Topology synchronization analysis method and system for packet transport network (PTN)

Abstract

The invention relates to the technical field of communication, in particular to a topology synchronization analysis method and system for a packet transport network (PTN), and the method comprises the steps: obtaining a transmission equipment model of each node in the packet transport network, a first data transmission quantity, a state of each transmission equipment, and a topological structure diagram formed by each node; collecting network hotspot information by adopting a web crawler method; analyzing the network hotspot information and the first data transmission quantity by adopting a preset data transmission prediction model to obtain prediction information; analyzing the topological structure diagram, the transmission equipment state, the preset time transmission characteristics and the prediction information by adopting a preset topology synchronous analysis model to obtain a data transmission strategy with the shortest transmission time; and adjusting the control state of the corresponding equipment according to the data transmission strategy. According to the invention, the problem of long transmission time delay caused by transmission channel blockage due to adoption of a fixedly set packet transmission mode when sudden large-scale data transmission is encountered in a packet transmission network can be solved.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and in particular to a topology synchronization analysis method and system for a PTN packet transmission network. Background Art

[0002] As the amount of data transmission continues to increase, the delay time when transmitting data becomes longer; therefore, the technology of reducing the data transmission delay when transmitting data becomes particularly important.

[0003] Currently, in packet transmission networks, the transmission mode of packet transmission networks is usually matched and set according to the current data transmission volume. However, when the packet transmission network encounters sudden large-scale data transmission, the packet transmission network often encounters transmission congestion, resulting in data transmission delays. In addition, there may be a situation where one node receives the transmission data while the other node is still waiting, resulting in data transmission synchronization failure, which in turn causes the intermediate node with the same function to be unable to perform the next operation, further delaying the transmission time for the terminal to receive the data. In addition, when transmitting large-scale data in packets, the dynamic changes of each node in the packet transmission network and the propagation characteristics of the time synchronization signal in a complex network environment are not considered, resulting in the accumulation of time deviations that cannot be corrected in time, thereby affecting the overall performance and stability of the platform.

[0004] Therefore, the present invention provides a topology synchronization analysis method and system for a PTN packet transmission network to solve the above problems. Summary of the invention

[0005] In view of the above situation, in order to overcome the defects of the prior art, the present invention provides a topology synchronization analysis method and system for a PTN packet transmission network to solve the problem that when the packet transmission network encounters sudden large-scale data transmission, the use of a fixed packet transmission mode causes the transmission channel to be blocked, thereby causing a long transmission time delay.

[0006] In order to achieve the above object, the technical solution adopted by the present invention is:

[0007] In a first aspect, the present invention provides a method for topology synchronization analysis of a PTN packet transmission network, the method comprising: obtaining a transmission device model of each node in the packet transmission network, a topology structure diagram formed by each node, a first data transmission volume of each node, and a state of each transmission device; and obtaining a preset time transmission characteristic corresponding to each transmission device according to each transmission device model;

[0008] Using a web crawler method to collect network hotspot information with a data transmission change rate greater than a preset change rate;

[0009] The network hotspot information and the first data transmission volume are analyzed by using a preset data transmission prediction model to obtain prediction information, specifically including: obtaining trend information including a trend prediction function according to the second data transmission volume, heat value and data transmission change rate of the network hotspot information in each node; analyzing the first data transmission volume and trend information to obtain prediction information formed by the predicted transmission volume, predicted transmission position, trend information and prediction probability of each node;

[0010] A preset topology synchronization analysis model is used to analyze the topology structure diagram, transmission device status, preset time transmission characteristics corresponding to each transmission device, and prediction information to obtain a data transmission strategy with the least transmission time; the control status of the corresponding device is adjusted according to the data transmission strategy.

[0011] Preferably, the process of obtaining trend information includes:

[0012] Monitor the data change amount of network hot spot information in real time, and obtain the data transmission change rate based on the data change amount; when the data transmission change rate is greater than the preset change rate, use the network crawler method to collect the corresponding network hot spot information, and analyze the comment data of the network hot spot information to determine the heat value; estimate the diffusion rate of the network hot spot information based on the heat value and data transmission change rate of the network hot spot information; obtain the trend prediction function based on the second data transmission amount and diffusion rate of the network hot spot information; integrate the trend prediction function, heat value and network hot spot information to obtain trend information.

[0013] Preferably, the comment data of the network hot information is analyzed to determine the heat value, including: monitoring and obtaining the change amount of the comment data in each communication platform; determining the average change rate according to the change amount of the comment data in each communication platform; predicting the duration according to the type of network hot information, the keywords in the content and the correspondence between the preset mapping library; using the weighted average method to perform weighted calculation on the preset heat value corresponding to the average change rate and the duration to obtain the heat value.

[0014] Preferably, the processing procedure for obtaining the prediction information includes: forming a quantity prediction function based on the first data transmission volume, the corresponding second data transmission volume and the trend prediction function, and obtaining the predicted transmission volume based on the quantity prediction function; predicting the transmission position based on the diffusion rate in the trend prediction function; and estimating the predicted probability of transmission to the predicted transmission position based on the correspondence between the extreme value interval of the data transmission change rate and the preset mapping table; integrating the predicted transmission volume, predicted transmission position, trend information and predicted probability to obtain the prediction information.

[0015] Preferably, the processing process of the preset topology synchronization analysis model includes: determining multiple transmission devices that need to adjust their states based on the predicted transmission volume, predicted transmission position, and total transmission bandwidth in the transmission device state of each node; determining the optimal transmission bandwidth and estimated transmission time based on the preset time transmission characteristics, topological structure diagram, predicted transmission volume, and total transmission bandwidth of each transmission device; determining the sending frequency of time synchronization information based on the preset time transmission characteristics of the transmission devices corresponding to the transmitting and receiving ends; and forming a data transmission strategy with multiple transmission devices that need to adjust their states, the optimal transmission bandwidth, and the sending frequency.

[0016] Preferably, the method of determining the optimal transmission bandwidth and estimating the transmission time according to the preset time transmission characteristics, topological structure diagram, predicted transmission volume, and total transmission bandwidth of each transmission device includes:

[0017] The ant colony algorithm is used to process the predicted transmission volume and total transmission bandwidth to determine the optimal transmission bandwidth; the estimated transmission time is obtained based on the optimal transmission bandwidth, the preset time transmission characteristics of each transmission device and the transmission distance in the topological structure diagram.

[0018] Preferably, determining the sending frequency of time synchronization information according to the preset time transmission characteristics of the transmission devices corresponding to the transmitting end and the receiving end includes: according to the preset time transmission characteristics of each transmission device, periodically sending time synchronization information to the corresponding transmission device to correct the data synchronization time.

[0019] Preferably, the preset topology synchronization analysis model is constructed based on a convolutional neural network, a transmission device state and preset time transmission characteristics corresponding to each transmission device.

[0020] Preferably, after adjusting the control state of the corresponding device according to the data transmission strategy, a topology synchronization analysis method of a PTN packet transmission network also includes: after adding the pre-transmission data to the list to be transmitted, compressing the pre-transmission data using a corresponding compression method according to the decompression format in the receiving device corresponding to the transmission terminal.

[0021] In a second aspect, the present invention provides a topology synchronization analysis system for a PTN packet transmission network, the system comprising: a data acquisition module, which acquires the transmission device model of each node in the packet transmission network, the topology structure diagram formed by each node, the first data transmission volume of each node, and the status of each transmission device; and acquires the preset time transmission characteristics corresponding to each transmission device according to each transmission device model;

[0022] An information collection module, which uses a web crawler method to collect network hotspot information whose data transmission change rate is greater than a preset change rate;

[0023] The transmission volume prediction module uses a preset data transmission prediction model to analyze the network hotspot information and the first data transmission volume to obtain prediction information, specifically including: obtaining trend information including a trend prediction function according to the second data transmission volume, heat value and data transmission change rate of the network hotspot information in each node; analyzing the first data transmission volume and trend information to obtain prediction information formed by the predicted transmission volume, predicted transmission position, trend information and prediction probability of each node;

[0024] The strategy formulation module uses a preset topology synchronization analysis model to analyze the topology structure diagram, transmission device status, preset time transmission characteristics corresponding to each transmission device, and prediction information to obtain a data transmission strategy with the least transmission time; the central control module adjusts the control status of the corresponding device according to the data transmission strategy.

[0025] The beneficial effects of the present invention are:

[0026] 1. The present invention collects network hotspot information whose data transmission change rate is greater than a preset change rate through a network crawler method; then uses a preset data transmission prediction model to analyze the network hotspot information and the first data transmission volume of each node in the packet transmission network, and estimates the predicted transmission volume, predicted transmission position, and predicted probability of transmission to the predicted transmission position of each node; then uses a preset topology synchronization analysis model to analyze the topology structure diagram, the state of the transmission equipment, the preset time transmission characteristics corresponding to each transmission equipment, and the preset information to obtain a data transmission strategy with the least transmission time; finally, adjust the control state of the corresponding device according to the data transmission strategy. The present invention estimates the predicted transmission volume of each node in the above manner, and generates a control strategy in a targeted manner, which solves the problem that when the packet transmission network encounters sudden large-scale data transmission, the fixed-set packet transmission mode is used to cause the transmission channel to be blocked, thereby causing a long transmission time delay, and ensures the timeliness and stability of data transmission.

[0027] 2. The present invention adopts a method of real-time monitoring of the data change amount of network hotspot information, and real-time monitoring of the status of network hotspot information. When the data transmission change rate of network hotspot information is greater than the preset change rate, a network crawler method is used to collect data corresponding to the network hotspot information in real time; then the comment data of the network hotspot information is analyzed to determine the heat value; and according to the heat value and data transmission change rate of the network hotspot information, the diffusion rate of the network hotspot information is estimated; according to the second data transmission amount and diffusion rate of the network hotspot information, a trend prediction function is obtained; according to the first data transmission amount, the corresponding second data transmission amount and the trend prediction function, a quantity prediction function is formed, and the predicted transmission amount is obtained according to the quantity prediction function. The present invention can estimate the predicted transmission amount of node transmission data through the above method, so that the data transmission strategy obtained subsequently can control the status of the transmission equipment, and avoid the problem of transmission congestion and transmission time delay when transmitting large-scale data in the packet transmission network. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 A schematic flow chart of a topology synchronization analysis method for a PTN packet transmission network according to the present invention;

[0029] Figure 2 The present invention is a schematic module diagram of a topology synchronization analysis system for a PTN packet transmission network. DETAILED DESCRIPTION

[0030] The following will refer to the attached Figure 1 To Attachment Figure 2 The embodiments of the present invention are described in detail. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0031] A topology synchronization analysis method for a PTN packet transmission network, as shown in the attached Figure 1 As shown, it includes the following steps:

[0032] Step S11: Obtain the transmission equipment model of each node in the packet transmission network, the topological structure diagram formed by each node, the first data transmission volume of each node, and the status of each transmission equipment; and according to each transmission equipment model, obtain the preset time transmission characteristics corresponding to each transmission equipment.

[0033] Preferably, the preset time transmission characteristics corresponding to each transmission device refer to the corresponding relationship between different transmission bandwidths and transmission times corresponding to various types of transmission devices.

[0034] Preferably, the first data transmission volume refers to the data volume transmitted in real time at the time node.

[0035] Preferably, the transmission device status includes but is not limited to the maximum transmission bandwidth, the current transmission bandwidth of the transmission device, and whether the transmission device is in operation or in standby.

[0036] Preferably, the topological structure diagram formed by each node includes the topological structure relationship of each node, the name and model of each node, the transmission distance between nodes, etc.

[0037] Step S12: using a web crawler method to collect network hotspot information whose data transmission change rate is greater than a preset change rate.

[0038] Specifically, before collecting network hotspot information, the data transmission change rate of the network hotspot information will be monitored in real time; when it is monitored that the data transmission change rate of the network hotspot information is greater than the corresponding preset change rate, a web crawler method is used to collect network hotspot information with a data transmission change rate greater than the preset change rate. The network hotspot information includes but is not limited to video data, audio data, text data, and comment data.

[0039] Step S13: Use a preset data transmission prediction model to analyze the network hotspot information and the first data transmission volume to obtain prediction information, specifically including: obtaining trend information including a trend prediction function based on the second data transmission volume, heat value and data transmission change rate of the network hotspot information in each node; analyzing the first data transmission volume and trend information to obtain prediction information formed by the predicted transmission volume, predicted transmission position, trend information and predicted probability of each node.

[0040] Preferably, in a node, the first data transmission volume includes the second data transmission volume, and the second data transmission volume refers to the data transmission volume corresponding to the network hotspot information; the first data transmission volume is the total data transmission volume of the node.

[0041] Step S14: using a preset topology synchronization analysis model to analyze the topology structure diagram, the transmission device status, the preset time transmission characteristics corresponding to each transmission device, and the prediction information to obtain a data transmission strategy with the shortest transmission time.

[0042] Step S15: adjusting the control state of the corresponding device according to the data transmission strategy.

[0043] Specifically, the present invention collects network hotspot information whose data transmission change rate is greater than a preset change rate through a network crawler method; then uses a preset data transmission prediction model to analyze the network hotspot information and the first data transmission volume of each node in the packet transmission network, and estimates the predicted transmission volume, predicted transmission position, and predicted probability of transmission to the predicted transmission position of each node; then uses a preset topology synchronization analysis model to analyze the topology structure diagram, the state of the transmission device, the preset time transmission characteristics corresponding to each transmission device, and the preset information to obtain a data transmission strategy with the least transmission time; finally, adjust the control state of the corresponding device according to the data transmission strategy. The present invention estimates the predicted transmission volume of each node in the above manner, and generates a control strategy in a targeted manner, which solves the problem that when the packet transmission network encounters sudden large-scale data transmission, the fixed-set packet transmission mode is used to cause the transmission channel to be blocked, thereby causing a long transmission time delay, and ensures the timeliness and stability of data transmission.

[0044] In one embodiment of the present invention, the processing process of obtaining trend information includes: real-time monitoring of the data change amount of network hotspot information, and obtaining the data transmission change rate based on the data change amount; when the data transmission change rate is greater than the preset change rate, using a web crawler method to collect the corresponding network hotspot information, and analyzing the comment data of the network hotspot information to determine the heat value; based on the heat value and data transmission change rate of the network hotspot information, estimating the diffusion rate of the network hotspot information; based on the second data transmission amount and diffusion rate of the network hotspot information, obtaining a trend prediction function; integrating the trend prediction function, the heat value, and the network hotspot information to obtain trend information.

[0045] In this embodiment, the method of determining network hotspot information includes but is not limited to counting the forwarding volume of the same information, the number of comments and forwarding volume of network hotspot information in each communication platform, etc. The present invention adopts a method of real-time monitoring of the data change volume of network hotspot information, real-time monitoring of the status of network hotspot information, and when the data transmission change rate of network hotspot information is greater than the preset change rate, a network crawler method is used to collect data corresponding to the network hotspot information in real time; then the comment data of the network hotspot information is analyzed to determine the heat value; and according to the heat value and data transmission change rate of the network hotspot information, the diffusion rate of the network hotspot information is estimated; according to the second data transmission volume and diffusion rate of the network hotspot information, a trend prediction function is obtained; according to the first data transmission volume, the corresponding second data transmission volume and the trend prediction function, a quantity prediction function is formed, and the predicted transmission volume is obtained according to the quantity prediction function. The present invention can estimate the predicted transmission volume of node transmission data through the above method, so that the subsequent data transmission strategy can control the status of the transmission equipment, and avoid the problem of transmission congestion and transmission time delay when transmitting large-scale data in the packet transmission network.

[0046] In one embodiment of the present invention, the comment data of network hot spot information is analyzed to determine the heat value, including: monitoring and obtaining the change amount of comment data in each communication platform; determining the average change rate according to the change amount of comment data in each communication platform; predicting the duration according to the type of network hot spot information, the keywords in the content and the correspondence between the preset mapping library; using the weighted average method to perform weighted calculation on the preset heat value corresponding to the average change rate and the duration to obtain the heat value.

[0047] Preferably, a corresponding relationship is established between the type of network hot spot information, the keywords in the content and the duration, and the corresponding relationship is stored in a preset mapping library.

[0048] In this embodiment, when collecting network hot spot information through the web crawler method, comment data corresponding to the network hot spot information will be collected. When monitoring the changes in the comment data, the data volume of the comment data will be counted, and the change amount of the comment data within the set time will be determined based on the statistical results; then the change amount of the comment data in each communication platform will be averaged to obtain the average change rate.

[0049] In one embodiment of the present invention, the processing process for obtaining prediction information includes: forming a quantity prediction function based on the first data transmission volume, the corresponding second data transmission volume and the trend prediction function, and obtaining the predicted transmission volume based on the quantity prediction function; predicting the transmission position based on the diffusion rate in the trend prediction function; and estimating the predicted probability of transmission to the predicted transmission position based on the correspondence between the extreme value interval of the data transmission change rate and the preset mapping table; integrating the predicted transmission volume, predicted transmission position, trend information and predicted probability to obtain prediction information.

[0050] In this embodiment, the first data transmission volume, the second data transmission volume and the trend prediction function of the node at the same time are obtained, and the first data transmission volume and the trend prediction function are summed to obtain the quantity prediction function of the node at the time. Then, the predicted data volume at the current time is obtained according to the quantity prediction function. The corresponding transmission position is determined according to the transmission range of the diffusion rate to obtain the predicted transmission position.

[0051] In one embodiment of the present invention, the processing of the preset topology synchronization analysis model includes the following steps:

[0052] Step S21: determining a plurality of transmission devices whose states need to be adjusted according to the predicted transmission volume of each node, the predicted transmission position, and the total transmission bandwidth in the transmission device state.

[0053] Step S22: Determine the optimal transmission bandwidth and estimated transmission time according to the preset time transmission characteristics, topology diagram, predicted transmission volume, and total transmission bandwidth of each transmission device.

[0054] Step S23: Determine the sending frequency of the time synchronization information according to the preset time transmission characteristics of the transmission devices corresponding to the sending end and the receiving end.

[0055] Step S24: forming a data transmission strategy based on the multiple transmission devices whose states need to be adjusted, the optimal transmission bandwidth, and the transmission frequency.

[0056] In step S24, the data transmission strategy includes the control mode of each transmission device, the planned control time, the regulated transmission bandwidth, the specified transmission time, the sending frequency of the time synchronization information, etc.

[0057] Preferably, the sending frequency of the time synchronization information refers to the correction frequency of the time synchronization, which can be determined according to the characteristics of the transmission device, or recorded in a database and called when in use.

[0058] In this embodiment, first, the required transmission equipment is determined based on the predicted transmission volume, predicted transmission position, and total transmission bandwidth of the node, so as to subsequently adjust the status of these transmission devices so that these devices can transmit data in packets when encountering sudden large-scale data transmission, thereby sharing the pressure of the packet transmission network, thereby avoiding transmission congestion and causing transmission time delays.

[0059] In one embodiment of the present invention, the method of determining the optimal transmission bandwidth and the estimated transmission time based on the preset time transmission characteristics, the topological structure diagram, the predicted transmission volume, and the total transmission bandwidth of each transmission device includes: using an ant colony algorithm to process the predicted transmission volume and the total transmission bandwidth to determine the optimal transmission bandwidth; and obtaining the estimated transmission time based on the optimal transmission bandwidth, the preset time transmission characteristics of each transmission device, and the transmission distance in the topological structure diagram.

[0060] In this embodiment, the present invention uses an ant colony algorithm to process the predicted transmission volume and the total transmission bandwidth to determine the optimal transmission bandwidth. Compared with the conventional fixed-mode optimization method, the ant colony algorithm has self-organization and dynamic adaptability, can enhance the global search capability and robustness, and improves the accuracy and reliability of determining the optimal transmission bandwidth.

[0061] In one embodiment of the present invention, the method of determining the sending frequency of time synchronization information based on the preset time transmission characteristics of the transmission devices corresponding to the transmitting end and the receiving end includes: according to the preset time transmission characteristics of each transmission device, periodically sending time synchronization information to the corresponding transmission device to correct the data synchronization time.

[0062] In one embodiment of the present invention, the preset topology synchronization analysis model is constructed based on a convolutional neural network, a transmission device state, and preset time transmission characteristics corresponding to each transmission device.

[0063] In this embodiment, first, an initial preset topology synchronization analysis model is constructed based on a convolutional neural network; then, a large amount of training data and test data are formed by using the transmission device status and the preset time transmission characteristics corresponding to each transmission device; the initial preset topology synchronization analysis model is trained by the training data, and then the initial preset topology synchronization analysis model is tested by the test data, and when the test results meet the preset standards, the construction of the preset topology synchronization analysis model is completed.

[0064] In one embodiment of the present invention, after adjusting the control state of the corresponding device according to the data transmission strategy, a topology synchronization analysis method of a PTN packet transmission network also includes: after adding the pre-transmission data to the list to be transmitted, the pre-transmission data is compressed using a corresponding compression method according to the decompression format in the receiving device corresponding to the transmission terminal.

[0065] Before the pre-transmission data is transmitted in packets, the pre-transmission data will be compressed to reduce the amount of data transmission and improve the data transmission rate in the packet transmission network.

[0066] The present invention also provides a topology synchronization analysis system for a PTN packet transmission network, as shown in the attached Figure 2 As shown, the system includes a data acquisition module, an information collection module, a transmission volume prediction module, a strategy formulation module and a central control module; wherein the data acquisition module obtains the transmission equipment model of each node in the packet transmission network, the topological structure diagram formed by each node, the first data transmission volume of each node, and the status of each transmission equipment; and according to each transmission equipment model, obtains the preset time transmission characteristics corresponding to each transmission equipment.

[0067] The information collection module uses a web crawler method to collect network hotspot information whose data transmission change rate is greater than a preset change rate.

[0068] The transmission volume prediction module uses a preset data transmission prediction model to analyze the network hotspot information and the first data transmission volume to obtain prediction information, specifically including: obtaining trend information including a trend prediction function based on the second data transmission volume, heat value and data transmission change rate of the network hotspot information in each node; analyzing the first data transmission volume and trend information to obtain the predicted transmission volume, predicted transmission position, trend information and prediction probability of each node.

[0069] The strategy formulation module uses a preset topology synchronization analysis model to analyze the topology structure diagram, the status of the transmission equipment, the preset time transmission characteristics corresponding to each transmission equipment, and the prediction information to obtain a data transmission strategy with the shortest transmission time.

[0070] The central control module adjusts the control status of the corresponding equipment according to the data transmission strategy.

[0071] The present invention realizes the following data processing flow through the cooperation of the data acquisition module, the information collection module, the transmission volume prediction module, the strategy formulation module and the central control module:

[0072] The network hotspot information whose data transmission change rate is greater than the preset change rate is collected by the network crawler method; then the network hotspot information and the first data transmission volume of each node in the packet transmission network are analyzed by using the preset data transmission prediction model, and the predicted transmission volume, predicted transmission position, and predicted probability of transmission to the predicted transmission position of each node are estimated; then the topology structure diagram, the transmission device status, the preset time transmission characteristics corresponding to each transmission device, and the preset information are analyzed by using the preset topology synchronization analysis model to obtain the data transmission strategy with the least transmission time; finally, the control state of the corresponding device is adjusted according to the data transmission strategy. The present invention estimates the predicted transmission volume of each node in the above manner, and generates a control strategy in a targeted manner, which solves the problem that when the packet transmission network encounters sudden large-scale data transmission, the fixed packet transmission mode is used to cause the transmission channel to be blocked, thereby causing a long transmission time delay, and ensures the timeliness and stability of data transmission.

[0073] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0074] It should be noted that in the description of the present invention, the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer" and the like indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings, which are only for the convenience of description, and do not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", and "third" are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance.

[0075] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0076] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0077] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0078] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0079] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0080] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.

[0081] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

Claims

1. A topology synchronization analysis method for a PTN packet transmission network, characterized in that: include: Acquire the transmission device model of each node in the packet transmission network, the topological structure diagram formed by each node, the first data transmission volume of each node, and the status of each transmission device; And according to the model of each transmission device, obtain the preset time transmission characteristics corresponding to each transmission device; Using a web crawler method to collect network hotspot information with a data transmission change rate greater than a preset change rate; The network hotspot information and the first data transmission volume are analyzed by using a preset data transmission prediction model to obtain prediction information, specifically including: obtaining trend information including a trend prediction function according to the second data transmission volume, heat value and data transmission change rate of the network hotspot information in each node; analyzing the first data transmission volume and trend information to obtain prediction information formed by the predicted transmission volume, predicted transmission position, trend information and prediction probability of each node; The preset topology synchronization analysis model is used to analyze the topology structure diagram, the transmission device status, the preset time transmission characteristics corresponding to each transmission device, and the prediction information to obtain the data transmission strategy with the shortest transmission time; Adjust the control status of the corresponding device according to the data transmission strategy.

2. The topology synchronization analysis method according to claim 1, characterized in that: The process of obtaining trend information includes: Monitor the data change amount of network hot spot information in real time, and obtain the data transmission change rate based on the data change amount; when the data transmission change rate is greater than the preset change rate, use the network crawler method to collect the corresponding network hot spot information, and analyze the comment data of the network hot spot information to determine the heat value; estimate the diffusion rate of the network hot spot information based on the heat value and data transmission change rate of the network hot spot information; obtain the trend prediction function based on the second data transmission amount and diffusion rate of the network hot spot information; integrate the trend prediction function, heat value and network hot spot information to obtain trend information.

3. The topology synchronization analysis method according to claim 2, characterized in that: The analysis of the comment data of the network hot information to determine the heat value includes: Monitor and obtain the change in comment data in each communication platform; determine the average change rate based on the change in comment data in each communication platform; predict the duration based on the type of network hot information, the keywords in the content and the corresponding relationship between the preset mapping library; use the weighted average method to weight the preset heat values ​​corresponding to the average change rate and duration to obtain the heat value.

4. The topology synchronization analysis method according to claim 3, characterized in that: The processing process of obtaining the prediction information includes: A quantity prediction function is formed based on a first data transmission volume, a corresponding second data transmission volume and a trend prediction function, and a predicted transmission volume is obtained based on the quantity prediction function; a transmission position is predicted based on a diffusion rate in the trend prediction function; and a predicted probability of transmission to the predicted transmission position is estimated based on a correspondence between an extreme value interval of a data transmission change rate and a preset mapping table; the predicted transmission volume, predicted transmission position, trend information and predicted probability are integrated to obtain prediction information.

5. The topology synchronization analysis method according to claim 1, characterized in that: The processing process of the preset topology synchronization analysis model includes: Determine multiple transmission devices whose states need to be adjusted according to the predicted transmission volume, predicted transmission position, and total transmission bandwidth of each node in the transmission device state; Determine the optimal transmission bandwidth and estimated transmission time based on the preset time transmission characteristics, topology diagram, predicted transmission volume, and total transmission bandwidth of each transmission device; Determine the sending frequency of the time synchronization information according to the preset time transmission characteristics of the transmission equipment corresponding to the sending end and the receiving end; A data transmission strategy is formed with multiple transmission devices that need to adjust their states, optimal transmission bandwidth, and transmission frequency.

6. The topology synchronization analysis method according to claim 5, characterized in that: The method of determining the optimal transmission bandwidth and estimating the transmission time according to the preset time transmission characteristics, topology diagram, predicted transmission volume, and total transmission bandwidth of each transmission device includes: The ant colony algorithm is used to process the predicted transmission volume and total transmission bandwidth to determine the optimal transmission bandwidth; the estimated transmission time is obtained based on the optimal transmission bandwidth, the preset time transmission characteristics of each transmission device and the transmission distance in the topological structure diagram.

7. The topology synchronization analysis method according to claim 5, characterized in that: The method of determining the sending frequency of time synchronization information according to the preset time transmission characteristics of the transmission devices corresponding to the transmitting end and the receiving end includes: according to the preset time transmission characteristics of each transmission device, regularly sending time synchronization information to the corresponding transmission device to correct the data synchronization time.

8. The topology synchronization analysis method according to claim 1, characterized in that: The preset topology synchronization analysis model is constructed based on a convolutional neural network, a transmission device state, and preset time transmission characteristics corresponding to each transmission device.

9. The topology synchronization analysis method according to claim 1, characterized in that: After adjusting the control state of the corresponding device according to the data transmission strategy, the method further includes: After the pre-transmission data is added to the to-be-transmitted list, the pre-transmission data is compressed using a corresponding compression method according to a decompression format in a receiving device corresponding to the transmission terminal.

10. A topology synchronization analysis system for a PTN packet transmission network, characterized in that: include: A data acquisition module, which acquires the transmission device model of each node in the packet transmission network, the topological structure diagram formed by each node, the first data transmission volume of each node, and the status of each transmission device; and acquires the preset time transmission characteristics corresponding to each transmission device according to the model of each transmission device; An information collection module, which uses a web crawler method to collect network hotspot information whose data transmission change rate is greater than a preset change rate; The transmission volume prediction module uses a preset data transmission prediction model to analyze the network hotspot information and the first data transmission volume to obtain prediction information, specifically including: obtaining trend information including a trend prediction function according to the second data transmission volume, heat value and data transmission change rate of the network hotspot information in each node; analyzing the first data transmission volume and trend information to obtain prediction information formed by the predicted transmission volume, predicted transmission position, trend information and prediction probability of each node; The strategy formulation module uses a preset topology synchronization analysis model to analyze the topology structure diagram, the status of the transmission equipment, the preset time transmission characteristics corresponding to each transmission equipment, and the prediction information to obtain a data transmission strategy with the least transmission time; The central control module adjusts the control status of the corresponding equipment according to the data transmission strategy.

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