values ​​for network resilience requires relying on the network's traffic matrix, and the traffic matrix can also provide a key data foundation for congestion analysis, performance diagnosis, network anomaly analysis, network migration analysis, and network security analysis. In summary, the traffic matrix plays a vital role in IP networks.

[0071] Currently, measurement methods are commonly used to determine the traffic matrix. Specifically, the network controller can obtain actual measurement information through the NetFlow / NetStream protocol. The actual measurement information includes network configuration, routing tables, forwarding tables, and NetFlow / NetStream log information. The network controller uses this actual measurement information to analyze and obtain the ingress and egress information of each data flow for all OD pairs in the network, as well as the transmission start and end times and data volume of each data flow for all OD pairs. Based on the ingress and egress information of all OD pairs, as well as the transmission time and data volume of all OD pairs, the network controller calculates the traffic flow of each OD pair in the network and determines the traffic matrix based on the traffic flow of each OD pair.

[0072] However, the above measurement method requires support from specific protocol features, such as NetFlow or NetStream protocol support. Since such features are basically not enabled in actual networks, the network controller cannot obtain key information to determine the traffic matrix (for example, network configuration, routing table, forwarding table, and network flow log information, etc.), which makes the above measurement method highly restrictive and less applicable, and thus it is rarely used in actual applications.

[0073] Furthermore, the above measurement method relies on a large amount of measurement information. Since the network controller needs to obtain the actual measurement information with a large amount of interactive information, and the network controller uses the actual measurement information to determine the ingress and egress information of each data flow of all OD pairs in the network, as well as the transmission start and end time and data flow of each data flow of all OD pairs, the process is relatively complex. Therefore, the above measurement method is only applicable to small-scale networks. Figure 4 Another schematic diagram of the node structure of an IP network is shown in FIG. Figure 4 As shown in the figure, in a smaller network, there are fewer nodes and fewer OD pairs, so the amount of interactive information for determining the traffic matrix is ​​less and the process complexity is lower.

[0074] However, the number of nodes in the network is usually large, and the number of OD pairs in the network is large, that is, the network scale is large. For a larger network, the amount of interactive information required for the network controller to obtain actual measurement information becomes larger, and the process of the network controller determining the ingress information and egress information of each data flow of all OD pairs in the network, as well as the transmission start and end time and data flow of each data flow of all OD pairs through actual measurement information becomes more complicated, resulting in the network controller taking a longer time to determine the ingress information and egress information of each data flow of all OD pairs in the network, as well as the transmission start and end time and data flow of each data flow of all OD pairs, which in turn leads to lower efficiency in determining the traffic matrix.

[0075] In order to improve the efficiency of determining the traffic matrix, an inference method can be used to determine the traffic matrix. Specifically, the above-mentioned inference method is taken as an example of an online real-time measurement method of the traffic matrix of a soft defined network (SDN) based on the open flow framework: the ternary content addressable memory (TCAM) in the switch can determine the traffic matrix through network information, wherein the network information includes routing information, network topology feature information, and the total input / output traffic information (also called load information) of all nodes in the network, that is, the TCAM in the switch can effectively aggregate the traffic information of some nodes, and infer the traffic matrix based on the traffic information of some nodes. In addition, the TCAM in the switch measures the traffic information of the OD pairs with larger traffic to provide the traffic information of some OD pairs for the service. Specifically, the traffic matrix can be inferred by the following formula 2:

[0076] Y=AX n×m Formula 2

[0077] Among them, Y includes the flow information of each source node in the network and the flow information of each destination node in the network, and A is the routing information.

[0078] However, the above inference method can only be executed by devices deployed with dedicated hardware (for example, TCAM), and the above dedicated hardware is generally not deployed in devices in existing IP networks, resulting in the inability of devices in existing IP networks to execute the above inference method, which in turn results in the above inference method being highly restrictive and having low applicability.

[0079] Furthermore, the inferred traffic matrix is ​​not very accurate. Typically, the error between the inferred and actual traffic matrices is between 20% and 30%. This inference fails to meet the needs of practical applications and can easily lead to anomalies in services such as network resilience assessment, congestion analysis, and performance diagnosis. Furthermore, this inference method is typically based on SNMP data, but packet loss and other issues are likely to occur during the SNMP data acquisition process, resulting in missing SNMP data and further reducing the accuracy of the traffic matrix determined based on SNMP data.

[0080] Based on this, an embodiment of the present application provides an online real-time measurement method, wherein the first measurement information includes the flow information of at least one OD pair measured in the first flow matrix, that is, the first measurement information includes the flow information of at least one OD pair measured actually, so that the first measurement information has higher accuracy, and then the network controller processes the inferred flow matrix (i.e., the first flow matrix) based on the first measurement information to obtain a second flow matrix to improve the accuracy of the processed second flow matrix. However, in order to further ensure that the accuracy of the second flow matrix sent to the flow matrix demand node is within a reasonable range, the network controller can send the second flow matrix to the flow matrix demand node when the error between the second flow matrix and the flow matrix measured in the previous cycle is within the target accuracy range. This not only improves the accuracy of the flow matrix obtained by the flow matrix demand node, but also ensures that the accuracy of the flow matrix obtained by the flow matrix demand node is within a reasonable range.

[0081] Furthermore, in an embodiment of the present application, the network controller does not need to measure all the traffic information in the network, but only needs to obtain information such as routing information, SNMP data of multiple nodes, target accuracy range, network topology information, network status information, and first measurement information. Since the traffic matrix itself has characteristics such as low rank characteristics, time correlation, and spatial correlation, the network controller can determine the traffic matrix that meets the accuracy requirements through a small amount of information (i.e., routing information, SNMP data of multiple nodes, target accuracy range, network topology information, network status information, and first measurement information). This can reduce the amount of information measured when meeting the accuracy requirements of the traffic matrix. And since information such as routing information, SNMP data of multiple nodes, target accuracy range, network topology information, network status information, and first measurement information is real-time, that is, the information related to determining the traffic matrix recorded in the embodiment of the present application is real-time, so the traffic matrix that meets the accuracy requirements determined based on the above information is also real-time, so if the above information related to determining the traffic matrix changes, the traffic matrix output by the network controller will also be adaptively adjusted in real time.

[0082] In addition, the online real-time measurement method provided in the embodiment of the present application can be executed by a network controller in an existing communication network without being restricted to devices deployed with dedicated hardware, thereby reducing the restrictiveness of the online real-time measurement method provided in the embodiment of the present application and improving the applicability of the online real-time measurement method provided in the embodiment of the present application.

[0083] The technical solutions in the embodiments of the present application will be described below in conjunction with the drawings in the embodiments of the present application.

[0084] In order to facilitate understanding of the embodiments of the present application, the following explanations are made before introducing the embodiments of the present application.

[0085] 1. In the embodiments of the present application, for ease of description, when numbering, the numbers may be consecutively numbered starting from 1, consecutively numbered starting from 0, or starting from any parameter. It should be understood that the above are all settings for the convenience of describing the technical solution 2 provided in the embodiments of the present application, and are not intended to limit the scope of the embodiments of the present application.

[0086] 2. In the embodiment of the present application, "indication" may include direct indication and indirect indication, and may also include explicit indication and implicit indication. The information indicated by a certain information (such as the first indication information below) is called information to be indicated. In the specific implementation process, there are many ways to indicate the information to be indicated, such as but not limited to, the information to be indicated can be directly indicated, such as the information to be indicated itself or the index of the information to be indicated. The information to be indicated can also be indirectly indicated by indicating other information, wherein the other information and the information to be indicated have an association relationship. A part of the information to be indicated can also be indicated, while the other parts of the information to be indicated are known or agreed in advance. For example, the indication of specific information can also be achieved by means of the arrangement order of each piece of information agreed in advance (such as specified in the protocol), thereby reducing the indication overhead to a certain extent. At the same time, the common parts of each piece of information can also be identified and indicated uniformly to reduce the indication overhead caused by indicating the same information separately.

[0087] In addition, the specific indication method can also be various existing indication methods, such as but not limited to the above-mentioned indication methods and various combinations thereof. The specific details of the various indication methods can be referred to the prior art and will not be repeated herein. As can be seen from the above, for example, when it is necessary to indicate multiple information of the same type, there may be a situation where the indication methods for different information are different. In the specific implementation process, the required indication method can be selected according to specific needs. The embodiment of the present application does not limit the selected indication method. In this way, the indication method involved in the embodiment of the present application should be understood to cover various methods that can enable the party to be indicated to obtain the information to be indicated.

[0088] It should be understood that the information to be indicated can be sent as a whole or divided into multiple sub-information and sent separately, and the sending period and / or sending time of these sub-information can be the same or different. The specific sending method is not limited in the embodiments of this application. Among them, the sending period and / or sending time of these sub-information can be predefined, for example, predefined according to a protocol, or can be configured by the transmitting device by sending configuration information to the receiving device. Among them, the configuration information can include, for example, but not limited to, radio resource control signaling.

[0089] 3. "Pre-definition" or "pre-configuration" can be implemented by pre-saving corresponding codes, tables or other methods that can be used to indicate relevant information in a device (for example, a network controller). The embodiments of the present application do not limit the specific implementation method. Among them, "saving" can mean saving in one or more memories. One or more memories can be set separately or integrated in an encoder or decoder, a processor, or a communication device. One or more memories can also be partially set separately and partially integrated in a decoder, a processor, or a communication device. The type of memory can be any form of storage medium, which is not limited by the embodiments of the present application.

[0090] 4. The “protocol” involved in the embodiments of the present application may refer to a standard protocol in the field of communications, for example, it may include a long term evolution (LTE) protocol, a new radio (NR) protocol, and related protocols used in future communication systems. The embodiments of the present application are not limited to this.

[0091] 5. In the embodiments of the present application, descriptions such as "when...", "in the case of...", "if" and "if" all mean that the device (for example, the network controller) will take corresponding actions under certain objective circumstances. It does not limit the time, nor does it require the device (for example, the network controller) to make a judgment action when implementing it, nor does it mean that there are other limitations.

[0092] 6. In the description of this application, unless otherwise specified, " / " indicates that the objects associated with each other are in an "or" relationship. For example, A / B can represent A or B. "And / or" in the embodiments of this application is a kind of association relationship that describes the associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. A and B can be singular or plural. In addition, in the description of the embodiments of this application, unless otherwise specified, "multiple" refers to two or more than two. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple. In addition, in order to facilitate the clear description of the technical solutions of the embodiments of this application, in the embodiments of this application, words such as "first" and "second" are used to distinguish between identical or similar items with basically the same functions and effects. Those skilled in the art will understand that words such as "first" and "second" do not limit the quantity and execution order, and words such as "first" and "second" do not necessarily limit differences. At the same time, in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or design. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a concrete way for easy understanding.

[0093] The embodiments of the present application can be applied to LTE systems or NR systems (also referred to as 5G systems), vehicle to everything (V2X) systems, LTE and NR hybrid networking systems, or device to device (D2D) systems, machine to machine (M2M) communication systems, Internet of Things (IoT) systems (such as narrowband Internet of Things (NB-IoT) systems), and other next-generation communication systems. Alternatively, the communication system may also be a non-3rd Generation Partnership Project (3GPP) communication system without limitation.

[0094] In addition, the communication architecture and business scenarios described in the embodiments of the present application are intended to more clearly illustrate the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided in the embodiments of the present application. Ordinary technicians in this field can know that with the evolution of the communication architecture and the emergence of new business scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0095] Figure 5 A possible, non-limiting system diagram is shown. Figure 5 As shown, Figure 5 The communication system 500 including the network controller 501 and the traffic matrix demand node 502 is used as an example for explanation. It should be understood that Figure 5 The number of network controllers 501 and the number of traffic matrix demand nodes 502 are only examples, and may be more or less.

[0096] In one possible implementation, the network controller 501 obtains the first traffic matrix corresponding to the current cycle and the first measurement information corresponding to the current cycle, processes the first traffic matrix based on the first measurement information, obtains the second traffic matrix corresponding to the current cycle, and sends a first indication message to the traffic matrix demand node 502 when the error between the second traffic matrix and the fourth traffic matrix corresponding to the previous cycle of the current cycle is within the target accuracy range, wherein the first traffic matrix is ​​determined based on routing information, Simple Network Management Protocol SNMP data of multiple nodes, target accuracy range, network topology information, or at least one of network status information, and the first measurement information includes the measured traffic information of at least one OD pair in the first traffic matrix; the first indication information is used to indicate the second traffic matrix, and the fourth traffic matrix is ​​determined based on the traffic information of multiple OD pairs in the previous cycle. The specific implementation of this solution and the related technical effects can be referred to the subsequent method embodiments and will not be repeated here.

[0097] In one possible implementation, the network controller in the embodiments of the present application can communicate with the traffic matrix demand node. For example, the network controller can be a switch in the network. Of course, the above is only an exemplary description of a network controller. The network controller can also be other devices, and the embodiments of the present application do not impose any limitations on this.

[0098] In one possible implementation, the traffic matrix demand node in the embodiment of the present application may be a router in the network. Of course, the above is only an exemplary description of the traffic matrix demand node, and the traffic matrix demand node may also be other devices, and the embodiment of the present application does not impose any limitation on this.

[0099] Optionally, Figure 6 Another possible, non-limiting system diagram is shown. Figure 6 As shown, the communication system 500 further includes at least one source node 503, at least one destination node 504, at least one access network device 505, at least one transmission node 506, and at least one data center 507, wherein the traffic matrix demand node 502 may include at least one of the at least one source node 503 and the at least one destination node 504. It should be understood that Figure 6 The number of network controllers 501, the number of traffic matrix demand nodes 502, the number of source nodes 503, the number of destination nodes 504, and the number of at least one access network device 505 are only examples, and may be more or less.

[0100] In one possible implementation, the network controller in the embodiment of the present application can also communicate with the source node or the destination node to achieve the purpose of controlling the source node or the destination node, for example, controlling the source node to set a measurement tag for the OD pair, and for example, controlling the destination node to measure the flow information of the corresponding OD pair. The source node can communicate with the destination node through a transmission node, and the embodiment of the present application does not impose any restrictions on the number of transmission nodes between the source node and the destination node. The source node in the embodiment of the present application can also communicate with the access network device to obtain flow information, and the destination node in the embodiment of the present application can also communicate with the data center to transmit flow information.

[0101] Exemplarily, the access network device may include an evolved base station (NodeB or eNB or e-NodeB, evolutionaryNode B) in a long term evolution (LTE) system or an enhanced LTE (LTE-advanced, LTE-A) system, such as a traditional macro base station eNB and a micro base station eNB in ​​a heterogeneous network scenario. Alternatively, it may include a next generation node B (gNB) in a new radio (NR) system. Alternatively, it may include a transmission reception point (TRP), a home base station (e.g., a home evolved NodeB, or home Node B, HNB), a baseband unit (BBU), a baseband pool (BBU pool), or a wireless fidelity (WiFi) access point (AP), etc. Alternatively, the access network device may include a base station in a non-terrestrial network (NTN), that is, it may be deployed on an aircraft platform or a satellite. Alternatively, the access network device may be a device that implements a base station function in IoT, such as a device that implements a base station function in drone communications, V2X, D2D, or machine to machine (M2M).

[0102] In a possible implementation, the network controller in the embodiment of the present application may also be referred to as a communication device, which may be a general device or a dedicated device, and the embodiment of the present application does not specifically limit this.

[0103] In one possible implementation, the relevant functions of the network controller in the embodiments of the present application can be implemented by a single device, or by multiple devices, or by one or more functional modules within a single device, and the embodiments of the present application do not specifically limit this. It is understood that the above functions can be network elements in hardware devices, software functions running on dedicated hardware, a combination of hardware and software, or virtualized functions instantiated on a platform (e.g., a cloud platform).

[0104] For example, the relevant functions of the network controller in the embodiment of the present application can be Figure 7 It is implemented by the communication device 710 in. Figure 7It is understood that the communication device 710 includes necessary means such as modules, units, components, circuits, or interfaces, which are appropriately configured together to implement the present solution. The communication device 710 may be Figure 6 The network controller in the device may also be a component (such as a chip) in these devices, used to implement the methods described in the following method embodiments. The communication device 710 includes one or more processors 711 and a transceiver 715. The processor 711 can be a general-purpose processor or a dedicated processor. For example, it can be a baseband processor or a central processing unit. The baseband processor can be used to process communication protocols and communication data, and the central processing unit can be used to control the communication device, execute software programs, and process data of software programs. The processor 711 is sometimes also called a processing unit, which controls the communication device. The transceiver 715 is sometimes also called a transceiver unit, a transceiver, a transceiver circuit, or a transceiver, etc., and is used to implement the transceiver function of the communication device through the antenna 716.

[0105] Optionally, in one design, the processor 711 may include a program 713 (sometimes also referred to as code or instruction), which may be executed on the processor 711 to enable the communication device 710 to perform the methods described in the following embodiments. In another possible design, the communication device 710 includes a circuit ( Figure 7 The circuit is used to implement the measurement function in the following embodiments.

[0106] Optionally, the communication device 710 may include one or more memories 712 on which a program 714 (sometimes also referred to as code or instructions) is stored. The program 714 can be executed on the processor 711 so that the communication device 710 performs the method described in the following method embodiment.

[0107] Optionally, the processor 711 and / or the memory 712 may include artificial intelligence (AI) modules 717 and 718, which are used to implement AI-related functions. The AI ​​module can be implemented through software, hardware, or a combination of software and hardware. For example, the AI ​​module may include a real-time information processing (RIC) module. For example, the AI ​​module may be a near-real-time RIC or a non-real-time RIC.

[0108] Optionally, data may be stored in the processor 711 and / or the memory 712. The processor and the memory may be provided separately or integrated together.

[0109] Optionally, the communication device 710 may further include an antenna 716 .

[0110] The following will be combined Figure 8, the online real-time measurement method provided in the embodiment of the present application is described in detail.

[0111] It should be noted that in the following embodiments of the present application, the names of the information between the various network elements, the names of the various parameters, or the names of the various information are only examples. In other embodiments, they may also be other names, and the methods provided in the embodiments of the present application are not specifically limited to this. It is understandable that in the embodiments of the present application, each network element may perform some or all of the steps in the embodiments of the present application. These steps or operations are examples, and the embodiments of the present application may also perform other operations or variations of various operations. In addition, the various steps may be performed in a different order than those presented in the embodiments of the present application, and it may not be necessary to perform all of the operations in the embodiments of the present application.

[0112] Figure 8 This is an example of the online real-time measurement method provided by the embodiment of the present application. The method is described with the network controller as the execution subject. Of course, the subject that executes the network controller action in the method can also be a device / module in the network controller, such as a chip, processor, processing unit, etc. in the network controller, and the embodiment of the present application does not specifically limit this. For example, Figure 8 , the online real-time measurement method comprises the following steps:

[0113] S801. The network controller obtains a first traffic matrix corresponding to a current period and first measurement information corresponding to the current period.

[0114] The first traffic matrix is ​​determined based on at least one of routing information, SNMP data of multiple nodes, a target accuracy range, network topology information, or network status information. The first measurement information includes measured traffic information of at least one OD pair in the first traffic matrix.

[0115] In one possible implementation, the number of OD pairs included in at least one OD pair is less than or equal to a first threshold, that is, the number of OD pairs to be measured is small, which can reduce the time required to measure the traffic information of the OD pairs as much as possible, and thus reduce the time of the entire process of outputting the traffic matrix as much as possible. That is to say, the network controller can determine the final output traffic matrix more quickly, so that the time interval between the time of the final output traffic matrix and the time of collecting the traffic information is shorter, thereby improving the real-time performance of the final output traffic matrix as much as possible, and making the reference value of the final output traffic matrix higher.

[0116] Optionally, the first threshold value may be set by the network controller according to actual network conditions. For example, the network controller sets the first threshold value to 10. Of course, the above is only an exemplary description of the first threshold value. The first threshold value may also be other values ​​(for example, 1), and the embodiments of the present application do not impose any limitation on this.

[0117] For example, the above cycle can be 10 minutes. Of course, the above is only an exemplary description of the cycle, and the cycle can also be other time periods (for example, 10 seconds), and the present embodiment does not impose any limitation on this.

[0118] S802: The network controller processes the first traffic matrix based on the first measurement information to obtain a second traffic matrix corresponding to the current period.

[0119] S803. When the error between the second traffic matrix and the fourth traffic matrix corresponding to the previous cycle of the current cycle is within the target accuracy range, the network controller sends a first indication message to the traffic matrix demand node. Correspondingly, the traffic matrix demand node receives the first indication message from the network controller.

[0120] The first indication information is used to indicate the second traffic matrix, and the fourth traffic matrix is ​​determined based on traffic information of multiple OD pairs in a previous cycle.

[0121] As mentioned above regarding the "traffic matrix", the traffic matrix changes periodically, that is, the traffic matrix in the current cycle is roughly the same as the traffic matrix in the previous cycle. In view of this, it can be seen that the actual measured traffic matrix corresponding to the previous cycle (i.e., the fourth traffic matrix) can be more consistent with the actual traffic matrix in the current cycle. If the error between the second traffic matrix and the fourth traffic matrix corresponding to the previous cycle is within the target accuracy range, it can be shown that the second traffic matrix can be more consistent with the actual traffic matrix in the current cycle, that is, the accuracy of the second traffic matrix is ​​higher. In this case, the network controller sends the second traffic matrix to the traffic matrix demand node, so that the network controller can effectively improve the accuracy of the traffic matrix output to the traffic matrix demand node.

[0122] In addition, the network controller may optionally obtain the traffic matrix sent to the traffic matrix demand node corresponding to the previous cycle from its own storage database, and send first indication information to the traffic matrix demand node if the error between the second traffic matrix and the traffic matrix sent to the traffic matrix demand node corresponding to the previous cycle is within a target accuracy range. The above-described implementation method can be applied to the situation where the network controller cannot obtain the fourth traffic matrix corresponding to the previous cycle.

[0123] In an embodiment of the present application, the first measurement information includes the measured flow information of at least one OD pair in the first flow matrix, that is, the first measurement information includes the flow information of at least one OD pair that is actually measured, so that the first measurement information has a higher accuracy. Then, the network controller processes the inferred flow matrix (i.e., the first flow matrix) based on the first measurement information to obtain a second flow matrix to improve the accuracy of the processed second flow matrix. However, in order to further ensure that the accuracy of the second flow matrix sent to the flow matrix demand node is within a reasonable range, the network controller can send the second flow matrix to the flow matrix demand node when the error between the second flow matrix and the flow matrix measured in the previous cycle is within the target accuracy range. This not only improves the accuracy of the flow matrix obtained by the flow matrix demand node, but also ensures that the accuracy of the flow matrix obtained by the flow matrix demand node is within a reasonable range.

[0124] Furthermore, in an embodiment of the present application, the network controller does not need to measure all the traffic information in the network, but only needs to obtain information such as routing information, SNMP data of multiple nodes, target accuracy range, network topology information, network status information, and first measurement information. Since the traffic matrix itself has characteristics such as low rank characteristics, time correlation, and spatial correlation, the network controller can determine the traffic matrix that meets the accuracy requirements through a small amount of information (i.e., routing information, SNMP data of multiple nodes, target accuracy range, network topology information, network status information, and first measurement information). This can reduce the amount of information measured when meeting the accuracy requirements of the traffic matrix. And since information such as routing information, SNMP data of multiple nodes, target accuracy range, network topology information, network status information, and first measurement information is real-time, that is, the information related to determining the traffic matrix recorded in the embodiment of the present application is real-time, so the traffic matrix that meets the accuracy requirements determined based on the above information is also real-time, so if the above information related to determining the traffic matrix changes, the traffic matrix output by the network controller will also be adaptively adjusted in real time.

[0125] In addition, the online real-time measurement method provided in the embodiment of the present application can be executed by a network controller in an existing communication network without being restricted to devices deployed with dedicated hardware, thereby reducing the restrictiveness of the online real-time measurement method provided in the embodiment of the present application and improving the applicability of the online real-time measurement method provided in the embodiment of the present application.

[0126] The following describes an implementation manner in which the network controller, as described in S801 above, obtains the first measurement information corresponding to the current period.

[0127] Optionally, the network controller can obtain the first measurement information corresponding to the current period in the following two ways: Method 1 is for the network controller to obtain the first measurement information corresponding to the current period from the destination node; Method 2 is for the network controller to obtain the first measurement information corresponding to the current period from the source node. Of course, the above is only an exemplary description of the implementation method for the network controller to obtain the first measurement information corresponding to the current period. The network controller can also obtain the first measurement information corresponding to the current period in other ways, and this embodiment of the application does not impose any restrictions on this.

[0128] The following is a detailed description of the above methods 1 and 2:

[0129] Method 1 is that the network controller obtains the first measurement information corresponding to the current period from the destination node. Figure 9 Another online real-time measurement method flow chart is shown in FIG. Figure 9 As shown, in the first method, the network controller may obtain the first measurement information corresponding to the current period through S901 to S902.

[0130] S901: The network controller sends second indication information to the destination node of each OD pair in at least one OD pair. Correspondingly, the destination node of the OD pair receives the second indication information from the network controller.

[0131] The second indication information is used to instruct the destination node to measure the flow information of the corresponding OD pair in the current period.

[0132] In one possible implementation, the implementation process of S901 may be: the network controller sends the second indication information to the source node of each OD pair in at least one OD pair, and accordingly, the source node of the OD pair receives the second indication information from the network controller. The source node of the OD pair sends the second indication information to the destination node of the OD pair, and accordingly, the destination node of the OD pair receives the second indication information from the source node of the OD pair. That is, in this implementation, the source node of the OD pair acts as a relay unit to transparently transmit the second indication information so that the destination node of the OD pair can receive the second indication information from the network controller.

[0133] In another possible implementation, the implementation process of S901 may be: the network controller directly sends the second indication information to the destination node of each OD pair in at least one OD pair, and the destination node of the OD pair accordingly receives the second indication information from the network controller. In other words, in this implementation, the network controller can directly communicate with the destination node of the OD pair, that is, the network controller can directly send the second indication information to the destination node of the OD pair without having to forward the second indication information through other nodes, thereby saving signaling overhead in the communication network.

[0134] Of course, the above is only an exemplary description of the implementation process of S901. The above S901 can also be implemented in other ways, and the embodiments of the present application do not impose any limitations on this.

[0135] For example, assuming that each OD pair in the network has a unique identifier, the second indication information can carry the unique identifier of the corresponding OD pair, so that after receiving the second indication information, the subsequent destination node can know the OD pair that needs to be measured based on the unique identifier of the corresponding OD pair.

[0136] Assuming that each OD pair in the network does not have a unique identifier, the second indication information can carry characteristic information of the corresponding OD pair, so that after receiving the second indication information, the subsequent destination node can identify the OD pair to be measured through the characteristic information of the OD pair.

[0137] S902 : The destination node of the OD pair sends third indication information to the network controller. Correspondingly, the network controller receives the third indication information from the destination node of each OD pair respectively.

[0138] The third indication information is used to indicate the flow information of the corresponding OD pair in the current period.

[0139] In one possible implementation, the implementation process of S901 may be as follows: the destination node of the OD pair sends the third indication information to the source node of the OD pair, and accordingly, the source node of the OD pair receives the third indication information from the destination node of the OD pair. The destination node of the OD pair sends the third indication information to the network controller, and accordingly, the network controller receives the third indication information from the destination node of each OD pair respectively. That is, in this implementation, the source node of the OD pair acts as a relay unit, transparently transmitting the third indication information so that the network controller can receive the third indication information from the destination node of the OD pair.

[0140] In another possible implementation, the implementation process of S901 may be as follows: the destination node of each OD pair in at least one OD pair may directly send the third indication information to the network controller, and accordingly, the network controller directly receives the third indication information from the destination node of each OD pair. In other words, in this implementation, the destination node of the OD pair may communicate directly with the network controller, that is, the destination node of the OD pair may directly send the third indication information to the network controller without the need for the third indication information to be relayed through other nodes, thereby saving signaling overhead in the communication network.

[0141] Of course, the above is only an exemplary description of the implementation process of S902. The above S902 can also be implemented in other ways, and the embodiments of the present application do not impose any limitations on this.

[0142] Optionally, before S902, the destination node of the OD pair may measure the flow information of the corresponding OD pair periodically. In addition, the destination node of the OD pair may report the flow information of the corresponding OD pair periodically, or may report the flow information of the corresponding OD pair based on a reporting trigger event. This embodiment of the present application does not impose any restrictions on this.

[0143] It can be understood that the network controller can instruct the destination node of each OD pair to measure the traffic information of the corresponding OD pair within the current period, and receive the traffic information of the corresponding OD pair within the current period sent by the destination node of each OD pair, so that the network controller can obtain the traffic information of the corresponding OD pair within the current period from the destination node of each OD pair, that is, the network controller can obtain the first measurement information from the destination node of each OD pair.

[0144] The second method is that the network controller obtains the first measurement information corresponding to the current cycle from the destination node. Figure 9 As shown, in the second method, the network controller may obtain the first measurement information corresponding to the current period through S903 to S904.

[0145] S903: The network controller sends fourth indication information to the source node of each OD pair in at least one OD pair. Correspondingly, the source node of the OD pair receives the fourth indication information from the network controller.

[0146] The fourth indication information is used to instruct the source node to set a measurement tag for the corresponding OD pair, and the measurement tag is used to instruct the destination node in the corresponding OD pair to measure traffic information of the corresponding OD pair in the current period.

[0147] Optionally, after S903 , the source node of the OD pair sets a measurement tag for the OD pair and sends the measurement tag set for the OD pair to the destination node of the OD pair to trigger the destination node of the OD pair to measure the traffic information of the OD pair in the current cycle.

[0148] S904 : The source node of the OD pair sends fifth indication information to the network controller. Correspondingly, the network controller receives the fifth indication information from the source node of each OD pair respectively.

[0149] The fifth indication information is used to indicate the flow information of the corresponding OD pair in the current period.

[0150] It should be pointed out that the method recorded in the above S904 refers to the source node of the OD pair informing the network controller of the fifth indication information. However, before S904, the destination node of the OD pair sends the fifth indication information to the source node of the OD pair so that the source node of the OD pair can obtain the fifth indication information.

[0151] However, optionally, the destination node of the OD pair may not send the fifth indication information to the source node of the OD pair, but directly send the fifth indication information to the network controller. That is, the destination node of the OD pair may directly inform the network controller of the fifth indication information to save signaling overhead.

[0152] In addition, in this implementation, after completing the flow information measurement of the OD pair in the current cycle, the destination node of the OD pair may delete the measurement tag set for the OD pair to prevent the measurement tag from affecting the flow information measurement in the next cycle.

[0153] It can be understood that the network controller can instruct the source node of each OD pair to set a measurement tag for the corresponding OD pair, so that the destination node of each OD pair in the above at least one OD pair can trigger the measurement of the traffic information of the corresponding OD pair in the current period based on the measurement tag, and receive the traffic information of the corresponding OD pair in the current period sent by the source node of each OD pair. In this way, the network controller can indirectly obtain the traffic information of the corresponding OD pair in the current period from the destination node of each OD pair through the source node of each OD pair, that is, the network controller can indirectly obtain the first measurement information from the destination node of each OD pair through the source node of each OD pair.

[0154] The following describes an implementation manner in which the network controller, as described in S801 above, obtains the first measurement matrix corresponding to the current cycle.

[0155] Optionally, the network controller can obtain the first measurement matrix corresponding to the current period in the following two ways: Method 3 is that the network controller obtains the first measurement matrix corresponding to the current period from other devices; Method 4 is that the network controller independently determines the first measurement matrix corresponding to the current period. Of course, the above is only an exemplary description of the implementation method of the network controller obtaining the first measurement matrix corresponding to the current period. The network controller can also obtain the first measurement matrix corresponding to the current period in other ways, and this embodiment of the application does not impose any restrictions on this.

[0156] The following is a detailed description of the above-mentioned method 3 and method 4:

[0157] The third method is that the network controller obtains the first measurement matrix corresponding to the current period from other devices. Figure 10 Another online real-time measurement method flow chart is shown in FIG. Figure 10As shown, in the third method, the network controller may obtain the first measurement matrix corresponding to the current cycle through S1001.

[0158] S1001. Other devices send sixth indication information to the network controller. Correspondingly, the network controller receives the sixth indication information from the other devices.

[0159] The sixth indication information is used to indicate the first measurement matrix corresponding to the current period.

[0160] For example, the other device may be a network management device. Of course, the above is only an exemplary description of other devices, and the embodiments of the present application do not impose any limitation on this.

[0161] The fourth method is that the network controller determines the first measurement matrix corresponding to the current cycle by itself. Figure 10 As shown, in the fourth mode, the network controller may obtain the first measurement matrix corresponding to the current cycle through S1002 to S1006.

[0162] S1002. The network controller obtains the target accuracy range and network status information from the operator server.

[0163] For example, taking the error as the normalized mean square error (NMSE), the target accuracy range can be 10% to 20%, and the target accuracy range can also be 8% to 10%. Taking the error as the mean absolute percentage error (MAPE), the target accuracy range can be 5% to 20%. Of course, the above is only an exemplary description of the target accuracy range, and the target accuracy range can also be other ranges, and the embodiments of the present application do not impose any limitations on this.

[0164] It should be noted that the above NMSE can satisfy the following formula 3:

[0165]

[0166] in, is the predicted flow value of the i-th OD pair, X i is the actual flow value of the i-th OD pair, where i is a positive integer.

[0167] For example, the network status information may be network characteristic information of an IP radio access network (RAN) or network characteristic information of an IP core. Of course, the above is merely an exemplary description of the network status information, and the network status information may also be other information, which is not limited in any way by the embodiments of the present application.

[0168] S1003: The network controller obtains network topology information from network compatible equipment (NCE).

[0169] S1004: The network controller obtains SNMP data of multiple nodes from the multiple nodes.

[0170] Optionally, the plurality of nodes may all collect SNMP data according to a sampling period. For example, the sampling period may be 10 minutes. Of course, the above is merely an exemplary description of the sampling period, and the sampling period may also be other periods, and the present application embodiment does not impose any limitation thereto.

[0171] S1005: The network controller obtains routing information from the network management device, or determines routing information according to network topology information.

[0172] S1006: The network controller inputs routing information, SNMP data of multiple nodes, target accuracy range, network topology information, and network status information into a traffic matrix inference model to determine a first traffic matrix.

[0173] Alternatively, the network controller inputs routing information, SNMP data of multiple nodes, network topology information, and network status information into a traffic matrix inference model to determine the first traffic matrix. In this case, the algorithm of the traffic matrix inference model includes a default target accuracy range.

[0174] It can be understood that since information such as routing information, SNMP data of multiple nodes, target accuracy range, network topology information, network status information, and first measurement information are real-time, that is, the information related to determining the traffic matrix recorded in the embodiments of the present application is real-time, so the traffic matrix that meets the accuracy requirements determined based on the above information is also real-time. In this way, if the above information related to determining the traffic matrix changes, the traffic matrix output by the network controller will also be adaptively adjusted in real time.

[0175] For example, the algorithm in the traffic matrix inference model can be as follows:

[0176]

[0177] In the above algorithm, please refer to formula 1 to understand the meaning of L and R. The matrices S and T c is the spatial and temporal correlation information matrix, T p Time period information matrix, Y is SNMP information, represents missing values, and ε is the upper limit of the allowed traffic matrix.

[0178] As mentioned above about "IP network", IP network is highly dynamic, that is, there are OD pairs with higher traffic and OD pairs with lower traffic in the IP network at the same time. Compared with OD pairs with lower traffic, OD pairs with higher traffic have a greater impact on the accuracy of the entire traffic matrix. In other words, different OD pairs have different impacts on the accuracy of determining the traffic matrix.

[0179] In view of this, optionally, the network controller can determine the above-mentioned at least one OD pair based on the first traffic matrix and the target accuracy range, rather than arbitrarily selecting the above-mentioned at least one OD pair, so that the first measurement information including the traffic information measured to at least one OD pair can be more in line with the accuracy requirements, and thus the second traffic matrix determined based on the first measurement information can also be more in line with the accuracy requirements.

[0180] Furthermore, optionally, the network controller may determine the at least one OD pair based on the first traffic matrix and the target accuracy range in one of the following two ways: Way five is for the network controller to determine the at least one OD pair based on the OD pair prediction model; Way six is ​​for the network controller to determine the at least one OD pair by sorting. Of course, the above is only an exemplary description of the way the network controller determines the at least one OD pair. The network controller may also determine the at least one OD pair using a greedy algorithm, and this embodiment of the application does not impose any restrictions on this.

[0181] The following is a detailed description of the above methods 5 and 6:

[0182] Method five is that the network controller determines at least one OD pair based on the OD pair prediction model. Figure 11 Another online real-time measurement method flow chart is shown in FIG. Figure 11 As shown, in the fifth mode, the implementation process of the network controller determining at least one OD pair may include the following S1101 to S1102.

[0183] S1101: The network controller determines the information volume of each OD pair in the first traffic matrix.

[0184] The information amount is used to characterize the flow of the OD pair indicated by the first flow matrix, or the information amount is used to characterize the error between the flow of the OD pair indicated by the first flow matrix and the flow of the OD pair indicated by the fourth flow matrix corresponding to the previous cycle.

[0185] In a possible implementation, if the information volume is used to characterize the traffic of the OD pairs indicated by the first traffic matrix, the implementation process of S1101 may be: the network controller obtains the information volume of each OD pair from the first traffic matrix.

[0186] In another possible implementation, if the information volume is used to characterize the error between the traffic volume of the OD pair indicated by the first traffic matrix and the traffic volume of the OD pair indicated by the fourth traffic matrix corresponding to the previous cycle, the implementation process of S1101 may be: the network controller may obtain the fourth traffic matrix corresponding to the previous cycle and obtain the historical actual traffic volume of the OD pair from the fourth traffic matrix. The network controller determines the error between the traffic volume of the OD pair indicated by the first traffic matrix and the historical actual traffic volume of the OD pair as the information volume of the OD pair.

[0187] In addition, if the network controller cannot obtain the fourth traffic matrix corresponding to the previous cycle from other devices, the amount of information can also be used to characterize the error between the traffic of the OD pairs indicated by the first traffic matrix and the traffic of the OD pairs indicated by the traffic matrix output to the traffic matrix demand node corresponding to the previous cycle.

[0188] In this case, optionally, the implementation process of S1101 may be as follows: the network controller may obtain the traffic matrix output to the traffic matrix demand node corresponding to the previous cycle from its own stored database (referred to as the fifth traffic matrix), and obtain the historical predicted traffic of the OD pair from the fifth traffic matrix. The network controller determines the error between the traffic of the OD pair indicated by the first traffic matrix and the historical predicted traffic of the OD pair as the information amount of the OD pair.

[0189] Of course, the above is only an exemplary description of the implementation process of S1101. The above S1101 can also be implemented in other ways, and the embodiments of the present application do not impose any limitations on this.

[0190] S1102: The network controller inputs the information volume and target accuracy range of each OD pair in the first traffic matrix into the OD pair prediction model to obtain at least one OD pair.

[0191] Optionally, the above prediction model can be determined by the network controller based on historical data training, or can be obtained by the network controller from other devices. The embodiments of the present application do not impose any restrictions on this.

[0192] It is understandable that the network controller can determine the flow-related information (i.e., the amount of information) of each OD pair in the first flow matrix, and use the information amount and target accuracy range of each OD pair determined above as input to the prediction model, and determine at least one OD pair through the prediction model. Since the algorithm in the prediction model is relatively complex and precise, the accuracy of the at least one OD pair determined by the prediction model is relatively high, so that the accuracy of the first measurement information including the measured flow information of the at least one OD pair is relatively high, and thus the second flow matrix determined based on the first measurement information can also better meet the accuracy requirements.

[0193] The sixth method is that the network controller determines at least one OD pair by sorting. Figure 11 As shown, in the sixth mode, the implementation process of the network controller determining at least one OD pair may include the following S1103 to S1104.

[0194] S1103: The network controller determines the information volume of each OD pair in the first traffic matrix.

[0195] The information amount is used to characterize the flow of the OD pair indicated by the first flow matrix, or the information amount is used to characterize the error between the flow of the OD pair indicated by the first flow matrix and the flow of the OD pair indicated by the fourth flow matrix corresponding to the previous cycle.

[0196] It can be understood that the above S1103 can be understood by referring to the relevant description of the above S1101, and will not be repeated here.

[0197] S1104: The network controller determines, among the OD pairs in the first traffic matrix, a plurality of OD pairs ranked in the top N in terms of information volume as at least one OD pair.

[0198] Wherein, N has a corresponding relationship with the target accuracy range, and N is a positive integer.

[0199] It can be understood that the network controller can determine the traffic-related information (i.e., the amount of information) of each OD pair in the first traffic matrix, and based on the amount of information, determine the multiple OD pairs ranked in the top N as at least one OD pair, and the multiple OD pairs ranked in the top N in terms of information amount have a greater impact on the accuracy of the traffic matrix. In this way, the network controller does not need to rely on the prediction model to determine at least one OD pair that has a greater impact on the accuracy of the traffic matrix, so that the subsequent network controller can better improve the accuracy of the traffic matrix based on the traffic information of at least one OD pair.

[0200] In addition, as can be seen from the aforementioned introduction to the "traffic matrix", the change curves of multiple OD pairs that are geographically close to each other are roughly the same. In view of this, when the network controller determines at least one OD pair, the address location of the OD pair can also be considered. For example, the distance between any two OD pairs in at least one OD pair is greater than the distance threshold, so that there is more similar redundant data in the first measurement information.

[0201] As mentioned above about Figure 8 As shown in the relevant introduction of the online real-time measurement method, Figure 8The online real-time measurement method shown records the scheme of the network controller determining the flow matrix when the error between the second flow matrix and the fourth flow matrix corresponding to the previous cycle is within the target accuracy range. However, the error between the second flow matrix and the fourth flow matrix corresponding to the previous cycle may not be within the target accuracy range. Based on this, an embodiment of the present application provides an online real-time measurement method for recording the scheme of the network controller determining the flow matrix when the error between the second flow matrix and the fourth flow matrix corresponding to the previous cycle is not within the target accuracy range. For example, Figure 12 Another online real-time measurement method flow chart is shown in FIG. Figure 12 As shown, when the error between the second flow matrix and the fourth flow matrix corresponding to the previous cycle is not within the target accuracy range, the online real-time measurement method includes the following steps:

[0202] S1201: When an error between a second traffic matrix and a fourth traffic matrix corresponding to a previous cycle is not within a target accuracy range, the network controller obtains second measurement information corresponding to a current cycle.

[0203] The second measurement information includes the measured flow information of other OD pairs except for the at least one OD pair in the first flow matrix.

[0204] Optionally, before S1201, the network controller may determine other OD pairs based on the first traffic matrix, the target accuracy range, and the error between the second traffic matrix and the fourth traffic matrix flow corresponding to the previous cycle. That is, the network controller determines the above-mentioned other OD pairs based on at least one of the first traffic matrix, the target accuracy range, or the error between the second traffic matrix and the fourth traffic matrix flow corresponding to the previous cycle, rather than arbitrarily selecting other OD pairs, so that the second measurement information including the flow information measured for the other OD pairs can better meet the accuracy requirements, and thus the third traffic matrix determined based on the second measurement information can also better meet the accuracy requirements.

[0205] Furthermore, in one possible implementation, if the network controller determines at least one OD pair based on the prediction model (i.e., the above-mentioned method five), the implementation process of the network controller determining other OD pairs can be: the network controller adjusts the parameters of the prediction model based on the error between the second flow matrix and the fourth flow matrix flow corresponding to the previous cycle to obtain a new prediction model, and determines other OD pairs based on the first flow matrix, the target accuracy range, and the new prediction model. If the target accuracy range changes, the network control can determine other OD pairs based on the real-time target accuracy range to achieve real-time adjustment of the OD pairs to be measured. The implementation process of the network controller determining other OD pairs based on the first flow matrix, the target accuracy range, and the new prediction model can be understood by referring to the description of the corresponding position above, and will not be repeated here. In another possible implementation, if the network controller determines at least one OD pair by sorting (i.e., the above-mentioned method six), the implementation process of the network controller determining other OD pairs can be: the network controller determines multiple OD pairs ranked in the top N in terms of information volume among the other OD pairs in the first flow matrix except for at least one OD pair as at least one OD pair. Regarding the implementation process of the network controller determining multiple OD pairs ranked in the top N in terms of information volume among other OD pairs except at least one OD pair in the first traffic matrix as at least one OD pair, you can refer to the description of the corresponding position above for understanding, and will not repeat it here.

[0206] Of course, the above is only an exemplary description of the implementation method of the network controller determining other OD pairs. The network controller can also determine other OD pairs in other ways, and the embodiments of the present application do not impose any limitations on this.

[0207] It should be pointed out that the network controller can dynamically adjust the OD pairs involved in the measurement information obtained during each iteration based on the actual network situation to ensure that the OD pairs involved in the measurement information can conform to the current network actual situation (for example, the current network status information, the current network topology information, and the current target accuracy range, etc.), thereby meeting the accuracy requirements of the traffic matrix of the communication network in different scenarios.

[0208] S1202: The network controller processes the second traffic matrix based on the second measurement information to obtain a third traffic matrix corresponding to the current period.

[0209] S1203. When the error between the third traffic matrix and the fourth traffic matrix corresponding to the previous cycle is within the target accuracy range, the network controller sends fourth indication information to the traffic matrix demand node. Correspondingly, the traffic matrix demand node receives the fourth indication information from the network controller.

[0210] The fourth indication information is used to indicate the third traffic matrix.

[0211] As mentioned above Figure 12 It can be seen from the method shown that the network controller can adjust the traffic matrix in real time based on the information obtained from real-time measurements (for example, the second measurement information, etc.). Specifically, the network controller can process the traffic matrix determined in the previous cycle (for example, the second traffic matrix) multiple times through iterative processing to continuously improve the accuracy of the traffic matrix until the error between the traffic matrix obtained in the current iteration (for example, the third traffic matrix) and the fourth traffic matrix corresponding to the previous cycle is within the target accuracy range, and the traffic matrix obtained in the current iteration is sent to the traffic matrix demand node. This not only improves the accuracy of the traffic matrix obtained by the traffic matrix demand node, but also ensures that the accuracy of the traffic matrix obtained by the traffic matrix demand node is within a reasonable range.

[0212] It is understandable that Figure 12 The described method can be understood by referring to the description of the corresponding position above, and will not be repeated here. In addition, optionally, when the error between the traffic matrix obtained by processing corresponding to the current cycle (for example, the second traffic matrix or the third traffic matrix) and the fourth traffic matrix corresponding to the previous cycle is within the target accuracy range, the network controller can instruct all OD pairs in the network to measure the traffic information within at least one cycle, and determine the traffic matrix (recorded as the sixth traffic matrix) based on the traffic information of all OD pairs within at least one cycle. The network controller can verify the accuracy of the traffic matrices obtained by processing corresponding to multiple cycles based on the sixth traffic matrix, and when the error between the traffic matrix obtained by processing corresponding to one cycle and the sixth traffic matrix within the cycle is not within the target accuracy range, the network controller can adaptively adjust at least one OD pair or prediction model involved in the first measurement information.

[0213] It should be pointed out that the method described above for verifying the accuracy of the traffic matrix through the traffic information of all OD pairs can also be performed periodically. For example, the network controller obtains the traffic information of all OD pairs measured in at least one cycle every day / week / month. The embodiments of the present application do not impose any restrictions on this.

[0214] In addition, it should be understood that the first traffic matrix corresponding to the current cycle, the second traffic matrix corresponding to the current cycle, and the third traffic matrix corresponding to the current cycle recorded in the embodiment of the present application can all be referred to as the first traffic matrix, the second traffic matrix, and the third traffic matrix. The fourth traffic matrix corresponding to the previous cycle and the fifth traffic matrix corresponding to the previous cycle recorded in the embodiment of the present application can all be referred to as the fourth traffic matrix and the fifth traffic matrix. The OD pairs recorded in the embodiment of the present application can also be referred to as OD flows, the source nodes recorded in the embodiment of the present application can also be referred to as ingress nodes, and the destination nodes recorded in the embodiment of the present application can also be referred to as egress nodes. The embodiment of the present application does not impose any restrictions on this.

[0215] The above mainly describes the solutions provided by the embodiments of the present application from the perspective of interaction between various network elements. Accordingly, the embodiments of the present application also provide a communication device, which is used to implement the various methods described above. The communication device can be the first terminal in the above method embodiments, or a device including the first terminal, or a component that can be used for the first terminal.

[0216] It is understandable that, in order to realize the above functions, the communication device includes hardware structures and / or software modules corresponding to the execution of each function. It should be easily appreciated by those skilled in the art that, in combination with the units and algorithm steps of each example described in the embodiments disclosed herein, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0217] In the embodiment of the present application, the communication device can be divided into functional modules according to the above method embodiment. For example, each functional module can be divided according to each function, or two or more functions can be integrated into one processing module. The above integrated modules can be implemented in the form of hardware or in the form of software functional modules. It should be understood that the division of modules in the embodiment of the present application is schematic and is a logical functional division. In actual implementation, there may be other division methods.

[0218] For example, taking the communication device as the terminal in the above method embodiment, Figure 13 1 shows a schematic structural diagram of a communication device 130. The communication device 130 includes a processing module 1301 and a transceiver module 1302. The transceiver module 1302, also called a transceiver unit, is used to implement transceiver functions, and can be, for example, a transceiver circuit, a transceiver, a transceiver, or a communication interface.

[0219] when Figure 13 When the communication device 130 is a network controller in the above embodiment:

[0220] In one possible implementation: the transceiver module 1302 obtains a first traffic matrix corresponding to the current period and first measurement information corresponding to the current period; the first traffic matrix is ​​determined based on at least one of routing information, Simple Network Management Protocol (SNMP) data of multiple nodes, a target accuracy range, network topology information, or network status information, and the first measurement information includes the measured traffic information of at least one source node-destination node OD pair in the first traffic matrix; the processing module 1301 is used to process the first traffic matrix based on the first measurement information to obtain a second traffic matrix corresponding to the current period; the transceiver module 1302 is also used to send a first indication information to the traffic matrix demand node when the error between the second traffic matrix and the fourth traffic matrix corresponding to the previous period of the current period is within the target accuracy range, the first indication information being used to indicate the second traffic matrix, and the fourth traffic matrix being determined based on the traffic information of multiple OD pairs in the previous period.

[0221] In some embodiments, the number of OD pairs included in the at least one OD pair is less than or equal to a first threshold.

[0222] In some embodiments, the transceiver module 1302 is also used to send second indication information to the destination node of each OD pair in at least one OD pair, and the second indication information is used to instruct the destination node to measure the traffic information of the corresponding OD pair within the current period; the transceiver module 1302 is also used to receive third indication information from the destination node of each OD pair, and the third indication information is used to indicate the traffic information of the corresponding OD pair within the current period.

[0223] In some embodiments, the transceiver module 1302 is further used to send fourth indication information to the source node of each OD pair in at least one OD pair, respectively, where the fourth indication information is used to instruct the source node to set a measurement tag for the corresponding OD pair, wherein the measurement tag is used to instruct the destination node in the corresponding OD pair to measure the traffic information of the corresponding OD pair in the current period; the transceiver module 1302 is further used to receive fifth indication information from the source node of each OD pair, respectively, where the fifth indication information is used to indicate the traffic information of the corresponding OD pair in the current period.

[0224] In some embodiments, at least one OD pair is determined based on the first flow matrix and the target accuracy range.

[0225] In some embodiments, the processing module 1301 is also used to determine the amount of information of each OD pair in the first traffic matrix, and the amount of information is used to characterize the traffic of the OD pair indicated by the first traffic matrix, or the amount of information is used to characterize the error between the traffic of the OD pair indicated by the first traffic matrix and the traffic of the OD pair indicated by the fourth traffic matrix corresponding to the previous cycle; the processing module 1301 is also used to input the amount of information and the target accuracy range of each OD pair in the first traffic matrix into the OD pair prediction model to obtain at least one OD pair.

[0226] In some embodiments, the processing module 1301 is also used to determine the amount of information of each OD pair in the first traffic matrix, the amount of information is used to characterize the traffic of the OD pair indicated by the first traffic matrix, or the amount of information is used to characterize the error between the traffic of the OD pair indicated by the first traffic matrix and the traffic of the OD pair indicated by the fourth traffic matrix corresponding to the previous cycle; the processing module 1301 is also used to determine the multiple OD pairs ranked in the top N in terms of information amount among the OD pairs of the first traffic matrix as at least one OD pair, where N corresponds to the target accuracy range and is a positive integer.

[0227] In some embodiments, the transceiver module 1302 is further used to obtain second measurement information corresponding to the current period when the error between the second traffic matrix and the fourth traffic matrix corresponding to the previous period is not within the target accuracy range, and the second measurement information includes the traffic information of other OD pairs except for at least one OD pair in the measured first traffic matrix; the processing module 1301 is further used to process the second traffic matrix based on the second measurement information to obtain the third traffic matrix corresponding to the current period; the transceiver module 1302 is further used to send fourth indication information to the traffic matrix demand node when the error between the third traffic matrix and the fourth traffic matrix corresponding to the previous period is within the target accuracy range, and the fourth indication information is used to indicate the third traffic matrix.

[0228] In some embodiments, the processing module 1301 is further configured to determine other OD pairs based on at least one of the first flow matrix, the target accuracy range, or the error between the second flow matrix and the fourth flow matrix flow corresponding to the previous cycle.

[0229] Among them, all relevant contents of each step involved in the above method embodiment can be referred to the functional description of the corresponding functional module and will not be repeated here.

[0230] In the embodiment of the present application, the first terminal is presented in the form of dividing various functional modules in an integrated manner. The "module" here can refer to a specific ASIC, circuit, processor and memory that executes one or more software or firmware programs, integrated logic circuit, and / or other devices that can provide the above functions. In a simple embodiment, those skilled in the art can imagine that the first terminal can be used Figure 7 The form of the communication device 710 is shown.

[0231] for example, Figure 7 The processor 711 in the communication device 710 shown can call the computer-executable instructions stored in the memory 712 to enable the communication device 710 to execute the online real-time measurement method in the above method embodiment.

[0232] Specifically, Figure 13 The functions / implementation processes of the transceiver module 1302 and the processing module 1301 can be realized by Figure 7 The processor 711 in the communication device 710 shown calls the computer execution instructions stored in the memory 712 to implement. Or, Figure 13 The function / implementation process of the processing module 1301 can be achieved by Figure 7 The processor 711 in the communication device 710 shown calls the computer execution instructions stored in the memory 712 to implement, Figure 13 The function / implementation process of the transceiver module 1302 can be achieved by Figure 7 This is implemented by the transceiver 715 in the communication device 710 shown in FIG.

[0233] Since the communication device 130 provided in the embodiment of the present application can execute the above-mentioned online real-time measurement method, the technical effects that can be obtained can refer to the above-mentioned method embodiment and will not be repeated here.

[0234] It should be understood that one or more of the above modules or units can be implemented by software, hardware, or a combination of the two. When any of the above modules or units is implemented in software, the software exists in the form of computer program instructions and is stored in a memory, and a processor can be used to execute the program instructions and implement the above method flow. The processor can be built into an SoC (system on chip) or an ASIC, or it can be an independent semiconductor chip. In addition to the core used to execute software instructions to perform calculations or processing within the processor, it can further include necessary hardware accelerators, such as field programmable gate arrays (FPGAs), PLDs (programmable logic devices), or logic circuits that implement dedicated logic operations.

[0235] When the above modules or units are implemented in hardware, the hardware can be any one or any combination of a CPU, a microprocessor, a digital signal processing (DSP) chip, a microcontroller unit (MCU), an artificial intelligence processor, an ASIC, a SoC, an FPGA, a PLD, a dedicated digital circuit, a hardware accelerator or a non-integrated discrete device, which can run the necessary software or not rely on the software to execute the above method flow.

[0236] In one possible implementation, an embodiment of the present application further provides a communication device (for example, the communication device may be a chip or a chip system), which includes a processor for implementing the method in any of the above method embodiments. In one possible design, the communication device also includes a memory. The memory is used to store necessary program instructions and data, and the processor can call the program code stored in the memory to instruct the communication device to execute the method in any of the above method embodiments. Of course, the memory may not be in the communication device. When the communication device is a chip system, it may be composed of a chip, or it may include a chip and other discrete devices, which is not specifically limited in the embodiment of the present application.

[0237] In one possible implementation, an embodiment of the present application also provides a computer-readable storage medium, which stores a computer program or instruction. When the computer program or instruction is run on a communication device, the communication device can execute any of the above-mentioned method embodiments or any of its implementation methods.

[0238] In a possible implementation, an embodiment of the present application further provides an online real-time measurement method, which includes any of the above method embodiments or any of its implementations.

[0239] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using a software program, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function according to the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website, computer, server or data center to another website, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more media that can be integrated. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a DVD), or a semiconductor medium (eg, a solid state disk (SSD)).

[0240] Although the present application is described herein in conjunction with various embodiments, in the process of implementing the claimed application, those skilled in the art may understand and implement other variations of the disclosed embodiments by reviewing the drawings, the disclosure, and the appended claims. In the claims, the word "comprising" does not exclude other components or steps, and "a" or "an" does not exclude multiple situations. A single processor or other unit may implement several functions listed in the claims. Certain measures are recorded in different dependent claims, but this does not mean that these measures cannot be combined to produce good results.

[0241] Although the present application has been described with reference to specific features and embodiments thereof, it will be apparent that various modifications and combinations may be made thereto without departing from the spirit and scope of the present application. Accordingly, this specification and the drawings are illustrative of the present application as defined by the appended claims and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, those skilled in the art may make various modifications and variations to the present application without departing from the spirit and scope of the present application. Thus, the present application is intended to encompass such modifications and variations as would fall within the scope of the claims of the present application and their equivalents.

Claims

1. An online real-time measurement method, characterized in that: Applied to a network controller, the method includes: Obtaining a first traffic matrix corresponding to a current period and first measurement information corresponding to the current period; the first traffic matrix is ​​determined based on at least one of routing information, Simple Network Management Protocol (SNMP) data of multiple nodes, a target accuracy range, network topology information, or network status information; the first measurement information includes measured traffic information of at least one source node-destination node OD pair in the first traffic matrix; Processing the first traffic matrix based on the first measurement information to obtain a second traffic matrix corresponding to the current period; When the error between the second traffic matrix and the fourth traffic matrix corresponding to the previous cycle of the current cycle is within the target accuracy range, a first indication information is sent to the traffic matrix demand node, where the first indication information is used to indicate the second traffic matrix, and the fourth traffic matrix is ​​determined based on the traffic information of multiple OD pairs in the previous cycle.

2. The method according to claim 1, characterized in that The number of OD pairs included in the at least one OD pair is less than or equal to a first threshold.

3. The method according to claim 1 or 2, characterized in that The obtaining of first measurement information corresponding to the current period includes: Sending second indication information to the destination node of each OD pair in the at least one OD pair, respectively, where the second indication information is used to instruct the destination node to measure traffic information of the corresponding OD pair within the current period; Third indication information is received respectively from the destination node of each OD pair, where the third indication information is used to indicate traffic information of the corresponding OD pair in the current period.

4. The method according to claim 1 or 2, characterized in that The obtaining of first measurement information corresponding to the current period includes: Sending fourth indication information to the source node of each OD pair in the at least one OD pair, respectively, where the fourth indication information is used to instruct the source node to set a measurement tag for the corresponding OD pair, wherein the measurement tag is used to instruct the destination node in the corresponding OD pair to measure traffic information of the corresponding OD pair in the current period; Fifth indication information is received respectively from the source node of each OD pair, where the fifth indication information is used to indicate traffic information of the corresponding OD pair in the current period.

5. The method according to any one of claims 1 to 4, characterized in that The at least one OD pair is determined based on the first traffic matrix and the target accuracy range.

6. The method according to claim 5, characterized in that The method further comprises: Determine an amount of information for each OD pair in the first traffic matrix, where the amount of information is used to characterize the traffic of the OD pair indicated by the first traffic matrix, or the amount of information is used to characterize an error between the traffic of the OD pair indicated by the first traffic matrix and the traffic of the OD pair indicated by the fourth traffic matrix corresponding to the previous period; The information amount of each OD pair in the first traffic matrix and the target accuracy range are input into the OD pair prediction model to obtain the at least one OD pair.

7. The method according to claim 5, characterized in that The method further comprises: Determine an amount of information for each OD pair in the first traffic matrix, where the amount of information is used to characterize the traffic of the OD pair indicated by the first traffic matrix, or the amount of information is used to characterize an error between the traffic of the OD pair indicated by the first traffic matrix and the traffic of the OD pair indicated by the fourth traffic matrix corresponding to the previous period; Among the OD pairs of the first traffic matrix, a plurality of OD pairs ranked in the top N in terms of information quantity are determined as the at least one OD pair, where N corresponds to the target accuracy range and is a positive integer.

8. The method according to any one of claims 1 to 7, characterized in that The method further comprises: When an error between the second flow matrix and the fourth flow matrix corresponding to the previous cycle is not within the target accuracy range, obtaining second measurement information corresponding to the current cycle, where the second measurement information includes flow information of other OD pairs measured in the first flow matrix except for the at least one OD pair; processing the second traffic matrix based on the second measurement information to obtain a third traffic matrix corresponding to the current period; When the error between the third traffic matrix and the fourth traffic matrix corresponding to the previous cycle is within the target accuracy range, fourth indication information is sent to the traffic matrix demand node, where the fourth indication information is used to indicate the third traffic matrix.

9. The method according to claim 8, characterized in that The method further comprises: The other OD pairs are determined according to at least one of the first flow matrix, the target accuracy range, or an error between the second flow matrix and the flow of the fourth flow matrix corresponding to the previous cycle.

10. A communication device, characterized in that: include: A functional unit for executing the method according to any one of claims 1 to 9; wherein the actions executed by the functional unit are implemented by hardware or the corresponding software is executed by hardware.

11. A communication device, characterized in that: The communication device includes a processor; the processor is configured to execute a computer program or instruction, or to enable the communication device to execute the method according to any one of claims 1 to 9 through a logic circuit.

12. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions or programs. When the computer instructions or programs are executed on a computer, the communication device is caused to execute the method according to any one of claims 1 to 9.

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