A traffic scheduling simulation method, device, equipment and storage medium

Abstract

The application discloses a traffic scheduling simulation method and device, equipment and a storage medium. The method comprises the following steps: obtaining a target traffic simulation model based on preset configuration parameters; introducing the target traffic into the target traffic simulation model and a target traffic processing device respectively to obtain target simulation network data and target actual network data; in the case that there is a target data deviation between the target simulation network data and the target actual network data, and the target data deviation is not within a first preset deviation range, acquiring link simulation network data of each link in the target traffic simulation model and link actual network data of each link in the target traffic processing device; determining an abnormal link from the multiple links based on the link simulation network data and the link actual network data of each link; and correcting preset configuration parameters corresponding to the abnormal link. The application can ensure that the simulation parameters configured are highly adaptable to the hardware environment of the equipment.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of vehicle-mounted Ethernet development, and in particular to a traffic scheduling simulation method and device, equipment and a storage medium. BACKGROUND

[0002] To ensure the time delay determinacy of TT (Time-Trigered) flow, the TSN (Time-Sensitive Networking) working group proposes the IEEE802.1Qbv standard, which uses time-aware shaping (TAS) and gate control list (GCL) to allocate exclusive transmission time window for the queue to which the TT flow belongs.

[0003] In the prior art, the transmission simulation of target traffic containing TT flow is generally to determine preset parameters, and to simulate the target traffic in a simulation model established based on the preset parameters, so as to obtain a simulation result of the target traffic in the simulation model; and to generate a gate control list based on the preset parameters and configure it into a hardware device to verify the target traffic, so as to obtain a hardware verification result. In the case that the hardware verification result and the simulation result are deviated, the deviation can generally be eliminated by randomly and repeatedly adjusting the preset parameters, but the random and repeated adjustment of the preset parameters has the problems of inaccurate parameter adjustment and low parameter adjustment efficiency. SUMMARY

[0004] To solve the above problems, the present application discloses a traffic scheduling simulation method, device, equipment and storage medium, which obtains a target traffic simulation model through preset configuration parameters, and imports the target traffic into the target traffic simulation model and a target traffic processing device respectively, to obtain target simulation network data of the target traffic in the target traffic simulation model and target actual network data of the target traffic in the target traffic processing device; when there is a target data deviation between the target simulation network data and the target actual network data and the target data deviation is not within a first preset deviation range, link simulation network data of each link in the target traffic simulation model and link actual network data of each link in the target traffic processing device are obtained, so as to determine an abnormal link and analyze the abnormal link, thereby correcting the preset configuration parameters. By comparing and analyzing the target simulation network data of the target traffic in the target traffic simulation model and the target actual network data of the target traffic in the target traffic processing device, the abnormal link is determined, and the corresponding preset configuration parameters are adjusted based on the abnormal link, so as to improve the adjustment efficiency of the preset configuration parameters, and make the preset configuration parameters and the simulation model highly compatible with the hardware environment of the device.

[0005] To achieve the above object, the application provides a flow scheduling simulation method, which comprises the following steps:

[0006] configuring a preset flow simulation model based on preset configuration parameters to obtain a target flow simulation model; the target flow simulation model comprises a plurality of links, and the preset configuration parameters represent the gating information of each link in the target flow simulation model;

[0007] introducing the target flow into the target flow simulation model and a target flow processing device respectively to obtain target simulation network data corresponding to the target flow simulation model and target actual network data corresponding to the target flow processing device;

[0008] when the target simulation network data and the target actual network data have a target data deviation and the target data deviation is not within a first preset deviation range, obtaining link simulation network data of each link in the target flow simulation model and link actual network data of each link in the target flow processing device;

[0009] determining an abnormal link from the plurality of links based on the link simulation network data of each link and the link actual network data of each link; the link data deviation between the link simulation network data of the abnormal link and the link actual network data of the abnormal link is not within a second preset deviation range;

[0010] correcting the preset configuration parameters corresponding to the abnormal link.

[0011] In some embodiments, the method further comprises:

[0012] obtaining the flow transmission period of a plurality of preset flows, the flow size of the plurality of preset flows, and the flow priority of the plurality of preset flows;

[0013] configuring the plurality of preset flows based on the flow transmission period of the plurality of preset flows, the flow size of the plurality of preset flows, and the flow priority of the plurality of preset flows to obtain the target flow.

[0014] In some embodiments, the preset configuration parameters comprise the network structure of a flow transmission network, the network routing information of the flow transmission network, the target delay of the flow transmission network, the expected network data of the flow transmission network, and the transmission configuration information of the plurality of links; the flow transmission network is formed based on the plurality of links;

[0015] The configuration of the preset flow simulation model based on the preset configuration parameters to obtain the target flow simulation model comprises:

[0016] configure the preset traffic simulation model based on the network structure of the traffic transmission network, the network routing information of the traffic transmission network, the target latency of the traffic transmission network, the expected network data of the traffic transmission network, and the transmission configuration information of the plurality of links, to obtain the target traffic simulation model; the preset traffic simulation model matches the traffic transmission network.

[0017] In some embodiments, the preset configuration parameters further include a buffer size of the target traffic processing device and a port memory of the target traffic processing device.

[0018] The method further includes:

[0019] configuring the preset traffic simulation model based on the buffer size of the target traffic processing device and the port memory of the target traffic processing device, to obtain the target traffic simulation model.

[0020] In some embodiments, the correcting the preset configuration parameters corresponding to the abnormal link includes:

[0021] obtaining the link actual network data and the link simulation network data corresponding to the target traffic in the abnormal link;

[0022] correcting the network structure of the traffic transmission network, the network routing information of the traffic transmission network, the target latency of the traffic transmission network, the expected network data of the traffic transmission network, and the transmission configuration information of the plurality of links based on the link actual network data and the link simulation network data.

[0023] In some embodiments, the correcting the network structure of the traffic transmission network, the network routing information of the traffic transmission network, the target latency of the traffic transmission network, the expected network data of the traffic transmission network, and the transmission configuration information of the plurality of links based on the link actual network data and the link simulation network data includes:

[0024] determining a current parameter to be corrected; the current parameter to be corrected is any one of the network structure of the traffic transmission network, the network routing information of the traffic transmission network, the target latency of the traffic transmission network, the expected network data of the traffic transmission network, and the transmission configuration information of the plurality of links;

[0025] correcting the current parameter to be corrected to obtain a target correction parameter;

[0026] configuring the preset traffic simulation model based on the target correction parameter to obtain a corrected simulation model;

[0027] Importing the target traffic into the simulation model to be corrected to obtain simulation network data to be corrected corresponding to the simulation model to be corrected;

[0028] When the current data deviation between the simulated network data to be corrected and the target actual network data is smaller than the target data deviation, updating the target correction parameter to the current parameter to be corrected;

[0029] Repeating the steps of: determining the current parameter to be corrected until the data deviation between the simulated network data to be corrected and the target actual network data is less than the target data deviation, and updating the target correction parameter to the current parameter to be corrected; until the data deviation between the current data deviation and the previous data deviation corresponding to the previous cycle is less than the first data deviation;

[0030] It is determined that the correction of the current parameter to be corrected is completed, and a correction result of the current parameter to be corrected is obtained.

[0031] In some embodiments, the method further comprises:

[0032] Obtaining the preset configuration parameters;

[0033] Generate a target gating list based on the preset configuration parameters, and import the target gating list into a file to generate a target file;

[0034] Acquire a preset protocol and a file format of the target file; the preset protocol is used to guide the configuration of the target file into the target traffic processing device;

[0035] If the file format of the target file meets the format requirement of the preset protocol, configuring the target file into the target traffic processing device;

[0036] In the case that the file format of the target file does not meet the format requirement of the preset protocol, the file format of the target file is converted, and the converted target file is configured in the target traffic processing device.

[0037] The present application also provides a traffic scheduling simulation device, which includes:

[0038] A target traffic simulation model determination module is configured to configure a preset traffic simulation model based on preset configuration parameters to obtain a target traffic simulation model; the target traffic simulation model includes multiple links, and the preset configuration parameters represent gating information of each link in the target traffic simulation model;

[0039] An overall data obtaining module is configured to direct the target traffic into the target traffic simulation model and the target traffic processing device respectively, to obtain target simulation network data corresponding to the target traffic simulation model and target actual network data corresponding to the target traffic processing device;

[0040] A link data obtaining module is configured to, in a case where there is a target data deviation between the target simulation network data and the target actual network data, and the target data deviation is not within a first preset deviation range, obtain link simulation network data of each link in the target traffic simulation model and link actual network data of each link in the target traffic processing device;

[0041] An abnormal link determining module is configured to determine an abnormal link from the multiple links based on the link simulation network data of each link and the link actual network data of each link; a link data deviation between the link simulation network data of the abnormal link and the link actual network data of the abnormal link is not within a second preset deviation range;

[0042] A preset configuration parameter correcting module is configured to correct a preset configuration parameter corresponding to the abnormal link.

[0043] The application further provides an electronic device, which comprises a processor and a memory, the memory storing at least one instruction or at least one program, the at least one instruction or the at least one program being loaded and executed by the processor to implement the traffic scheduling simulation method.

[0044] The application further provides a computer readable storage medium, which stores computer executable instructions, the computer executable instructions being executed by a processor to implement the traffic scheduling simulation method.

[0045] The application has the following advantages:

[0046] The embodiment of the present specification obtains a target traffic simulation model by presetting configuration parameters, and imports the target traffic into the target traffic simulation model and a target traffic processing device respectively to obtain target simulation network data of the target traffic in the target traffic simulation model and target actual network data of the target traffic in the target traffic processing device; when there is a target data deviation between the target simulation network data and the target actual network data and the target data deviation is not within a first preset deviation range, link simulation network data of each link of the target traffic in the target traffic simulation model and link actual network data of each link of the target traffic in the target traffic processing device are obtained, so as to determine an abnormal link and analyze the abnormal link, thereby correcting the preset configuration parameters. By comparing and analyzing the target simulation network data of the target traffic in the target traffic simulation model and the target actual network data of the target traffic in the target traffic processing device, the abnormal link is determined, and the corresponding preset configuration parameters are adjusted based on the abnormal link, so as to improve the adjustment efficiency of the preset configuration parameters, and make the preset configuration parameters and the simulation model highly adapt to the hardware environment of the device. BRIEF DESCRIPTION OF DRAWINGS

[0047] In order to more clearly illustrate the traffic scheduling simulation method, device, equipment and storage medium provided in the present application, the drawings required in the embodiments of the present application will be briefly introduced as follows. Obviously, the drawings described below are only some embodiments described in the present application, and other drawings can be obtained according to these drawings without creative labor for those skilled in the art.

[0048] Figure 1 is a flowchart of a traffic scheduling simulation method provided by an embodiment of the present application;

[0049] Figure 2 is a flowchart of a target traffic processing device configuration method provided by an embodiment of the present application;

[0050] Figure 3 is a flowchart of a preset configuration parameter correction method provided by an embodiment of the present application;

[0051] Figure 4 is a structural diagram of a traffic scheduling simulation device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0052] In order to enable a person skilled in the art to better understand the technical solutions in the present application, the technical solutions in the embodiments of the present application will be clearly and completely described in the following with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all the embodiments. Based on the embodiments of the present application, all other embodiments obtained by a person skilled in the art without creative labor should be within the scope of protection of the present application.

[0053] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily describe a specific order or sequence. It should be understood that the information thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or server including a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0054] Currently, the exclusive transmission time window is mainly allocated to the queue to which the TT flow belongs by using time-aware shaping and gating list. In the prior art, the transmission simulation of the target traffic including the TT flow is generally to determine preset parameters, and to simulate the target traffic in a simulation model established based on the preset parameters, so as to obtain a simulation result of the target traffic in the simulation model. Meanwhile, the hardware verification of the target traffic is performed by generating a gating list based on the preset parameters and configuring the gating list into a hardware device, so as to obtain a hardware verification result. In the case that the hardware verification result and the simulation result are deviated, the deviation can be eliminated by randomly and repeatedly adjusting the preset parameters. However, the random and repeated adjustment of the preset parameters has the problems of inaccurate parameter adjustment and low parameter adjustment efficiency.

[0055] Please refer to Figure 1 , which is a flowchart of a traffic scheduling simulation method provided by an embodiment of the present application. The specification provides the method operation steps as described in the embodiments or flowcharts. The order of steps listed in the embodiments is only one of the many execution orders of the steps, and does not represent the only execution order. The traffic scheduling simulation method can be executed according to the method order shown in the embodiments or the drawings. Specifically, as shown in Figure 1 , the method can include the following steps:

[0056] S101: configure a preset traffic simulation model based on preset configuration parameters to obtain a target traffic simulation model; the target traffic simulation model includes a plurality of links, and the preset configuration parameters represent gating information of each link in the target traffic simulation model;

[0057] In this embodiment, the preset configuration parameters can include a preset scheduling algorithm and a preset scheduling strategy. The preset scheduling algorithm can include Satisfiability Modulo Theories (SMT), integer linear programming (ILP), and heuristic algorithm. The preset scheduling strategy can include FIFO (First In First Out) and RR (Round Robin). In addition, the preset configuration parameters can also include network structure of a traffic transmission network, network routing information of the traffic transmission network, target delay of the traffic transmission network, expected network data of the traffic transmission network, configuration information of each link, and buffer size of a target traffic processing device and port memory of the target traffic processing device. The target traffic simulation model can be obtained by configuring the preset traffic simulation model based on the above-mentioned preset configuration parameters, wherein the target traffic simulation model includes a plurality of links for target traffic transmission, and the gating information of each link is determined based on the preset configuration parameters, and the traffic transmission network is formed based on the plurality of links.

[0058] In some example embodiments, the method further includes:

[0059] obtaining traffic transmission periods of a plurality of preset traffics, traffic sizes of the plurality of preset traffics, and traffic priorities of the plurality of preset traffics;

[0060] configuring the plurality of preset traffics based on the traffic transmission periods of the plurality of preset traffics, the traffic sizes of the plurality of preset traffics, and the traffic priorities of the plurality of preset traffics to obtain the target traffic.

[0061] In the above exemplary embodiments, specifically, first, traffic information of a plurality of preset traffics is acquired, the traffic information including traffic transmission periods, traffic sizes, and traffic priorities of the plurality of preset traffics, and according to the traffic information, the plurality of preset traffics configured are determined as the target traffics. The traffic transmission periods of the plurality of preset traffics can be the same or different, the traffic sizes can be the same or different, and the traffic priorities can be the same or different. For example, the number of preset traffics is 3, including a TT frame (time-triggered data flow) with a type of 0x88d7 and a highest priority, an RC frame (Rate-constrained data flow) with a type of 0x0888 and a second priority, and a BE frame (Best-effort data flow) with a type of 0x0800 and a lowest priority.

[0062] By acquiring traffic information of a plurality of traffics and determining target traffics based on the traffic information, rationality of selection of the target traffics can be ensured, and influences of other traffics can be excluded, so as to ensure simulation of target traffics required by a user and improve accuracy of traffic scheduling simulation.

[0063] In some exemplary embodiments, the preset configuration parameters include a network structure of the traffic transmission network, network routing information of the traffic transmission network, a target delay of the traffic transmission network, expected network data of the traffic transmission network, and transmission configuration information of the plurality of links; and the traffic transmission network is formed based on the plurality of links.

[0064] The configuring, based on the preset configuration parameters, of the preset traffic simulation model to obtain the target traffic simulation model includes:

[0065] The configuring, based on the network structure of the traffic transmission network, the network routing information of the traffic transmission network, the target delay of the traffic transmission network, the expected network data of the traffic transmission network, and the transmission configuration information of the plurality of links, of the preset traffic simulation model to obtain the target traffic simulation model; and the preset traffic simulation model is matched with the traffic transmission network.

[0066] In the above exemplary embodiments, specifically, the traffic transmission network is formed by a plurality of links, the network structure of the traffic transmission network represents a network topology path formed by the plurality of links when the target traffics are transmitted; the network routing information is path information for guiding the target traffics to be forwarded; the target delay represents an ideal delay of the traffic transmission network expected by a user, and the target delay can be 0; the expected network data can include a sending phase of the target traffics, representing a sending time of the target traffics; and the transmission configuration information of the plurality of links can include clock synchronization information and gate switch information, representing rule information followed by the target traffics in a transmission process.

[0067] By acquiring the network routing information of the traffic transmission network, the target delay of the traffic transmission network, the expected network data of the traffic transmission network, and the transmission configuration information of the plurality of links, it is ensured that the influence of various parameter factors on the simulation can be fully considered, and the inaccuracy of the simulation result caused by considering only a single factor is avoided, thereby improving the accuracy of the preset configuration parameters.

[0068] In some example embodiments, the preset configuration parameters further include a buffer size of the target traffic processing device and a port memory of the target traffic processing device.

[0069] The method further includes:

[0070] Based on the buffer size of the target traffic processing device and the port memory of the target traffic processing device, the preset traffic simulation model is configured to obtain the target traffic simulation model.

[0071] In the above example embodiments, specifically, the target traffic processing device includes a switch, the buffer in the target traffic processing device represents bandwidth information, and the occurrence of packet loss caused by congestion due to burst traffic can be prevented, and the acquisition of the buffer size can ensure that target traffic is reduced or avoided from packet loss during transmission; the port memory represents the data exchange capability of the target traffic processing device, and the port memory can include a flash memory (Flash) and a random access memory (RAM). The buffer size and the port memory vary with the model and application scenario of the switch.

[0072] By taking the buffer size of the target traffic processing device and the port memory of the target traffic processing device as part of the preset configuration parameters, the parameter characteristics of the hardware device are fully considered, thereby reducing or even avoiding packet loss and delay phenomena of the target traffic during transmission, so that the adaptability of the simulation result to the hardware device environment when the simulation is performed based on the preset configuration parameters can be improved, and the transmission effect is ensured.

[0073] S103: The target traffic is respectively introduced into the target traffic simulation model and the target traffic processing device to obtain target simulation network data corresponding to the target traffic simulation model and target actual network data corresponding to the target traffic processing device.

[0074] In this embodiment, the target traffic is introduced into the target traffic simulation model to obtain target simulation network data of the target traffic in the target traffic simulation model, and the target simulation network data represents the transmission characteristics of the target traffic simulation model; the target traffic is introduced into the target traffic processing device to obtain target actual network data of the target traffic in the target traffic processing device, and the target actual network data represents the transmission characteristics of the target traffic processing device.

[0075] Specifically, the target traffic enters a target traffic simulation model and a target traffic processing device respectively, and is transmitted in the target traffic simulation model and the target traffic processing device according to preset configuration parameters, so that target simulation network data and target actual network data can be obtained. The target simulation network data can include expected delay and expected jitter of the target traffic, and the target actual network data can include actual delay and actual jitter of the target traffic. It should be noted that the target simulation network data used in the embodiments of the present application is the expected delay of the target traffic, and the target actual network data is the actual delay of the target traffic.

[0076] In some example embodiments, referring to Figure 2 which is a flowchart of a target traffic processing device configuration method provided by the embodiments of the present application. As shown in Figure 2 the method further includes:

[0077] S201: obtaining the preset configuration parameters;

[0078] Specifically, the preset configuration parameters include network structure of a traffic transmission network, network routing information of the traffic transmission network, target delay of the traffic transmission network, expected network data of the traffic transmission network, and transmission configuration information of a plurality of links, and further include buffer size of the target traffic processing device and port memory of the target traffic processing device.

[0079] S203: generating a target gating list based on the preset configuration parameters, and importing the target gating list into a file to generate a target file;

[0080] Specifically, based on the network structure of the traffic transmission network, the network routing information of the traffic transmission network, the target delay of the traffic transmission network, the expected network data of the traffic transmission network, the transmission configuration information of the plurality of links, the buffer size of the target traffic processing device, and the port memory of the target traffic processing device, the number of queues required for target traffic transmission is analyzed, and the on-off state of each queue gate at different times is analyzed, so that the target gating list is generated based on the number of queues and the on-off state of each queue gate at different times. The transmission process of the target traffic in the target traffic processing device is controlled through the above target gating list, that is, the target traffic is transmitted based on the designed target gating list, and different traffic priorities in the target traffic enter different queues for transmission.

[0081] S205: obtaining a preset protocol and a file format of the target file; the preset protocol is used to guide configuration of the target file into the target traffic processing device;

[0082] Specifically, the preset protocol can include an IEEE 802.1QCC (Quantized Communication Channel) protocol, which is a network management configuration protocol in TSN and is used to optimize real-time transmission by quantizing network resources such as bandwidth, delay, jitter, and packet loss rate. The QCC defines file format requirements for a gating list when the gating list is delivered to a target traffic processing device.

[0083] S207: In a case where the file format of the target file meets the format requirements of the preset protocol, the target file is configured into the target traffic processing device;

[0084] Specifically, the preset protocol can include one or more file format requirements. If the preset protocol includes one file format requirement, the file format of the target file meets the above-mentioned one file format requirement. Or, if the preset protocol includes multiple file format requirements, the file format of the target file meets any one of the multiple file format requirements. In this case, the target file can be configured and delivered to the target traffic processing device based on the preset protocol, so that the target traffic processing device transmits target traffic according to the target file and the requirements of the preset protocol.

[0085] S209: In a case where the file format of the target file does not meet the format requirements of the preset protocol, the file format of the target file is converted, and the converted target file is configured into the target traffic processing device.

[0086] Specifically, if the file format of the target file is not one or more file formats included in the preset protocol, the file format of the target file is converted to ensure that the file format of the target file meets the requirements of the preset protocol, so that the target file is successfully delivered to the target traffic processing device.

[0087] The target gating list is solved by the preset configuration parameter, and the target gating list is converted into a file form that meets the preset protocol, so as to be imported into the target traffic processing device, thereby improving the matching degree among the target gating list, the preset protocol, and the target traffic processing device.

[0088] S105: In a case where the target data deviation is not within the first preset deviation range, link simulation network data of each link in the target traffic simulation model and link actual network data of each link in the target traffic processing device are obtained.

[0089] In the embodiment, firstly, it is judged whether the target simulation network data and the target actual network data exist deviation; if the deviation exists, the target data deviation between the target simulation network data and the target actual network data is calculated and compared with the first preset deviation range; if the target data deviation is in the first preset deviation range, it is indicated that the preset configuration parameter meets the requirement of the target traffic processing device, that is, the preset configuration parameter is the final configuration parameter; if the target data deviation is not in the first preset deviation range, it is indicated that the preset configuration parameter does not meet the requirement of the target traffic processing device, at this time, the link is located, that is, the link simulation network data of each link in the target traffic simulation model and the link actual network data of each link in the target traffic processing device are acquired, and the comparison and analysis are re-performed based on the link simulation network data and the link actual network data. It should be noted that the target traffic processing device also includes multiple links, and each link in the target traffic simulation model and each link in the target traffic processing device can be in a one-to-one correspondence relationship, and the target simulation network data is composed of a target traffic sending time, a sum of link simulation network data of multiple links and a device processing time, wherein the target traffic sending time is a time required for sending the first bit from the device output port to the last bit, the link simulation data of each link is a time required for the target traffic to be transmitted on the link, and the device processing time is a time required for the target traffic to enter the device input port to the device output port. For example, the target simulation network data is 1ms, the target actual network data is 2ms, the first preset deviation range is 0-0.6ms, the target simulation network data and the target actual network data exist deviation, and the deviation value is 1ms, which is not in the preset deviation range, indicating that the preset configuration parameter at this time does not meet the requirement of the target traffic processing device; the link simulation network data and the link actual network data of each link are acquired, for example, the number of links is 3, the link simulation network data and the link actual network data corresponding to the first link are respectively 0.2ms and 0.25ms, the link simulation network data and the link actual network data corresponding to the second link are respectively 0.2ms and 0.3ms, and the link simulation network data and the link actual network data corresponding to the third link are respectively 0.2ms and 0.28ms.

[0090] S107: determining an abnormal link from the multiple links based on the link simulation network data of each link and the link actual network data of each link; a link data deviation between the link simulation network data of the abnormal link and the link actual network data of the abnormal link is not in a second preset deviation range;

[0091] In this embodiment, firstly, it is judged whether the link simulation network data of each link deviates from the link actual network data of each link. If there is deviation, the link data deviation between the link simulation network data of each link and the link actual network data of each link is calculated and compared with the second preset deviation range. If the link data deviation is within the second preset deviation range, it is indicated that the link is normal. If the link data deviation is not within the second preset deviation range, it is indicated that the link is abnormal, and the corresponding link is determined as an abnormal link. For example, the number of links is 3, and the second preset deviation range is 0 to 30% of the link actual network data. The link simulation network data and the link actual network data of the first link are 0.2 ms and 0.25 ms respectively, the second preset deviation range of the first link is 0-0.075 ms, the link data deviation of the first link is 0.05 ms, and the link is normal within the second preset deviation range. The link simulation network data and the link actual network data of the second link are 0.2 ms and 0.3 ms respectively, the second preset deviation range of the second link is 0-0.09 ms, the link data deviation of the second link is 0.1 ms, and the link is abnormal out of the second preset deviation range. The link simulation network data and the link actual network data of the third link are 0.2 ms and 0.28 ms respectively, the second preset deviation range of the third link is 0-0.084 ms, the link data deviation of the third link is 0.08 ms, and the link is normal within the second preset deviation range. Thus, the second link is determined as an abnormal link.

[0092] It should be noted that the first preset deviation range and the second preset deviation range can be the same or different.

[0093] S109: correcting the preset configuration parameter corresponding to the abnormal link.

[0094] In this embodiment, the preset configuration parameter corresponding to the abnormal link is acquired, and then the corresponding preset configuration parameter is corrected.

[0095] In some example embodiments, the correction of the preset configuration parameter corresponding to the abnormal link comprises:

[0096] The link actual network data and the link simulation network data corresponding to the target traffic in the abnormal link are acquired.

[0097] Based on the link actual network data and the link simulation network data, the network structure of the traffic transmission network, the network routing information of the traffic transmission network, the target delay of the traffic transmission network, the expected network data of the traffic transmission network, and the transmission configuration information of the plurality of links are corrected.

[0098] In the above exemplary embodiments, the link actual network data and the link simulation network data corresponding to the target traffic in the abnormal link are obtained, so that the deviation of the link actual network data and the link simulation network data in the abnormal link can be determined, and the plurality of parameters are corrected according to the deviation, that is, the network structure of the traffic transmission network, the network routing information of the traffic transmission network, the target delay of the traffic transmission network, the expected network data of the traffic transmission network, and the transmission configuration information of the plurality of links are corrected.

[0099] The beneficial effects are that by comparing and analyzing the link actual network data and the link simulation network data corresponding to the target traffic in the abnormal link, the data deviation can be determined, so that one or more parameters in the preset configuration parameters can be corrected accordingly, the accuracy and efficiency of the abnormal link positioning are improved, the subsequent preset configuration parameter correction is provided with reference, and the preset configuration parameter correction is highly adapted to the device hardware environment.

[0100] In some exemplary embodiments, please refer to Figure 3 which is a flowchart of a preset configuration parameter correction method provided by the embodiments of the present application. Specifically, as shown in Figure 3 based on the link actual network data and the link simulation network data, the network structure of the traffic transmission network, the network routing information of the traffic transmission network, the target delay of the traffic transmission network, the expected network data of the traffic transmission network, and the transmission configuration information of the plurality of links include:

[0101] S301: determining a current parameter to be corrected; the current parameter to be corrected is any one of the network structure of the traffic transmission network, the network routing information of the traffic transmission network, the target delay of the traffic transmission network, the expected network data of the traffic transmission network, and the transmission configuration information of the plurality of links;

[0102] Specifically, any one of the network structure of the traffic transmission network, the network routing information of the traffic transmission network, the target delay of the traffic transmission network, the expected network data of the traffic transmission network, and the transmission configuration information of the plurality of links is corrected by using the control variable method, and any one is selected as the parameter to be corrected, and the other parameters remain unchanged.

[0103] S303: performing parameter correction on the current parameter to be corrected to obtain a target correction parameter;

[0104] Specifically, when the current to-be-modified parameter is a network structure of the traffic transmission network, the first network structure can be changed to the second network structure to obtain the target modified parameter, the first network structure being an initial network structure; when the current to-be-modified parameter is network routing information of the traffic transmission network, the first network routing information can be changed to the second network routing information to obtain the target modified parameter, the first network routing information being initial network routing information; when the current to-be-modified parameter is a target delay of the traffic transmission network, the target delay can be increased or decreased to obtain the target modified parameter; when the current to-be-modified parameter is expected network data of the traffic transmission network, the expected network data can be increased or decreased to obtain the target modified parameter; when the current to-be-modified parameter is transmission configuration information of a plurality of links, the first transmission configuration information can be changed to the second transmission configuration information to obtain the target modified parameter, the first transmission configuration information being the transmission configuration information.

[0105] S305: Configure the preset traffic simulation model based on the target modified parameter to obtain a to-be-modified simulation model.

[0106] Specifically, the current to-be-modified parameter and other parameters that are not changed are collectively used as target modified parameters, so that the to-be-modified simulation model is reconfigured based on the target modified parameters. For example, when the to-be-modified parameter is a network structure of the traffic transmission network, the network structure of the traffic transmission network is changed to a second network structure, and the network routing information of the traffic transmission network, the target delay of the traffic transmission network, the expected network data of the traffic transmission network, the transmission configuration information of a plurality of links, and the second network structure are collectively determined as target modified parameters, so that the modified simulation model is configured.

[0107] S307: Introduce the target traffic into the to-be-modified simulation model to obtain to-be-modified simulation network data corresponding to the to-be-modified simulation model.

[0108] S309: When a current data deviation between the to-be-modified simulation network data and the target actual network data is less than the target data deviation, the target modified parameter is updated to the current to-be-modified parameter.

[0109] Specifically, the target traffic is introduced into the to-be-corrected simulation model to obtain to-be-corrected simulation network data. If a data deviation between the to-be-corrected simulation network data and the target actual network data is less than a target data deviation before the uncorrected parameter is modified, it is indicated that the current to-be-corrected parameter meets the correction requirement, and then the target correction parameter is updated to the current to-be-corrected parameter. For example, after the network structure of the traffic transmission network is changed to the second network structure, the to-be-corrected simulation network data is 1.5 ms, the target actual network data is 2 ms, the target data deviation is 1 ms, and the first preset deviation range is 0-0.6 ms. At this time, the current data deviation between the to-be-corrected simulation network data and the target actual network data is 0.5 ms, which is less than the target data deviation and in the first preset deviation range, indicating that the change of the network structure of the traffic transmission network is effective. At this time, the target correction parameter includes the network routing information of the traffic transmission network, the target time delay of the traffic transmission network, the expected network data of the traffic transmission network, the transmission configuration information of the plurality of links, and the changed network structure of the traffic transmission network.

[0110] S311: In a case where the number of cycles is greater than 1, it is judged whether a data deviation between the current data deviation and a previous data deviation corresponding to a previous cycle is less than a first data deviation. If yes, the correction is ended. If no, step S301 is returned to continue execution.

[0111] Specifically, if the current data deviation between the to-be-corrected simulation network data obtained by simulation based on the current to-be-corrected parameter and the target actual network data is not within the first preset deviation range, but is reduced compared with the target data deviation, it indicates that the current to-be-corrected parameter has a positive effect on the transmission of the target traffic, and then the current to-be-corrected parameter is continuously adjusted until the data deviation between the current data deviation and the last data deviation corresponding to the last cycle is less than the first data deviation. That is, the adjustment of the current to-be-corrected parameter is not endless, and if the influence on the current data deviation after adjustment is less than the first data deviation, the current to-be-corrected parameter will not be adjusted. For example, the first data deviation is 0.1 ms, after the network structure of the traffic transmission network is changed for the first time, the to-be-corrected simulation network data is 1.3 ms, the target actual network data is 2 ms, the target data deviation is 1 ms, and the first preset deviation range is 0-0.6 ms. At this time, the current data deviation between the to-be-corrected simulation network data and the target actual network data is 0.7 ms, which is less than the target data deviation but not within the first preset deviation range, indicating that changing the network structure of the traffic transmission network is effective, but does not meet the requirements of the target traffic processing device. At this time, the network structure of the traffic transmission network is adjusted for the second time, and the to-be-corrected simulation network data obtained is 1.35 ms. At this time, the current data deviation between the to-be-corrected simulation network data and the target actual network data is 0.65 ms, which is less than the target data deviation but still not within the first preset deviation range. The difference between the current data deviation and the data deviation corresponding to the last cycle is 0.7-0.65=0.05 ms, which is less than the first data deviation, and the network structure of the traffic transmission network will not be adjusted.

[0112] S313: determining that the correction of the current to-be-corrected parameter is completed, and obtaining a correction result of the current to-be-corrected parameter.

[0113] In the above exemplary embodiments, specifically, the adjustment of the to-be-corrected parameter is not endless, and if the influence on the current data deviation after adjustment is less than the first data deviation, the current to-be-corrected parameter will not be adjusted. That is, the correction of the current to-be-corrected parameter is completed.

[0114] By correcting any one of the network structure of the traffic transmission network, the network routing information of the traffic transmission network, the target time delay of the traffic transmission network, the expected network data of the traffic transmission network, and the transmission configuration information of the plurality of links in the preset configuration parameters, the relationship between the to-be-corrected network simulation data and the target actual network data when any one parameter is corrected is analyzed to determine whether the corrected parameter meets the device requirements, and the correction is continued when it does not meet the requirements, thereby forming a closed loop system and ensuring the accuracy and effectiveness of the correction of the preset configuration parameters, and improving the adaptability of the preset configuration parameters to the hardware environment of the device.

[0115] The embodiment of the present application further provides a flow scheduling simulation device, please refer to Figure 4 which is a structural schematic diagram of a flow scheduling simulation device provided by the embodiment of the present application, and specifically as shown in Figure 4 The flow scheduling simulation device comprises:

[0116] A target flow simulation model determination module 401 is configured to configure a preset flow simulation model based on preset configuration parameters to obtain a target flow simulation model; the target flow simulation model comprises a plurality of links, and the preset configuration parameters represent the gating information of each link in the target flow simulation model.

[0117] An overall data acquisition module 403 is configured to import the target flow into the target flow simulation model and a target flow processing device respectively to obtain target simulation network data corresponding to the target flow simulation model and target actual network data corresponding to the target flow processing device.

[0118] A link data acquisition module 405 is configured to acquire link simulation network data of each link in the target flow simulation model and link actual network data of each link in the target flow processing device in a case where there is a target data deviation between the target simulation network data and the target actual network data, and the target data deviation is not within a first preset deviation range.

[0119] An abnormal link determination module 407 is configured to determine an abnormal link from the plurality of links based on the link simulation network data of each link and the link actual network data of each link; the link data deviation between the link simulation network data of the abnormal link and the link actual network data of the abnormal link is not within a second preset deviation range.

[0120] A preset configuration parameter correction module 409 is configured to correct the preset configuration parameters corresponding to the abnormal link.

[0121] In an optional embodiment, the flow scheduling simulation device further comprises:

[0122] A preset flow information acquisition module is configured to acquire the flow transmission period of a plurality of preset flows, the flow size of the plurality of preset flows, and the flow priority of the plurality of preset flows.

[0123] A target flow determination module is configured to configure the plurality of preset flows based on the flow transmission period of the plurality of preset flows, the flow size of the plurality of preset flows, and the flow priority of the plurality of preset flows to obtain the target flow.

[0124] In an optional embodiment, the flow scheduling simulation device further comprises:

[0125] The first target traffic simulation model determination module is configured to configure the preset traffic simulation model based on the network structure of the traffic transmission network, the network routing information of the traffic transmission network, the target delay of the traffic transmission network, the expected network data of the traffic transmission network, and the transmission configuration information of the plurality of links, to obtain the target traffic simulation model; the preset traffic simulation model matches the traffic transmission network.

[0126] In an optional embodiment, the traffic scheduling simulation device further comprises:

[0127] The second target traffic simulation model determination module is configured to configure the preset traffic simulation model based on the buffer size of the target traffic processing device and the port memory of the target traffic processing device, to obtain the target traffic simulation model.

[0128] In an optional embodiment, the traffic scheduling simulation device further comprises:

[0129] The first link data acquisition module is configured to acquire the link actual network data and the link simulation network data corresponding to the target traffic in the abnormal link.

[0130] The first preset configuration parameter correction module is configured to correct the network structure of the traffic transmission network, the network routing information of the traffic transmission network, the target delay of the traffic transmission network, the expected network data of the traffic transmission network, and the transmission configuration information of the plurality of links based on the link actual network data and the link simulation network data.

[0131] In an optional embodiment, the traffic scheduling simulation device further comprises:

[0132] The current parameter to be corrected determination module is configured to determine a current parameter to be corrected; the current parameter to be corrected is any one of the network structure of the traffic transmission network, the network routing information of the traffic transmission network, the target delay of the traffic transmission network, the expected network data of the traffic transmission network, and the transmission configuration information of the plurality of links.

[0133] The target correction parameter determination module is configured to perform parameter correction on the current parameter to be corrected to obtain a target correction parameter.

[0134] The simulation model to be corrected determination module is configured to configure the preset traffic simulation model based on the target correction parameter to obtain a simulation model to be corrected.

[0135] The simulation network data to be corrected determining module is configured to import the target traffic into the simulation model to be corrected to obtain simulation network data to be corrected corresponding to the simulation model to be corrected.

[0136] The target correction parameter updating module is configured to update the target correction parameter to the current target correction parameter when the current data deviation between the simulation network data to be corrected and the target actual network data is less than the target data deviation.

[0137] The repeating execution module is configured to repeatedly execute the steps of determining the current target correction parameter until the data deviation between the current data deviation and a previous data deviation corresponding to a previous cycle is less than a first data deviation, wherein the current target correction parameter is updated to the target correction parameter when the data deviation between the simulation network data to be corrected and the target actual network data is less than the target data deviation.

[0138] The correction result determining module is configured to determine that the correction of the current target correction parameter is completed to obtain a correction result of the current target correction parameter.

[0139] In an optional embodiment, the traffic scheduling simulation device further comprises:

[0140] The preset configuration parameter obtaining module is configured to obtain the preset configuration parameter.

[0141] The target file generating module is configured to generate a target gating list based on the preset configuration parameter and import the target gating list into a file to generate a target file.

[0142] The preset protocol and file format module is configured to obtain a preset protocol and a file format of the target file, wherein the preset protocol is used to guide the configuration of the target file into the target traffic processing device.

[0143] The first configuration module is configured to configure the target file into the target traffic processing device when the file format of the target file meets the format requirement of the preset protocol.

[0144] The second configuration module is configured to perform format conversion on the file format of the target file when the file format of the target file does not meet the format requirement of the preset protocol, and configure the converted target file into the target traffic processing device.

[0145] As to the device in the above embodiments, the specific manners in which various modules perform operations have been described in details in the embodiments of the method, and will not be described in details here.

[0146] The embodiment of the present application further provides a flow scheduling simulation electronic device, the electronic device comprising a processor and a memory, the memory storing at least one instruction or at least one program, the at least one instruction or the at least one program being loaded and executed by the processor to implement the flow scheduling simulation method according to the method embodiment.

[0147] The embodiment of the present application further provides a computer readable storage medium, the computer readable storage medium storing computer executable instructions, the computer executable instructions being executed by a processor to implement the flow scheduling simulation method according to the embodiment of the present application.

[0148] Those skilled in the art can understand that all or part of the processes in the above-mentioned method embodiments can be completed by a computer program instructing related hardware, and the computer program can be stored in a non-volatile computer readable storage medium. When the computer program is executed, the processes of the above-mentioned embodiments can be included. Any reference to memory, storage, database or other medium used in the embodiments provided by the present application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration but not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM) and memory bus dynamic RAM (RDRAM) and the like.

[0149] The above describes specific embodiments of the present specification, and other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in an order different from that in the embodiments and still achieve the desired result. In addition, the processes depicted in the drawings do not necessarily have to be implemented in the specific order shown or in a continuous sequence to achieve the desired result. In some embodiments, multi-task processing and parallel processing are possible or can be advantageous.

[0150] The various embodiments in the present application are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the difference from other embodiments. In particular, for the electronic device and computer readable storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the part of the method embodiments.

[0151] The electronic device, computer readable storage medium and method provided by the embodiments of the present application are corresponding, and therefore the electronic device and computer readable storage medium also have similar beneficial technical effects as the corresponding method. Since the beneficial technical effects of the method have been described in detail above, the beneficial technical effects of the corresponding electronic device and computer readable storage medium will not be described here.

[0152] The above only describes the embodiments of the present application and is not intended to limit the present application. Those skilled in the art can make various modifications and changes to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the scope of the claims of the present application.

Claims

1. A method of traffic scheduling simulation, characterized by, The method comprises the following steps: configuring a preset traffic simulation model based on preset configuration parameters to obtain a target traffic simulation model; the target traffic simulation model comprises a plurality of links, and the preset configuration parameters represent the gating information of each link in the target traffic simulation model; the target traffic is respectively introduced into the target traffic simulation model and a target traffic processing device to obtain target simulation network data corresponding to the target traffic simulation model and target actual network data corresponding to the target traffic processing device; when there is a target data deviation between the target simulation network data and the target actual network data, and the target data deviation is not within a first preset deviation range, link simulation network data of each link in the target traffic simulation model and link actual network data of each link in the target traffic processing device are obtained; an abnormal link is determined from the plurality of links based on the link simulation network data of each link and the link actual network data of each link; the link data deviation between the link simulation network data of the abnormal link and the link actual network data of the abnormal link is not within a second preset deviation range; the preset configuration parameters corresponding to the abnormal link are corrected.

2. The method of claim 1, wherein, The method further comprises: obtaining the traffic transmission period of a plurality of preset traffics, the traffic size of the plurality of preset traffics, and the traffic priority of the plurality of preset traffics; configuring the plurality of preset traffics based on the traffic transmission period of the plurality of preset traffics, the traffic size of the plurality of preset traffics, and the traffic priority of the plurality of preset traffics to obtain the target traffic.

3. The method of claim 1, wherein, The preset configuration parameters comprise the network structure of a traffic transmission network, the network routing information of the traffic transmission network, the target delay of the traffic transmission network, the expected network data of the traffic transmission network, and the transmission configuration information of the plurality of links; The traffic transmission network is formed based on the plurality of links. The method of configuring a preset traffic simulation model based on preset configuration parameters to obtain a target traffic simulation model comprises: configuring the preset traffic simulation model based on the network structure of the traffic transmission network, the network routing information of the traffic transmission network, the target delay of the traffic transmission network, the expected network data of the traffic transmission network, and the transmission configuration information of the plurality of links to obtain the target traffic simulation model; the preset traffic simulation model matches the traffic transmission network.

4. The method of claim 3, wherein, The preset configuration parameters further comprise the buffer size of the target traffic processing device and the port memory of the target traffic processing device. The method further comprises: configuring the preset traffic simulation model based on the buffer size of the target traffic processing device and the port memory of the target traffic processing device to obtain the target traffic simulation model.

5. The method of claim 3, wherein, The method of correcting the preset configuration parameters corresponding to the abnormal link comprises: obtaining the link actual network data and the link simulation network data corresponding to the target traffic in the abnormal link; correct the network structure of the traffic transmission network, the network routing information of the traffic transmission network, the target delay of the traffic transmission network, the expected network data of the traffic transmission network, and the transmission configuration information of the plurality of links based on the actual network data of the links and the simulated network data of the links.

6. The method of claim 5, wherein, The correcting the network structure of the traffic transmission network, the network routing information of the traffic transmission network, the target delay of the traffic transmission network, the expected network data of the traffic transmission network, and the transmission configuration information of the plurality of links based on the actual network data of the links and the simulated network data of the links includes: determining a current parameter to be corrected; the current parameter to be corrected is any one of the network structure of the traffic transmission network, the network routing information of the traffic transmission network, the target delay of the traffic transmission network, the expected network data of the traffic transmission network, and the transmission configuration information of the plurality of links; performing parameter correction on the current parameter to be corrected to obtain a target correction parameter; configuring the preset traffic simulation model based on the target correction parameter to obtain a to-be-corrected simulation model; introducing the target traffic into the to-be-corrected simulation model to obtain to-be-corrected simulation network data corresponding to the to-be-corrected simulation model; when a current data deviation between the to-be-corrected simulation network data and the target actual network data is less than the target data deviation, updating the target correction parameter to the current parameter to be corrected; repeating the steps of determining the current parameter to be corrected until the data deviation between the current data deviation and a previous data deviation corresponding to a previous cycle is less than a first data deviation; determining that the correction of the current parameter to be corrected is completed to obtain a correction result of the current parameter to be corrected.

7. The method of claim 1, wherein, The method further includes: obtaining the preset configuration parameter; generating a target gating list based on the preset configuration parameter and introducing the target gating list into a file to generate a target file; obtaining a preset protocol and a file format of the target file; the preset protocol is used to guide the configuration of the target file into the target traffic processing device; when the file format of the target file meets the format requirements of the preset protocol, configuring the target file into the target traffic processing device; when the file format of the target file does not meet the format requirements of the preset protocol, performing format conversion on the file format of the target file, and configuring the converted target file into the target traffic processing device.

8. A traffic scheduling simulation apparatus characterized by comprising: The traffic scheduling simulation device includes: a target traffic simulation model determination module configured to configure a preset traffic simulation model based on a preset configuration parameter to obtain a target traffic simulation model; the target traffic simulation model includes a plurality of links, and the preset configuration parameter represents gating information of each link in the target traffic simulation model. The whole data acquisition module is configured to direct the target traffic into the target traffic simulation model and the target traffic processing device respectively, to obtain target simulation network data corresponding to the target traffic simulation model and target actual network data corresponding to the target traffic processing device; The link data acquisition module is configured to acquire link simulation network data of each link in the target traffic simulation model and link actual network data of each link in the target traffic processing device, in a case that the target simulation network data and the target actual network data have a target data deviation and the target data deviation is not within a first preset deviation range. The abnormal link determination module is configured to determine an abnormal link from the multiple links based on the link simulation network data of each link and the link actual network data of each link, and the link data deviation between the link simulation network data of the abnormal link and the link actual network data of the abnormal link is not within a second preset deviation range. The preset configuration parameter correction module is configured to correct a preset configuration parameter corresponding to the abnormal link.

9. An electronic device, comprising: The electronic device includes a processor and a memory, the memory stores at least one instruction or at least one program, the at least one instruction or the at least one program is loaded and executed by the processor to implement the traffic scheduling simulation method of any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer executable instructions, and the computer executable instructions are executed by the processor to implement the traffic scheduling simulation method of any one of claims 1-7.

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