A data processing method and system based on communication network

Abstract

The present application provides a data processing method and system based on a communication network, which divides the communication traffic in the communication traffic data into continuous communication traffic and intermittent communication traffic based on time domain distribution characteristics; determines the traffic trust tolerance of each communication node in the communication network according to the continuous communication traffic, and then estimates the stability of the traffic through the trust tolerance of each traffic and the time domain distribution characteristics to obtain the communication response state of each communication node; determines the intermittent characteristics of the communication nodes in the communication network in the node communication, and then determines the stability margin of each communication node in the node communication through the intermittent characteristics; determines the traffic anomaly of each communication node according to the communication response state and stability margin of each communication node, and evenly distributes the traffic of each communication node according to each traffic anomaly. Based on the above scheme, even distribution of traffic in communication nodes can be achieved, thereby improving the traffic utilization rate of communication nodes in the communication network.

Description

Technical Field

[0001] The present application relates to the technical field of communication networks, and more specifically, to a data processing method and system based on a communication network. Background Art

[0002] A communication network is an infrastructure system used to transmit data and information between multiple devices. It consists of various interconnected nodes that exchange data through wired or wireless means to support users to communicate between different geographical locations. The core components of a communication network include routers, switches, base stations, servers, etc. They coordinate with each other through transmission protocols and network topology to ensure that data is effectively transmitted in the network. With the advancement of technology, modern communication networks not only support voice calls and text messages, but also carry high-speed data transmission requirements such as video streaming, IoT data, and real-time applications.

[0003] With the rapid growth of data volume in communication networks and the increase in real-time processing requirements, traditional data transmission and processing modes face problems such as delays and congestion, which may cause abnormalities in communication nodes. Data processing methods based on communication networks can achieve efficient utilization and dynamic balanced management of network resources through distributed processing and intelligent scheduling of data collected in real time by each communication node, which can improve the traffic utilization rate of communication networks. Therefore, how to achieve balanced distribution of traffic in communication nodes and thus improve the traffic utilization rate of communication nodes in communication networks is a difficult problem faced by the industry. Summary of the invention

[0004] The present application provides a data processing method and system based on a communication network, which can achieve balanced distribution of traffic in communication nodes, thereby improving the traffic utilization rate of communication nodes in the communication network.

[0005] In a first aspect, the present application provides a data processing method based on a communication network, the data processing method comprising the following steps:

[0006] Monitor the communication traffic of each communication node in the communication network, and then obtain the communication traffic data;

[0007] Acquire time-domain distribution characteristics of communication traffic in the communication network, and then divide the communication traffic in the communication traffic data into continuous communication traffic and intermittent communication traffic based on the time-domain distribution characteristics;

[0008] Determine the flow trust tolerance of each communication node in the communication network according to the continuous communication flow, and then estimate the stability of the flow of each communication node in the communication network according to the trust tolerance of each flow and the time domain distribution characteristics, and obtain the communication response state of each communication node;

[0009] Determine the intermittent characteristics of the communication nodes in the communication network in the node communication, and then determine the stability margin of each communication node in the node communication through the intermittent characteristics and the flow volatility of each communication node in the intermittent communication flow;

[0010] The flow anomaly degree of each communication node is determined according to the communication response state and stability margin of each communication node, and the flow of each communication node in the communication network is evenly distributed according to each flow anomaly degree.

[0011] In this embodiment, obtaining the time domain distribution characteristics of the communication traffic in the communication network specifically includes:

[0012] Obtain historical traffic data of each communication node in the communication network;

[0013] Determine the flow gradient in the time dimension of the corresponding communication node according to the historical flow data of each communication node;

[0014] The time domain distribution characteristics of communication traffic in the communication network are obtained based on all traffic gradients.

[0015] In this embodiment, dividing the communication traffic in the communication traffic data into continuous communication traffic and intermittent communication traffic based on the time domain distribution characteristics specifically includes:

[0016] Pre-training a traffic anomaly detection model according to the time domain distribution characteristics;

[0017] All communication flows are subjected to anomaly detection through the traffic anomaly detection model to obtain continuous communication flows and intermittent communication flows.

[0018] In this embodiment, determining the flow trust tolerance of each communication node in the communication network according to the continuous communication flow specifically includes:

[0019] Performing noise reduction on the continuous communication traffic to obtain noise reduction traffic information;

[0020] Extracting the noise reduction traffic data of each communication node in the communication network from the noise reduction traffic information;

[0021] The upper and lower bounds of the traffic trust tolerance of the corresponding communication node are determined according to the noise reduction traffic data of each communication node, and then the traffic trust tolerance of each communication node in the communication network is obtained.

[0022] In this embodiment, the stability of the traffic of each communication node in the communication network is estimated by using the trusted tolerance of each traffic and the time domain distribution characteristics, and the communication response state of each communication node is obtained, which specifically includes:

[0023] For each communication node, the abnormal flow value of the communication node is determined according to the flow trust tolerance of the communication node;

[0024] Determine the abnormal factor of the communication node according to the abnormal flow value and the time domain distribution characteristics;

[0025] The stability of the communication node traffic is estimated by the abnormal factor, the communication response state of the communication node is obtained, and then the communication response state of each communication node is obtained.

[0026] In this embodiment, determining the discontinuity characteristics of a communication node in a communication network in node communication specifically includes:

[0027] Obtaining data packet loss records and data packet retransmission records of communication nodes in the communication network;

[0028] determining a packet loss rate in a communication network based on the packet loss record;

[0029] Determining a data packet retransmission rate in a communication network through the data packet retransmission record;

[0030] The discontinuity characteristics of the communication nodes in the communication network in the node communication are determined according to the data packet loss rate and the data packet retransmission rate.

[0031] In this embodiment, determining the flow abnormality of each communication node according to the communication response state and stability margin of each communication node specifically includes:

[0032] Obtain the traffic threshold of each communication node;

[0033] For each communication node, a flow deviation is determined according to the communication response state of the communication node and the flow threshold;

[0034] The flow deviation is evaluated by responding to the stability margin of the communication node to obtain the flow anomaly of the communication node, and then the flow anomaly of each communication node is obtained.

[0035] In this embodiment, determining the stability margin of each communication node in the node communication by the intermittent characteristics and the traffic volatility of each communication node in the intermittent communication traffic specifically includes:

[0036] For each communication node in the node communication, determining the traffic significance value and traffic volatility of the communication node according to the intermittent communication traffic;

[0037] Determining a stability factor based on the flow volatility and the discontinuity characteristics;

[0038] The stability margin of the communication node is determined according to the stability factor and the traffic significance value, and then the stability margin of each communication node in the node communication is obtained.

[0039] In this embodiment, a traffic monitoring tool is used to monitor the communication traffic of each communication node in the communication network.

[0040] In a second aspect, the present application provides a data processing system based on a communication network, for executing a data processing method based on a communication network, the data processing system comprising:

[0041] A monitoring module is used to monitor the communication traffic of each communication node in the communication network, and then obtain the communication traffic data;

[0042] A division module, used to obtain the time domain distribution characteristics of the communication traffic in the communication network, and then divide the communication traffic in the communication traffic data into continuous communication traffic and intermittent communication traffic based on the time domain distribution characteristics;

[0043] A communication response module, used to determine the flow trust tolerance of each communication node in the communication network according to the continuous communication flow, and then estimate the stability of the flow of each communication node in the communication network through each flow trust tolerance and the time domain distribution characteristics, so as to obtain the communication response state of each communication node;

[0044] A stability margin determination module, used to determine the intermittent characteristics of the communication nodes in the communication network in the node communication, and then determine the stability margin of each communication node in the node communication through the intermittent characteristics and the flow volatility of each communication node in the intermittent communication flow;

[0045] The balanced distribution module is used to determine the flow anomaly degree of each communication node according to the communication response state and stability margin of each communication node, and to evenly distribute the flow of each communication node in the communication network according to each flow anomaly degree.

[0046] The technical solution provided by the embodiments disclosed in this application has the following beneficial effects:

[0047] Monitor the communication traffic of each communication node in the communication network to obtain communication traffic data; obtain the time domain distribution characteristics of the communication traffic in the communication network, and then divide the communication traffic in the communication traffic data into continuous communication traffic and intermittent communication traffic based on the time domain distribution characteristics; determine the traffic trust tolerance of each communication node in the communication network according to the continuous communication traffic, and then estimate the stability of the traffic of each communication node in the communication network through each traffic trust tolerance and the time domain distribution characteristics to obtain the communication response state of each communication node; determine the intermittent characteristics of the communication nodes in the communication network in the node communication, and then determine the stability margin of each communication node in the node communication through the intermittent characteristics and the traffic volatility of each communication node in the intermittent communication traffic; determine the traffic anomaly of each communication node according to the communication response state and stability margin of each communication node, and evenly distribute the traffic of each communication node in the communication network according to each traffic anomaly.

[0048] It can be seen that in this application, the flow anomaly of each communication node is determined according to the communication response state and stability margin of each communication node, and the flow of each communication node in the communication network is evenly distributed according to each flow anomaly; first, the communication response state can be determined to obtain parameters that reflect the coping ability of each communication node in the face of flow changes. By monitoring the response state of each communication node, overloaded nodes and underutilized communication nodes in the network can be discovered in time. Identifying overloaded nodes helps to avoid communication nodes being overwhelmed by excessive flow, so that flow distribution can be dynamically adjusted, and flow can be reallocated to communication nodes with stronger response capabilities to avoid the emergence of performance bottlenecks, thereby improving performance. Improve the overall load balance of the communication network; then, determine the stability margin to obtain the tolerance of the communication node under traffic fluctuations. Understanding the stability margin of the communication node can help determine whether the communication node can maintain stable performance when the traffic suddenly increases or fluctuates. By reasonably allocating traffic to communication nodes with higher stability margins, the network load can be effectively balanced, and communication interruptions and performance degradation caused by traffic fluctuations can be reduced, thereby effectively improving the resource utilization efficiency of the communication network and avoiding communication delays and network congestion caused by overloaded communication nodes. In summary, based on the above scheme, balanced distribution of traffic in communication nodes can be achieved, thereby improving the traffic utilization rate of communication nodes in the communication network. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0050] Figure 1 is a flow chart of a data processing method based on a communication network provided by the present application;

[0051] Figure 2 is an exemplary flow chart of traffic division provided by the present application;

[0052] Figure 3 is an exemplary flow chart for determining a flow trust tolerance according to the present application;

[0053] Figure 4 It is a module structure diagram of a data processing system based on a communication network provided in this application. DETAILED DESCRIPTION

[0054] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0055] The embodiment of the present application provides a data processing method and system based on a communication network, which divides the communication traffic in the communication traffic data into continuous communication traffic and intermittent communication traffic based on the time domain distribution characteristics; determines the traffic trust tolerance of each communication node in the communication network according to the continuous communication traffic, and then estimates the stability of the traffic through the trust tolerance of each traffic and the time domain distribution characteristics, and obtains the communication response state of each communication node; determines the intermittent characteristics of the communication nodes in the communication network in the node communication, and then determines the stability margin of each communication node in the node communication through the intermittent characteristics; determines the traffic anomaly of each communication node according to the communication response state and stability margin of each communication node, and evenly distributes the traffic of each communication node according to each traffic anomaly. Based on the above scheme, the balanced distribution of traffic in the communication nodes can be achieved, thereby improving the traffic utilization rate of the communication nodes in the communication network.

[0056] Embodiment 1

[0057] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods. Figure 1 As shown in FIG. 1 , this figure is an exemplary flow chart of a data processing method based on a communication network according to this embodiment of the present application, and the data processing method includes the following steps:

[0058] In step S1, the communication flow of each communication node in the communication network is monitored to obtain communication flow data.

[0059] It should be noted that in the present application, the communication traffic data is a data set of the current communication traffic in each communication node; in specific implementation, the traffic monitoring tool in each communication node can be used to detect the communication traffic every 1 second within a specified short time period (the default is 5 minutes), and the collection of all communication traffic can be used as the communication traffic data.

[0060] In step S2, the time domain distribution characteristics of the communication traffic in the communication network are obtained, and then the communication traffic in the communication traffic data is divided into continuous communication traffic and intermittent communication traffic based on the time domain distribution characteristics.

[0061] In this embodiment, obtaining the time domain distribution characteristics of the communication traffic in the communication network can be achieved by using the following steps:

[0062] Obtain historical traffic data of each communication node in the communication network;

[0063] Determine the flow gradient in the time dimension of the corresponding communication node according to the historical flow data of each communication node;

[0064] The time domain distribution characteristics of communication traffic in the communication network are obtained based on all traffic gradients.

[0065] It should be noted that, in the present application, the time domain distribution characteristics reflect the severity of changes in the communication traffic of each communication node in each time dimension; the traffic gradient is an indicator to measure the degree of change of the communication traffic in a specified communication node over time.

[0066] In the specific implementation, first, the historical traffic data of the corresponding communication node in the specified time period (the default is 1 month ago to 5 minutes ago) can be obtained from the database of each communication node in the communication network; then, for each communication node, the historical traffic data at each communication node in the communication node is obtained, and the Euclidean distance between the historical traffic data at adjacent communication nodes is used as the traffic difference between the adjacent communication nodes, and then the traffic difference between all adjacent communication nodes is obtained, and then the average value of all traffic differences is used as the traffic gradient of the communication node in the time dimension, and then the traffic gradient of each communication node in the time dimension is obtained; finally, the matrix composed of each traffic gradient according to the horizontal position of the corresponding communication node can be used as the time domain distribution characteristics of the communication traffic in the communication network in the time dimension.

[0067] In this embodiment, reference Figure 2 As shown, the figure is a schematic diagram of the flow of traffic division in this embodiment of the present application. The communication traffic in the communication traffic data is divided into continuous communication traffic and intermittent communication traffic based on the time domain distribution characteristics, which can be achieved by the following steps:

[0068] In S21, a traffic anomaly detection model is pre-trained according to the time domain distribution characteristics;

[0069] In S22, all communication flows are subjected to anomaly detection by using the flow anomaly detection model to obtain continuous communication flows and intermittent communication flows.

[0070] It should be noted that in the present application, the traffic anomaly detection model is a model for detecting abnormal data in historical traffic data. The traffic anomaly detection model can be obtained by pre-training with historical traffic data. In other embodiments, the traffic anomaly detection model is also obtained based on convolutional neural network training, which is not limited here.

[0071] In the specific implementation, first, the time domain distribution characteristics are introduced into the traffic anomaly detection model as the initial constraint parameters, which can provide the traffic anomaly detection model with a priori knowledge of the communication traffic distribution. This priori knowledge can constrain the traffic anomaly detection model's understanding of historical traffic data during the detection process, and avoid the traffic anomaly detection model from mistakenly identifying normal communication traffic fluctuations as anomalies without constraints. The constraint of this priori knowledge makes the traffic anomaly detection model more accurate in distinguishing continuous communication traffic from intermittent communication traffic; then, all monitored communication traffic is used as the input of the traffic anomaly detection model, and the continuous data and intermittent data are output by the traffic anomaly detection model, and the set composed of the output continuous data is used as the continuous communication traffic, and the set composed of the output intermittent data is used as the intermittent communication traffic.

[0072] In step S3, the flow trust tolerance of each communication node in the communication network is determined according to the continuous communication flow, and then the stability of the flow of each communication node in the communication network is estimated through each flow trust tolerance and the time domain distribution characteristics to obtain the communication response status of each communication node.

[0073] In this embodiment, reference Figure 3 As shown, this figure is a schematic diagram of the process of determining the trusted tolerance of traffic in this embodiment of the present application. In this embodiment, the trusted tolerance of traffic of each communication node in the communication network can be determined according to the continuous communication traffic by the following steps:

[0074] In S31, the continuous communication traffic is subjected to noise reduction to obtain noise reduction traffic information;

[0075] In S32, extracting the noise reduction traffic data of each communication node in the communication network from the noise reduction traffic information;

[0076] In S33, the upper and lower bounds of the traffic trust tolerance of the corresponding communication node are determined according to the noise reduction traffic data of each communication node, and then the traffic trust tolerance of each communication node in the communication network is obtained.

[0077] It should be noted that, in the present application, the flow trust tolerance refers to the allowable range of flow fluctuations of each communication node in the communication network under normal circumstances; in specific implementation, first, the Kalman filtering technology can be used to perform noise reduction processing on the continuous communication flow, and then the data segment obtained after the noise reduction processing is used as the noise reduction flow information; secondly, the noise reduction flow data corresponding to each communication node in the communication network is intercepted from the noise reduction flow information; then, the average value of all communication flow values ​​in the noise reduction flow data of each communication node is used as the mean value of the communication flow of the corresponding communication node, and all communication flow values ​​in the noise reduction flow data of each communication node are substituted into the variance calculation formula, and then the variance of the communication flow of the corresponding communication node is obtained. It is assumed that the communication flow distribution of each communication node conforms to the normal distribution. Then select a confidence level (such as 95%), and obtain the confidence critical value according to the selected confidence level. Usually, at the 95% confidence level, the confidence critical value is usually 1.96. Then, the upper and lower bounds of the corresponding communication node traffic trust tolerance are calculated by the confidence critical value, the mean and variance of the communication traffic of each communication node. The upper bound of the traffic trust tolerance can be determined by the following formula, namely: the upper bound of the traffic trust tolerance = mean + confidence critical value * (variance / half of the total number of data), and the lower bound of the traffic trust tolerance can be determined by the following formula, namely: the lower bound of the traffic trust tolerance = mean - confidence critical value * (variance / half of the total number of data), and then the interval composed of the lower bound and the upper bound is used as the traffic trust tolerance of the corresponding communication node.

[0078] In this embodiment, the stability of the traffic of each communication node in the communication network is estimated by using the trustworthy tolerance of each traffic and the time domain distribution characteristics, and the communication response state of each communication node is obtained, which can be achieved by the following steps:

[0079] For each communication node, the abnormal flow value of the communication node is determined according to the flow trust tolerance of the communication node;

[0080] Determine the abnormal factor of the communication node according to the abnormal flow value and the time domain distribution characteristics;

[0081] The stability of the communication node traffic is estimated by the abnormal factor, the communication response state of the communication node is obtained, and then the communication response state of each communication node is obtained.

[0082] It should be noted that in the present application, the communication response state represents the stability state of the communication node, and the communication response state includes the normal response state, the interference state and the failure state; the abnormal flow value is a quantitative value used to measure the degree of flow exceeding the normal fluctuation; the abnormal factor is an indicator used to measure the degree of deviation of the abnormal flow value in the time domain distribution.

[0083] In specific implementation, first, for each communication node, the difference between the mean of all communication flows of the communication node in the communication flow data and the flow trust tolerance of the communication node can be used as the abnormal flow value; then, the ratio of the abnormal flow value to the characteristic value of the time domain distribution feature can be used as the abnormal factor of the communication node; finally, a stability threshold (including a stable threshold, a moderate threshold and a severe threshold) is set, and the abnormal factor of the communication node is compared with the stability threshold. If the abnormal factor is less than or equal to the stable threshold, it is determined that the flow stability is high and the communication node is in a normal response state; if the abnormal factor is greater than the stable threshold and less than or equal to the moderate threshold, it is determined that the flow fluctuation is large and the communication node is in a disturbed state; if the abnormal factor is greater than the severe threshold, it is determined that the communication node responds abnormally and the communication node is in a failed state, and the determination result is used as the communication response state of the communication node. The communication response state of each communication node can be obtained in the above manner.

[0084] In step S4, the intermittent characteristics of the communication nodes in the communication network in the node communication are determined, and then the stability margin of each communication node in the node communication is determined based on the intermittent characteristics and the traffic volatility of each communication node in the intermittent communication traffic.

[0085] In this embodiment, determining the discontinuity characteristics of a communication node in a communication network in node communication may be implemented by the following steps:

[0086] Obtaining data packet loss records and data packet retransmission records of communication nodes in the communication network;

[0087] determining a packet loss rate in a communication network based on the packet loss record;

[0088] Determining a data packet retransmission rate in a communication network through the data packet retransmission record;

[0089] The discontinuity characteristics of the communication nodes in the communication network in the node communication are determined according to the data packet loss rate and the data packet retransmission rate.

[0090] It should be noted that, in the present application, the intermittent feature is a feature that reflects the fact that a communication node has a brief connection interruption and data is not successfully transmitted during the transmission process; the packet loss record refers to the record of sent data packets that failed to successfully reach the target due to various reasons in the network; the packet retransmission record refers to the record of data packets resent by the sender due to failure to receive confirmation; the packet loss rate is the ratio of the number of lost data packets per unit time to the total number of sent data packets; the packet retransmission rate is the ratio of the number of retransmitted data packets per unit time to the total number of lost packets.

[0091] In specific implementation, first, the data packet loss records and data packet retransmission records of the communication nodes can be obtained from the central console of the communication network; secondly, the number of data packet transmissions of the communication nodes can be obtained from the central console of the communication network, and the ratio of the data volume of the data packet loss records to the number of data packet transmissions can be used as the data packet loss rate in the communication network; then, the ratio of the data volume of the data packet retransmission records to the data volume of the data packet loss records can be used as the data packet retransmission rate in the communication network; the product of the data packet loss rate and the data packet retransmission rate can be used as the intermittent feature of the communication nodes in the communication network in the node communication.

[0092] In this embodiment, determining the stability margin of each communication node in the node communication by the intermittent characteristics and the traffic volatility of each communication node in the intermittent communication traffic can be implemented by the following steps:

[0093] For each communication node in the node communication, determining the traffic significance value and traffic volatility of the communication node according to the intermittent communication traffic;

[0094] Determining a stability factor based on the flow volatility and the discontinuity characteristics;

[0095] The stability margin of the communication node is determined according to the stability factor and the traffic significance value, and then the stability margin of each communication node in the node communication is obtained.

[0096] It should be noted that, in the present application, the stability margin reflects the redundant space for the communication node to maintain normal communication under fluctuating conditions; in specific implementation, first, for each communication node in the node communication, the mode of all communication flows of the communication node in the intermittent communication flow can be used as the flow significance value of the communication node, and the flow significance value represents the baseline level of the flow of the communication node under normal communication conditions, and the standard deviation of all communication flows of the communication node in the intermittent communication flow can be used as the flow volatility, and the flow volatility represents the stability and mutation degree of the flow in the communication node; then, the inverse of the product of the flow volatility and the intermittent characteristic can be used as the stability factor, and the stability factor is an indicator for evaluating the stability of the communication node; finally, the product of the stability factor and the flow significance value can be used as the stability margin of the communication node. The stability margin of each communication node in the node communication can be obtained in the above manner.

[0097] In step S5, the flow anomaly degree of each communication node is determined according to the communication response state and stability margin of each communication node, and the flow of each communication node in the communication network is evenly distributed according to each flow anomaly degree.

[0098] In this embodiment, the flow abnormality of each communication node can be determined according to the communication response state and stability margin of each communication node by using the following steps:

[0099] Obtain the traffic threshold of each communication node;

[0100] For each communication node, a flow deviation is determined according to the communication response state of the communication node and the flow threshold;

[0101] The flow deviation is evaluated by responding to the stability margin of the communication node to obtain the flow anomaly of the communication node, and then the flow anomaly of each communication node is obtained.

[0102] It should be noted that, in the present application, the flow anomaly degree indicates the degree of abnormality of the flow in the communication node; in specific implementation, first, the upper limit of the flow that each communication node can transmit can be obtained from the central control console of the communication network as the flow threshold of the corresponding communication node, and the flow threshold is the flow range that the communication node should comply with under normal working conditions; then, for each communication node, the absolute value of the difference between the mean of all communication flows of the communication node in the communication flow data and the upper limit of the flow threshold can be used as the flow deviation, and the flow deviation indicates the degree to which the flow deviates from the normal range; finally, the ratio of the flow deviation to the stability margin of the communication node can be used as the flow anomaly degree of the communication node, and the flow anomaly degree of each communication node can be obtained in the above manner.

[0103] In this embodiment, the traffic of each communication node in the communication network is evenly distributed according to each traffic anomaly degree. In the specific implementation, a balanced distribution model is initialized, and each traffic anomaly degree is used as the distribution benchmark of the balanced distribution model. The balanced distribution model is used to distribute the traffic of each communication node in the communication network to ensure that the traffic anomaly degree of each communication node is within the preset abnormal range.

[0104] In summary, the present application determines the flow anomaly of each communication node according to the communication response state and stability margin of each communication node, and evenly distributes the flow of each communication node in the communication network according to each flow anomaly; first, the communication response state can be determined to obtain parameters that reflect the coping ability of each communication node when facing flow changes. By monitoring the response state of each communication node, overloaded nodes and underutilized communication nodes in the network can be discovered in a timely manner. Identifying overloaded nodes helps to prevent communication nodes from being overwhelmed by excessive flow, so that flow distribution can be dynamically adjusted, and flow can be reallocated to communication nodes with stronger response capabilities, avoiding the emergence of performance bottlenecks, thereby improving The overall load of the communication network is balanced; then, the stability margin can be determined to obtain the tolerance of the communication node under traffic fluctuations. Understanding the stability margin of the communication node can help determine whether the communication node can maintain stable performance when the traffic suddenly increases or fluctuates. By reasonably allocating traffic to communication nodes with higher stability margins, the network load can be effectively balanced, and communication interruptions and performance degradation caused by traffic fluctuations can be reduced, thereby effectively improving the resource utilization efficiency of the communication network and avoiding communication delays and network congestion caused by overloaded communication nodes; in summary, based on the above scheme, balanced distribution of traffic in communication nodes can be achieved, thereby improving the traffic utilization rate of communication nodes in the communication network.

[0105] Embodiment 2

[0106] The present application provides a data processing system based on a communication network, referring to Figure 4 As shown, this figure is a schematic diagram of a data processing system according to this embodiment of the present application, and the data processing system includes:

[0107] The monitoring module 100 is used to monitor the communication traffic of each communication node in the communication network, and then obtain the communication traffic data;

[0108] A division module 200, configured to obtain a time domain distribution feature of the communication traffic in the communication network, and then divide the communication traffic in the communication traffic data into continuous communication traffic and intermittent communication traffic based on the time domain distribution feature;

[0109] The communication response module 300 is used to determine the flow trust tolerance of each communication node in the communication network according to the continuous communication flow, and then estimate the stability of the flow of each communication node in the communication network through the trust tolerance of each flow and the time domain distribution characteristics, so as to obtain the communication response state of each communication node;

[0110] A stability margin determination module 400, for determining intermittent characteristics of communication nodes in the communication network in node communication, and then determining the stability margin of each communication node in the node communication through the intermittent characteristics and the traffic volatility of each communication node in the intermittent communication traffic;

[0111] The balanced distribution module 500 is used to determine the flow anomaly degree of each communication node according to the communication response state and stability margin of each communication node, and to evenly distribute the flow of each communication node in the communication network according to each flow anomaly degree.

[0112] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0113] A person skilled in the art may understand that all or part of the steps in the various methods of the above embodiments may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, the storage medium including a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically-erasable programmable read-only memory (EEPROM), a compact disc (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0114] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

Claims

1. A data processing method based on a communication network, characterized in that: The data processing method comprises the following steps: Monitor the communication traffic of each communication node in the communication network, and then obtain the communication traffic data; Acquire time-domain distribution characteristics of communication traffic in the communication network, and then divide the communication traffic in the communication traffic data into continuous communication traffic and intermittent communication traffic based on the time-domain distribution characteristics; Determine the flow trust tolerance of each communication node in the communication network according to the continuous communication flow, and then estimate the stability of the flow of each communication node in the communication network according to the trust tolerance of each flow and the time domain distribution characteristics, and obtain the communication response state of each communication node; Determine the intermittent characteristics of the communication nodes in the communication network in the node communication, and then determine the stability margin of each communication node in the node communication through the intermittent characteristics and the flow volatility of each communication node in the intermittent communication flow; Determine the flow anomaly degree of each communication node according to the communication response state and stability margin of each communication node, and evenly distribute the flow of each communication node in the communication network according to each flow anomaly degree; Wherein, determining the flow trust tolerance of each communication node in the communication network according to the continuous communication flow specifically includes: Performing noise reduction on the continuous communication traffic to obtain noise reduction traffic information; Extracting the noise reduction traffic data of each communication node in the communication network from the noise reduction traffic information; Determine the upper and lower bounds of the traffic trust tolerance of the corresponding communication node according to the noise reduction traffic data of each communication node, and then obtain the traffic trust tolerance of each communication node in the communication network; Among them, the stability of the traffic of each communication node in the communication network is estimated by using the trustworthy tolerance of each traffic and the time domain distribution characteristics, and the communication response state of each communication node is obtained, which specifically includes: For each communication node, the abnormal flow value of the communication node is determined according to the flow trust tolerance of the communication node; Determine the abnormal factor of the communication node according to the abnormal flow value and the time domain distribution characteristics; The stability of the traffic of the communication node is estimated by the abnormal factor to obtain the communication response state of the communication node, and then the communication response state of each communication node is obtained; Wherein, determining the flow anomaly degree of each communication node according to the communication response state and stability margin of each communication node specifically includes: Obtain the traffic threshold of each communication node; For each communication node, a flow deviation is determined according to the communication response state of the communication node and the flow threshold; The flow deviation is evaluated by responding to the stability margin of the communication node to obtain the flow anomaly degree of the communication node, and then the flow anomaly degree of each communication node is obtained; Among them, determining the stability margin of each communication node in the node communication by the intermittent characteristics and the traffic volatility of each communication node in the intermittent communication traffic specifically includes: For each communication node in the node communication, determining the traffic significance value and traffic volatility of the communication node according to the intermittent communication traffic; Determining a stability factor based on the flow volatility and the discontinuity characteristics; The stability margin of the communication node is determined according to the stability factor and the traffic significance value, and then the stability margin of each communication node in the node communication is obtained.

2. A data processing method based on a communication network as claimed in claim 1, characterized in that: The time domain distribution characteristics of the communication traffic in the communication network are obtained specifically including: Obtain historical traffic data of each communication node in the communication network; Determine the flow gradient in the time dimension of the corresponding communication node according to the historical flow data of each communication node; The time domain distribution characteristics of communication traffic in the communication network are obtained based on all traffic gradients.

3. A data processing method based on a communication network as claimed in claim 1, characterized in that: Dividing the communication traffic in the communication traffic data into continuous communication traffic and intermittent communication traffic based on the time domain distribution characteristics specifically includes: Pre-training a traffic anomaly detection model according to the time domain distribution characteristics; All communication flows are subjected to anomaly detection through the traffic anomaly detection model to obtain continuous communication flows and intermittent communication flows.

4. A data processing method based on a communication network as claimed in claim 1, characterized in that Determining the discontinuity characteristics of a communication node in a communication network in node communication specifically includes: Obtaining data packet loss records and data packet retransmission records of communication nodes in the communication network; determining a packet loss rate in a communication network based on the packet loss record; Determining a data packet retransmission rate in a communication network through the data packet retransmission record; The discontinuity characteristics of the communication nodes in the communication network in the node communication are determined according to the data packet loss rate and the data packet retransmission rate.

5. A data processing method based on a communication network as claimed in claim 1, characterized in that: Use traffic monitoring tools to monitor the communication traffic of each communication node in the communication network.

6. A data processing system based on a communication network, used to execute a data processing method based on a communication network as claimed in any one of claims 1 to 5, characterized in that: The data processing system comprises: A monitoring module is used to monitor the communication traffic of each communication node in the communication network, and then obtain the communication traffic data; A division module, used to obtain the time domain distribution characteristics of the communication traffic in the communication network, and then divide the communication traffic in the communication traffic data into continuous communication traffic and intermittent communication traffic based on the time domain distribution characteristics; A communication response module, used to determine the flow trust tolerance of each communication node in the communication network according to the continuous communication flow, and then estimate the stability of the flow of each communication node in the communication network through each flow trust tolerance and the time domain distribution characteristics, so as to obtain the communication response state of each communication node; A stability margin determination module, used to determine the intermittent characteristics of the communication nodes in the communication network in the node communication, and then determine the stability margin of each communication node in the node communication through the intermittent characteristics and the flow volatility of each communication node in the intermittent communication flow; The balanced distribution module is used to determine the flow anomaly degree of each communication node according to the communication response state and stability margin of each communication node, and to evenly distribute the flow of each communication node in the communication network according to each flow anomaly degree.

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