Service flow processing method and device, equipment and storage medium

Abstract

The invention provides a service flow processing method and device, equipment and a storage medium. Relates to the technical field of computers. The method comprises the steps of obtaining a network topological relation and a network performance index of an SDN network, determining routing configuration information of service flow according to the network topological relation, the network performance index and a service quality requirement of the service flow, and performing routing forwarding on the service flow according to the routing configuration information. Wherein the routing configuration information is used for indicating the target transmission network of the service flow in the SDN network when the service quality is optimal. According to the method, the target transmission network when the service quality is optimal can be determined according to the service quality requirement of the service flow in combination with the network topological relation and the network performance index of the SDN network, and routing forwarding is performed on the service flow, so that the service quality requirement corresponding to the service flow is met, and the service quality of the service flow is improved.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a method, apparatus, device, and storage medium for processing business traffic. Background Art

[0002] As banks evolve from traditional single financial transaction platforms to core hubs connecting multiple parties for economic activity, their business scope has expanded significantly. This is particularly true for intermediary services such as agency payments for third-party clients (such as utility bill payments, insurance premium deductions, and payroll payments), which are characterized by a wide variety of services, diverse scenarios, and numerous participants. These services often require high-frequency, large-scale data transmission between banking and client systems. The resulting massive traffic volume poses significant challenges to the banking system's data transmission network.

[0003] In related technologies, various business flows generated within a banking system can be routed and forwarded to client systems via network devices. However, different business flows have different quality of service requirements. In this approach, the banking system directly sends various business flows sequentially to the network devices, which then route and forward them to each client system. This approach fails to meet the quality of service requirements for each business flow, resulting in poor service quality for the business flows. Summary of the Invention

[0004] The present application provides a method, apparatus, device and storage medium for processing business traffic, so as to meet the service quality requirements corresponding to different business traffic, thereby improving the service quality of business traffic.

[0005] In a first aspect, the present application provides a method for processing service traffic, comprising:

[0006] Obtain the network topology and network performance indicators of the SDN network;

[0007] Determine routing configuration information for the service traffic based on the network topology, the network performance indicators, and the service quality requirements of the service traffic, wherein the routing configuration information is used to indicate a target transmission network for the service traffic when the service quality is optimal in the SDN network;

[0008] The service traffic is routed and forwarded according to the routing configuration information.

[0009] In a possible implementation manner, determining the routing configuration information of the service traffic according to the network topology, the network performance indicator, and the quality of service requirement of the service traffic includes:

[0010] Determining a service identifier of the business flow according to a quality of service requirement of the business flow;

[0011] The network topology relationship, the network performance indicators and the service identifier of the business traffic are processed by the ant colony algorithm to determine the routing configuration information of the business traffic, wherein the routing configuration information includes the target transmission network, flow table items, metering table items and port queue information corresponding to the business traffic.

[0012] In one possible implementation, the network performance indicators include average remaining bandwidth, average packet loss rate, and average latency; and the processing of the network topology, the network performance indicators, and the service identifier of the service traffic by an ant colony algorithm to determine the routing configuration information of the service traffic includes:

[0013] Determining the average remaining bandwidth, the average packet loss rate, and the average delay;

[0014] Determining a quality of service metric of the SDN network according to the average remaining bandwidth, the average packet loss rate, and the average delay;

[0015] Based on the network topology relationship and the service identifier of the business traffic, the service quality metric value is iteratively calculated by the ant colony algorithm to determine the minimum service quality metric value, and the local network corresponding to the minimum service quality metric value is determined as the target transmission network in the SDN network, and the routing configuration information of the target transmission network is determined.

[0016] In a possible implementation manner, determining the average remaining bandwidth includes:

[0017] In the SDN network, determining an nth real-time bandwidth of an nth data flow in each link segment;

[0018] Determine the nth remaining bandwidth of each link segment based on the preset bandwidth of each link segment and the nth real-time bandwidth;

[0019] Determine the nth minimum remaining bandwidth among the nth remaining bandwidths of each link;

[0020] An average value of the sum of the n minimum residual bandwidths is determined as the average residual bandwidth.

[0021] In a possible implementation, determining the average packet loss rate includes:

[0022] In the SDN network, determining an nth successful transmission rate of an nth data flow on each link;

[0023] Determining the packet loss rate of the nth data stream according to the product of the nth successful transmission rates on each link;

[0024] The average value of the sum of the packet loss rates of the n data streams is determined as the average packet loss rate.

[0025] In a possible implementation manner, determining the average delay includes:

[0026] In the SDN network, determining a transmission time of multiple messages in an nth data flow on each link;

[0027] The average value of the sum of the transmission time of multiple messages on each link is determined as the nth transmission delay;

[0028] An average value of the sum of the n transmission delays is determined as the average delay.

[0029] In a possible implementation, the iterative calculation of the service quality metric value based on the network topology relationship and the service identifier of the service flow by the ant colony algorithm to determine the minimum service quality metric value includes:

[0030] Determining, in a T-th calculation, a T-th pheromone of each link in the SDN network based on the network topology and the service identifier of the business traffic;

[0031] According to the Tth pheromone of each link in the SDN network, the pheromone matrix is ​​updated until the number of iterations reaches a preset number to obtain a target pheromone matrix;

[0032] A minimum quality of service metric value is calculated based on the target pheromone matrix.

[0033] In a second aspect, the present application provides a device for processing service traffic, including:

[0034] The acquisition module is used to obtain the network topology and network performance indicators of the SDN network;

[0035] a processing module, configured to determine routing configuration information of the service traffic based on the network topology, the network performance indicators, and the quality of service requirements of the service traffic, wherein the routing configuration information is used to indicate a target transmission network for the service traffic when the quality of service is optimal in the SDN network;

[0036] The routing and forwarding module is used to route and forward the service traffic according to the routing configuration information.

[0037] In a third aspect, the present application provides an electronic device, comprising: a memory, a processor;

[0038] The memory stores computer-executable instructions;

[0039] The processor executes the computer-executable instructions stored in the memory, so that the processor executes the above first aspect and / or various possible implementations of the first aspect.

[0040] In a fourth aspect, the present application provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the above first aspect and / or various possible implementations of the first aspect.

[0041] In a fifth aspect, the present application provides a computer program product, comprising a computer program, which, when executed by a processor, implements the above first aspect and / or various possible implementations of the first aspect.

[0042] The service traffic processing method, apparatus, device, and storage medium provided herein include obtaining the network topology and network performance indicators of an SDN network, determining routing configuration information for the service traffic based on the network topology, network performance indicators, and the service traffic's quality of service requirements, and then routing and forwarding the service traffic based on the routing configuration information. The routing configuration information indicates the target transmission network for the service traffic when the service quality is optimal in the SDN network. This process can meet the quality of service requirements for different service traffic flows, thereby improving the service quality of the service traffic. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0044] Figure 1 A schematic diagram of an application scenario provided by an embodiment of the present application;

[0045] Figure 2 A flowchart of a first embodiment of a method for processing service traffic provided by this application;

[0046] Figure 3 A schematic diagram of the process of forwarding service traffic provided in an embodiment of the present application;

[0047] Figure 4 A flowchart of a second embodiment of the method for processing service traffic provided by this application;

[0048] Figure 5 A flowchart of a third embodiment of the method for processing service traffic provided by this application;

[0049] Figure 6 An architectural diagram of the service traffic scheduling system provided in an embodiment of the present application;

[0050] Figure 7 A schematic diagram of the structure of a device for processing service traffic provided in an embodiment of the present application;

[0051] Figure 8 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0052] The above drawings illustrate specific embodiments of the present application, which will be described in more detail below. These drawings and the textual description are not intended to limit the scope of the present application in any way, but rather to illustrate the concepts of the present application to those skilled in the art by reference to specific embodiments. DETAILED DESCRIPTION

[0053] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

[0054] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0055] First, let’s explain the terms involved in this application:

[0056] Agency intermediary business: The business in which a bank accepts a client's entrustment, handles the client's designated economic affairs on his behalf, and provides financial services, including agency commercial banking business, payment of utility bills, withholding of insurance premiums, salary payment, and agency bank card acquiring business for other banks.

[0057] Software Defined Networking (SDN): SDN is a new network architecture that decouples network control and forwarding functions, abstracting the underlying infrastructure from applications and services and allowing direct control through programming.

[0058] SDN controller: It can decouple the control plane and data plane through the southbound interface protocol, and perform flow-level control of SDN switches, thereby achieving smooth transmission of data streams, intelligently managing network traffic, and ensuring the provision of high-level service quality.

[0059] Adaptation: During the processing and analysis process, the processing method, processing sequence, processing parameters, boundary conditions or constraints are automatically adjusted according to the data characteristics of the processed data to adapt them to the statistical distribution characteristics and structural characteristics of the processed data to achieve the best processing effect.

[0060] Ant Colony Algorithm (ACO): An optimization algorithm based on swarm intelligence that aims to solve combinatorial optimization problems. It simulates the foraging behavior of ants in nature, specifically their use of pheromones to select paths, to find the optimal solution.

[0061] When banks provide intermediary agency services to third-party clients, they face massive traffic transmission between their systems and client systems. Different types of clients have varying requirements for network performance. For example, provident fund agency services require accurate and rapid results, while utility bill agency services require relatively low timeliness. The increasing scale of networks and the complex and diverse business demands place a severe strain on the transmission performance of banking networks.

[0062] In related technologies, various business flows generated within a banking system can be routed and forwarded to client systems via network devices, such as switches. However, different business flows have different quality of service requirements. In this approach, the banking system directly sends various business flows sequentially to the network devices, which then route and forward them to each client system. This approach fails to meet the quality of service requirements for each business flow, resulting in poor service quality for the business flows.

[0063] To address the above issues, the inventors considered that intelligent routing and forwarding management of service traffic could be performed based on the SDN network to meet different service quality requirements. Based on this, after multiple experiments, the inventors discovered that it is possible to obtain the network topology and network performance indicators of the SDN network, determine the routing configuration information for the service traffic based on the network topology, network performance indicators, and the service quality requirements of the service traffic, and route and forward the service traffic based on the routing configuration information to meet the service quality requirements corresponding to different service traffic. Based on this, the present application proposes a method for processing service traffic for dynamically analyzing and purposefully managing the service traffic generated by agent-type intermediary services in a banking system to optimize network performance and traffic transmission, thereby meeting different service quality requirements.

[0064] Figure 1 This is a schematic diagram of the application scenario provided by the embodiment of this application. Figure 1, including the banking system, routing devices and customer systems. When the source host of the banking system processes the proxy-type intermediate business, the business traffic generated can be forwarded to the target host of the customer system through the routing device. The routing forwarding path can be that the business traffic flows through SDN switch 1, SDN switch 2, SDN switch 3 and then forwarded to the target host.

[0065] Alternatively, the routing device may be an integral part of the banking system.

[0066] The following specific embodiments describe in detail the technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0067] Figure 2 This is a flowchart of the first embodiment of the method for processing business traffic provided by this application. Figure 2 , the method comprising:

[0068] S201: Obtain the network topology and network performance indicators of the SDN network.

[0069] The execution subject of the embodiments of the present application may be an electronic device, or a service flow processing device provided in the electronic device. The service flow processing device may be implemented by software, or by a combination of software and hardware. The service flow processing device may be a processor in the electronic device. For ease of understanding, the following description will take the execution subject electronic device as an example.

[0070] In this step, the electronic device can communicate with the routing device in the SDN network, exchange information through the interface protocol, obtain the network resource information and status of the SDN network reported by the routing device, and obtain the network topology and network performance indicators based on the network resource information and status. The routing device can be an SDN switch.

[0071] Optionally, the network topology relationship may include node discovery, link discovery, and host discovery. The node may be an SDN switch, and through an interactive handshake protocol between the electronic device and the SDN switch, the availability of the SDN switch node may be determined and a persistent connection may be established.

[0072] Links are inter-node links. Electronic devices broadcast link layer discovery protocol messages between nodes. If a bidirectional message loop exists between two nodes and the electronic device, a full-duplex link exists between the two nodes. Host discovery involves confirming information about hosts connected to the SDN switch. By broadcasting address resolution protocol messages, electronic devices can locate hosts directly connected to the SDN switch. These directly connected hosts can include both source and destination hosts.

[0073] Optionally, the network performance indicators may refer to real-time performance indicators of all links measured by the electronic device, including throughput, packet loss rate, and delay.

[0074] Throughput refers to the actual amount of data transmitted per unit time on a network, channel, or port. Packet loss rate refers to the percentage of packets lost during network transmission. Electronic devices can calculate throughput and packet loss rate by regularly acquiring port statistics from SDN switches. Latency refers to the time it takes for a packet to travel from one end of a network to the other. Electronic devices can send link latency measurement messages and determine latency by calculating the transmission and reception times of these messages.

[0075] S202: Determine routing configuration information for the service traffic based on the network topology, network performance indicators, and service quality requirements of the service traffic.

[0076] In this step, the electronic device can determine the routing configuration information for the service traffic based on the network topology, network performance indicators, and the service quality requirements of the service traffic. The routing configuration information is used to indicate the target transmission network for the service traffic when the service quality is optimal in the SDN network. In a specific implementation, the service identifier of the service traffic can be determined based on the service quality requirements of the service traffic. The network topology, network performance indicators, and the service identifier of the service traffic are processed using an ant colony algorithm to determine the routing configuration information for the service traffic. The routing configuration information includes the target transmission network, flow table entries, metering table entries, and port queue information corresponding to the service traffic.

[0077] Specifically, the ant colony algorithm processes network topology, network performance indicators, and service identifiers of business traffic to determine routing configuration information for the business traffic. This routing configuration information can refer to the calculation of global routing for multiple types of business traffic (such as utility bill payments, insurance premium deductions, and payroll payments) on the SDN network, resulting in a routing forwarding path for each type of business traffic to optimize resource utilization and meet the service quality requirements of various business types. The routing configuration information for each type of business traffic can include the target transmission network, flow table entries, metering table entries, and port queue information corresponding to the business traffic.

[0078] For example, the business traffic includes two types of business traffic, namely business traffic 1 and business traffic 2. The network topology relationship, network performance indicators, service identification of business traffic 1, and service identification of business traffic 2 can be processed through the ant colony algorithm to determine the routing configuration information 1 of business traffic 1 and the routing configuration information 2 of business traffic 2.

[0079] Optionally, the service identifier can be a 6-bit Differentiated Services Code Point (DSCP), where 2 bits represent the meter limit ratio, 1 bit represents the port queue rate, and the remaining 3 bits correspond to the service demand bits for bandwidth, packet loss rate, and latency, respectively.

[0080] For example, the 6-bit DiffServ value for service flow 1 can be 011111. The first two digits correspond to the meter's current limit ratio requirement, which is divided into four levels: 00 for unlimited flow, 01 for low flow limit, 10 for medium flow limit, and 11 for high flow limit. The third digit corresponds to the port queue rate requirement, with 0 representing a low rate and 1 representing a high rate. The fourth digit corresponds to the bandwidth requirement, with 0 representing a low bandwidth requirement and 1 representing a high bandwidth requirement. The fifth digit corresponds to the packet loss rate requirement, with 0 indicating a higher packet loss rate and 1 indicating a lower packet loss rate. The sixth digit corresponds to the latency requirement, with 0 indicating latency sensitivity and 1 indicating latency insensitivity.

[0081] Optionally, when bank agent intermediary service traffic enters the bank's internal SDN network, dedicated line routing equipment can assign DiffServ values ​​to the traffic based on customer requirements. For example, DiffServ value 1 can be assigned to service traffic 1, and DiffServ value 2 can be assigned to service traffic 2.

[0082] Specifically, the target transmission network can refer to the routing and forwarding order of a certain type of business traffic in multiple SDN switches; the flow table entry is used to define how to process business traffic and implement the matching and forwarding function of business traffic; the meter table entry is used to set rate limits, control the rate of business traffic, and prevent SDN network congestion. It is often used to implement Quality of Service (QoS) policies to ensure that critical businesses obtain the required bandwidth; the port queue information is used to manage the business traffic queues on the SDN switch ports and control the scheduling and priority of business traffic. By configuring different queues and priorities, high-priority traffic (such as real-time voice or video) can be ensured to be processed first.

[0083] S203: Routing and forwarding the service traffic according to the routing configuration information.

[0084] In this step, the service traffic may be routed and forwarded according to the target transmission network, flow table entry, metering table entry, and port queue information corresponding to the service traffic included in the determined routing configuration information.

[0085] Figure 3 This is a schematic diagram of the process of forwarding business traffic provided by the embodiment of this application. Figure 3 When the source host's service traffic (e.g., service traffic 1 generated by the utility bill payment service) enters the edge layer switch, it is first matched against the Internet Protocol (IP) domain by the flow table entry (flow table) and forwarded to the corresponding meter entry (meter). The meter specifies the maximum transmission rate, performs fine-grained flow control on the edge layer service traffic, and then forwards it to the egress port. When service traffic 1 enters the aggregation layer switch, it matches the flow table entry (flow table) and is forwarded to the port queue. The port queue performs coarse-grained flow control and finally enters the core layer switch. After a simple match, it is quickly forwarded and then passes through the aggregation layer switch and edge layer switch to the target host.

[0086] Fine-grained traffic limiting is implemented in edge switches through metering entries, allowing precise rate control for each type of service traffic to ensure that traffic does not exceed the preset maximum transmission rate. Coarse-grained traffic limiting is implemented through port queue management. Port queues can classify and manage traffic based on different priorities, ensuring that high-priority traffic is processed first.

[0087] Optionally, since the edge layer switches, aggregation layer switches, and core layer switches can each include multiple SDN switches, the target transmission network can refer to the sequence of multiple SDN switches that the service traffic passes through during routing and forwarding. Furthermore, during network transmission, the edge layer and aggregation layer that the service traffic generated by the source host passes through can be different from the aggregation layer and edge layer that the service traffic passes through after passing through the core layer and on its way to the target host, ultimately reaching the target host.

[0088] In the embodiments of the present application, routing configuration information for service traffic can be determined based on the network topology of the SDN network, network performance indicators, and the service quality requirements of the service traffic, and the service traffic can be routed and forwarded based on the routing configuration information. In the above process, by analyzing the network topology and network performance indicators, an optimal traffic network can be provided for service traffic with service quality requirements, thereby improving the service quality of the service traffic.

[0089] Figure 4 This is a flow chart of the second embodiment of the method for processing business traffic provided by this application. Figure 4 , the method comprising:

[0090] S401: Obtain the network topology and network performance indicators of the SDN network.

[0091] S402: Determine a service identifier of the business flow according to the service quality requirement of the business flow.

[0092] For example, for the service traffic of the utility bill payment service, if the service has high requirements for bandwidth, packet loss rate, and latency, a specific service identifier can be assigned to the service traffic. For example, the DSCP value is 101110. The first two bits (10) of the DSCP value indicate medium flow control, the third bit (1) indicates a high-speed port queue rate to reduce latency, the fourth bit (1) indicates high bandwidth requirements, the fifth bit (1) indicates a low packet loss rate, and the sixth bit (0) indicates sensitivity to latency.

[0093] S403: Process the network topology, network performance indicators, and service identifiers of the business traffic through an ant colony algorithm to determine routing configuration information of the business traffic.

[0094] In this step, the network topology, network performance indicators and service identifiers of business traffic can be processed by the ant colony algorithm to determine the target transmission network, flow table entries, metering table entries and port queue information corresponding to the business traffic.

[0095] In an optional embodiment, electronic devices can obtain global SDN network information, including network topology and network performance indicators. The network topology can include node, link, and host information, and network performance indicators can include throughput, packet loss rate, and latency. Based on the network topology, network performance indicators, and service identifiers of service traffic, an ant colony algorithm is used to calculate routes and generate target transmission networks, flow table entries, meter entries, and port queue information corresponding to the service traffic. The service identifiers of service traffic can be used as constraints for determining the target transmission network.

[0096] In a specific implementation, after determining the routing configuration information of the service traffic, a corresponding configuration message may be sent to the SDN switch involved in the target transmission network to complete the configuration of the flow table entries, metering table entries, and port queues.

[0097] For example, the target transmission network involves SDN switch 1 at the edge layer, SDN switch 2 at the aggregation layer, and SDN switch 3 at the core layer; flow entries and metering entries can be configured for SDN switch 1, flow entries and port queues can be configured for SDN switch 2, and flow entries can be configured for SDN switch 3.

[0098] It should be noted that the specific content of the configuration of each SDN switch can be specified based on the calculation results of the ant colony algorithm, so as to optimize the operation of each switch to meet the service quality requirements of the overall network, to ensure that switches at different levels can work together and achieve efficient transmission of business traffic.

[0099] S404: Routing and forwarding the service traffic according to the routing configuration information.

[0100] For example, service traffic 1 can be efficiently routed and forwarded based on the routing configuration information. Service traffic 1 starts from the source host, passes through the edge layer, aggregation layer, core layer, aggregation layer, edge layer, and finally reaches the destination host.

[0101] In an embodiment of the present application, an electronic device can determine its service identifier based on the service quality requirements of the business traffic. The network topology relationship, network performance indicators and the service identifier of the business traffic are processed by the ant colony algorithm to determine the routing configuration information of the business traffic, and the business traffic is routed and forwarded according to the routing configuration information. In the above process, by accurately identifying the service quality requirements of the business traffic, network resources can be more efficiently allocated and utilized, reducing resource waste. In addition, the ant colony algorithm used to process the network topology relationship, network performance indicators and the service identifier of the business traffic can simultaneously allocate a traffic network with the best overall service quality to multiple types of business traffic, thereby maximizing network transmission performance.

[0102] Figure 5 This is a flow chart of the third embodiment of the method for processing business traffic provided by this application. Figure 5 The network performance indicators include average remaining bandwidth, average packet loss rate, and average delay; the specific implementation of step S403 may include:

[0103] S501: Determine average remaining bandwidth, average packet loss rate, and average delay.

[0104] Optionally, the average remaining bandwidth of multiple data streams can be determined by the following steps ①②③④. Wherein, the number of data streams can be n, where n = 1, 2, ..., Z n The average remaining bandwidth of multiple data flows refers to the average remaining bandwidth of multiple simultaneous data flows (service traffic) within a certain period of time in an SDN network.

[0105] Step 1: In the SDN network, determine the nth real-time bandwidth of the nth data flow in each link.

[0106] Step ②: Determine the nth remaining bandwidth of each link segment based on the preset bandwidth of each link segment and the nth real-time bandwidth.

[0107] Step 3: Determine the nth minimum remaining bandwidth among the nth remaining bandwidths of each link.

[0108] Step 4: Determine the average value of the sum of the n minimum residual bandwidths as the average residual bandwidth.

[0109] Optionally, you can use the following formula to calculate the average remaining bandwidth of multiple data streams:

[0110]

[0111] In formula (1), L represents the link set path of the data flow, that is, all links of data flow transmission, l is any link in L, link is the link between nodes, F nl represents the real-time throughput of the lth link before sending the nth data stream, C nl The set bandwidth of the lth link of the nth data flow. The real-time throughput of the lth link before the nth data flow can be obtained by obtaining the port statistics of the SDN switch in real time.

[0112] For example, take a data flow (service flow) as an example, that is, n = 1. The remaining bandwidth of the data flow can be calculated by formula (1). Specifically, in the SDN network, the real-time bandwidth of each link before the data flow is sent can be determined; based on the preset bandwidth of each link and the real-time bandwidth of each link, the remaining bandwidth of each link can be determined, and the minimum remaining bandwidth in the remaining bandwidth of each link is determined as the remaining bandwidth of the data flow.

[0113] Optionally, the average packet loss rate of multiple data streams can be determined through the following steps ①②③.

[0114] Step 1: In the SDN network, determine the nth successful transmission rate of the nth data flow on each link.

[0115] Step 2: Determine the packet loss rate of the nth data stream based on the product of the nth successful transmission rates on each link.

[0116] Step 3: The average value of the sum of the packet loss rates of the n data streams is determined as the average packet loss rate.

[0117] Optionally, you can use the following formula to calculate the average packet loss rate of multiple data streams:

[0118]

[0119] In formula (2), Indicates the packet loss rate of the lth link of the nth data flow.

[0120] For example, n = 1. The packet loss rate of the data stream can be calculated using formula (2). Specifically, in an SDN network, the successful transmission rate of the data stream on each link segment can be determined, and the complement of the product of the successful transmission rates on each link segment can be used to determine the packet loss rate of the data stream.

[0121] Optionally, the average packet loss rate of multiple data streams can be determined through the following steps ①②③.

[0122] Step 1: In the SDN network, determine the transmission time of multiple packets in the nth data flow on each link.

[0123] Step 2: The average value of the sum of the transmission time of multiple messages on each link is determined as the nth transmission delay.

[0124] Step 3: The average value of the sum of the n transmission delays is determined as the average delay.

[0125] Optionally, you can use the following formula to calculate the average latency of multiple data streams:

[0126]

[0127] In formula (3), Indicates the time when the pth message of the lth link of the nth data flow is sent at the beginning of the link. Indicates the time when the pth packet of the lth link segment of the nth data flow is received at the link end.

[0128] For example, if n = 1 and p = 1, the data flow is a single data flow with one message. The average delay of the data flow can be calculated using formula (3). Specifically, in an SDN network, the transmission time of a single message of the data flow on each link segment can be determined, and the average of the sum of the transmission times of a single message on each link segment is determined as the average delay.

[0129] S502: Determine a service quality metric value of the SDN network according to the average remaining bandwidth, the average packet loss rate, and the average delay.

[0130] In this step, the service quality metric value of the SDN network can be determined based on the average remaining bandwidth, average packet loss rate, and average delay of the multiple data flows. The service quality metric value of the SDN network is the average service quality metric value of the multiple data flows.

[0131] Optionally, the average quality of service metric of multiple data streams can be obtained using the following calculation formula:

[0132]

[0133] In formula (4), ε is the positive offset of the service quality metric to avoid is negative; The smaller the value, the better the service quality of multiple data streams. a1, a2, and a3 are quality coefficients, and β1, β2, and β3 are proportional coefficients, which are used to balance QoS indicators with large differences in absolute values. Indicates the average remaining bandwidth of multiple data streams Indicates the average packet loss rate of multiple data streams Indicates the average delay of multiple data streams

[0134] In an optional implementation, if the service identifier of the business traffic determines that a certain service quality indicator (such as bandwidth, packet loss rate, and latency) has high requirements, the quality coefficient of the corresponding item can be increased. By adjusting the quality coefficient and the proportional coefficient, differentiated service routing for different types of business traffic can be achieved.

[0135] S503. Based on the network topology, the service quality metric value is iteratively calculated by the ant colony algorithm to determine the minimum service quality metric value, and the local network corresponding to the minimum service quality metric value is determined as the target transmission network in the SDN network, and the routing configuration information of the target transmission network is determined.

[0136] In this step, in order to minimize the average service quality metric value of multiple data streams, the service quality metric value can be iteratively calculated through the ant colony algorithm based on the network topology relationship to determine the minimum service quality metric value, and the local network corresponding to the minimum service quality metric value in the SDN network is determined as the target transmission network, and the routing configuration information of the target transmission network is determined.

[0137] It should be noted that this solution models and analyzes multiple data flows, obtaining the average remaining bandwidth, average packet loss rate, and average latency of these flows with the goal of minimizing the average quality of service (QoS) metric for these flows. In the actual routing calculation process, the routing configuration information for each service flow at its local optimum can be used. This means that each service flow is matched to the optimal QoS of the current SDN network traffic. This results in the minimum QoS metric for that service flow, along with the target transport network, and the routing configuration for that service flow is then determined.

[0138] In an optional implementation, the minimum quality of service metric value may be determined through the following steps ①②③.

[0139] Step ①: Based on the network topology and the service identifier of the business traffic, determine the Tth pheromone of each link in the SDN network in the Tth calculation.

[0140] Where T = 1, 2, ..., o. Where o is the preset threshold of the number of iterations; the service identifier of the business traffic can be used as a constraint condition for determining the target transmission network. For links that do not meet the constraint conditions, they can be directly excluded from the routing selection.

[0141] Step ②: Update the pheromone matrix according to the mth pheromone of each link in the SDN network until the number of iterations reaches the preset number to obtain the target pheromone matrix.

[0142] The pheromone matrix is ​​used to record the pheromone concentration on each link.

[0143] Step ③: Calculate the minimum service quality metric value based on the target pheromone matrix.

[0144] For ease of understanding, we will use the example of calculating the minimum QoS metric for a single service flow. In this process, the SDN network can be represented as a directed graph G(V, E), where V represents the set of nodes in the SDN network and E represents the set of directed edges in the SDN network. For node v i The set of adjacent nodes, the number of ants in the ant colony is m; represents the state transition probability of ant k from node i to node j at time t, which is defined as follows:

[0145]

[0146] In formula (5), θ is is the pheromone constant adjustment coefficient from node i to node s; represents the node that ant k can reach next at time t; Vi(t) is the node where ant k is located at time t. It is the taboo table for the next step to reach the node.

[0147] Among them, the pheromone constant adjustment coefficient θ is It can be adjusted based on other algorithms (such as genetic algorithms) combined with the real-time performance of the network. During the entire pathfinding process, ant k must avoid the nodes in the taboo table. The nodes in the taboo table are the nodes that ant k has already passed through to avoid forming a loop.

[0148] Optionally, the pheromone update rule on the link (i, j)∈E at time (t+n) can be obtained by the following calculation formula:

[0149]

[0150] In formula (6), ρ represents the pheromone volatility coefficient; 1-ρ represents the pheromone residual factor, and the value range of ρ is (0, 1); Δτ ij (t) represents the current cycle path eij The pheromone increment on.

[0151] In a specific embodiment, in order to avoid the algorithm from converging to a non-global optimal solution prematurely and stagnation in the search, when the pheromone τ ij (t+n) is greater than τ max When τ is limited to an extreme value max ; pheromone τ ij (t+n) is less than τ min When τ is limited to an extreme value min .

[0152] Furthermore, the following calculation formula can be used to obtain the number of ants that stay on path e in this cycle: ij Pheromones on:

[0153]

[0154] In formula (7), Usually a scalar, Q represents the service quality metric constant offset, which is used to adjust the service quality metric, Q k G represents the service quality metric value corresponding to the path of the kth valid ant in this cycle. The smaller the service quality metric value, the better the service quality of the path. k represents the pheromone gain coefficient of the kth effective ant, L k Represents the number of path hops. Valid ants are ants that successfully find their way from the source node to the target node, and their number can be X and less than or equal to m.

[0155] Specifically, the pheromone gain coefficient of the kth effective ant can be obtained by the following calculation formula:

[0156] G k =Gn k Formula (8)

[0157] In formula (7), G represents the pheromone gain constant, n k Represents the ranking of the kth valid ant.

[0158] Specifically, in the ranking-based ant colony algorithm, ants can be ranked according to their path quality (e.g., path length, objective function value). Ants with the best path quality are ranked highest. k Starting from 1 (representing the best ant, such as the ant with the shortest path), the number increases in sequence. k The smaller the G k The larger the value is, the faster the pheromone increase on the path with better service quality performance will be, which will accelerate the convergence of the algorithm.

[0159] For example, after sorting the path qualities of the effective ants, the first ant is the best (with the shortest path); then n k =1; the second ant is suboptimal, then n k =2; and so on, until the worst ant n k =X (X is the number of effective ants in the total number of ants m).

[0160] Specifically, k The smaller the G k The larger the value, combined with formula (7), the Tth pheromone of each link in the path of the kth valid ant in this cycle (i.e., the Tth iteration calculation) can be calculated. For the paths of invalid ants or links that valid ants do not pass through, the pheromone will gradually evaporate and decrease. After each iteration, the pheromone matrix can be updated based on the T pheromones, and the next ant colony random pathfinding can be performed. After the number of iterations reaches the preset number o, the path with the highest pheromone concentration can be selected from the target pheromone matrix as the optimal path, and the service quality metric value of the optimal path can be determined.

[0161] Furthermore, based on the minimum service quality metric value, the local network corresponding to the minimum service quality metric value can be determined as the target transmission network in the SDN network, and the routing configuration information of the target transmission network can be determined to allocate the traffic network with the best service quality to the business traffic, thereby maximizing the network transmission performance.

[0162] For example, when a bank system processes utility bill payments, it generates service flow 1. Based on the minimum QoS metric, the local network corresponding to the minimum QoS metric can be identified as the target transmission network in the SDN network. This target transmission network includes SDN switch 1 at the edge layer, SDN switch 2 at the aggregation layer, and SDN switch 3 at the core layer. Furthermore, flow entries and metering entries can be configured for SDN switch 1, flow entries and port queues for SDN switch 2, and flow entries for SDN switch 3. Service flow 1 is assigned to the traffic network with the best QoS, maximizing network transmission performance.

[0163] In an embodiment of the present application, during the process of routing and forwarding service traffic, a quality of service (QoS) metric of the SDN network can be determined based on the average remaining bandwidth, average packet loss rate, and average latency of the link. Based on the network topology, an ant colony algorithm is used to iteratively calculate the QoS metric to determine the minimum QoS metric. The local network corresponding to the minimum QoS metric is then identified as the target transmission network in the SDN network, and routing configuration information for the target transmission network is determined. Furthermore, based on the target transmission network and routing configuration information, the traffic network with the optimal QoS can be allocated to the service traffic, thereby improving the overall network transmission performance.

[0164] Figure 6 This is the architecture diagram of the service traffic scheduling system provided in the embodiment of this application. Figure 6 The service traffic scheduling system architecture can be divided into a control plane and a data plane. The control plane can be composed of an SDN controller 60, which provides a global SDN network view monitoring, realizes all-round processing and analysis at all levels of the network, and completes fine-grained comprehensive scheduling of network traffic.

[0165] The data plane is composed of SDN switches 61, which interact with the SDN controller 60 through an interface protocol. On the one hand, they report network resource information and status, and on the other hand, they receive instructions issued by the SDN controller 60 and complete specific business traffic processing according to these instructions.

[0166] Optionally, the SDN controller 60 may include: a topology discovery module 601 , a performance monitoring module 602 , a storage management module 603 , a network element configuration module 604 , a task scheduling module 605 , and a route calculation module 606 .

[0167] The topology discovery module 601 can explore network topology information in real time, including node discovery, link discovery, and host discovery.

[0168] The performance monitoring module 602 can measure the network performance indicators of all links in real time, including throughput, packet loss rate and delay.

[0169] The storage management module 603 can store the full network control and data platform information in real time, including network topology information, network performance indicators, routing calculation results, and network element configuration information. It can synchronize with each module in real time and provide the stored information to each module for calling.

[0170] The network element configuration module 604 can send control instructions to the SDN switch based on the routing calculation results, including configuration information such as flow table entries, metering table entries, port queues, etc. Among them, the flow table entries complete the forwarding matching function, and the metering table entries and port queues complete the current limiting function.

[0171] The task scheduling module 605 can serve as a routing calculation initiation module, responsible for initiating the initial routing calculation task of the service traffic for the first time and regularly initiating the rerouting calculation task of the service traffic with large data volume, long time and high service quality requirements.

[0172] After obtaining the information of the storage management module, the routing calculation module 606 can use the network topology relationship, network performance indicators, and service identifiers (differentiated service values) of business traffic as algorithm inputs, calculate the optimal service quality route through the adaptive ant colony algorithm, and generate all flow table items, metering table items, and port queue information of the routing link.

[0173] In a specific embodiment, when the service traffic scheduling system is working, the topology discovery module 601 and the performance monitoring module 602 can detect the network topology relationship and network performance indicators in real time and save them to the storage management module 603; when the first message of the service traffic enters the network, the SDN switch can pass the message to the SDN controller, and the task scheduling module 605 parses the message and calls the route calculation module 606 through the initial route calculation task mode, or calls the route calculation module 606 through the timed rerouting calculation task mode when there is no data flow trigger; the route calculation module 606 reads the global network information stored and managed, including network topology information, network performance indicators, and service identifiers based on service traffic, and calculates the route based on the network topology information, network performance indicators, and service identifiers based on service traffic using the ant colony algorithm, and generates various table entries. After receiving the route configuration information from the route calculation module 606, the network element configuration module 604 can send the corresponding configuration message to the SDN switch involved in the route to complete the table entry and queue configuration.

[0174] The service traffic scheduling system of the SDN network provided in the embodiment of the present application can refer to the technical solution shown in the above method embodiment for the specific execution process of processing service traffic. Its implementation principles and beneficial effects are similar and will not be repeated here.

[0175] Figure 7 This is a schematic diagram of the structure of the service flow processing device provided in the embodiment of the present application. Figure 7 , the service flow processing device 70 includes:

[0176] An acquisition module 71 is used to acquire the network topology and network performance indicators of the SDN network;

[0177] a processing module 72 configured to determine routing configuration information for the service traffic based on the network topology, the network performance indicators, and the quality of service requirements of the service traffic, wherein the routing configuration information is used to indicate a target transmission network for the service traffic when the quality of service is optimal in the SDN network;

[0178] The routing and forwarding module 73 is used to route and forward the service traffic according to the routing configuration information.

[0179] The service traffic processing device provided in the embodiment of the present application can execute the technical solution shown in the above method embodiment. Its implementation principle and beneficial effects are similar and will not be repeated here.

[0180] In a possible implementation, the processing module 72 is specifically configured to:

[0181] Determining a service identifier of the business flow according to a quality of service requirement of the business flow;

[0182] The network topology relationship, the network performance indicators and the service identifier of the business traffic are processed by the ant colony algorithm to determine the routing configuration information of the business traffic, wherein the routing configuration information includes the target transmission network, flow table items, metering table items and port queue information corresponding to the business traffic.

[0183] In a possible implementation, the network performance indicators include average remaining bandwidth, average packet loss rate, and average latency; the processing module 72 is specifically configured to:

[0184] Determining the average remaining bandwidth, the average packet loss rate, and the average delay;

[0185] Determining a quality of service metric of the SDN network according to the average remaining bandwidth, the average packet loss rate, and the average delay;

[0186] Based on the network topology relationship and the service identifier of the business traffic, the service quality metric value is iteratively calculated by the ant colony algorithm to determine the minimum service quality metric value, and the local network corresponding to the minimum service quality metric value is determined as the target transmission network in the SDN network, and the routing configuration information of the target transmission network is determined.

[0187] In a possible implementation, the processing module 72 is specifically configured to:

[0188] In the SDN network, determining an nth real-time bandwidth of an nth data flow in each link segment;

[0189] Determine the nth remaining bandwidth of each link segment based on the preset bandwidth of each link segment and the nth real-time bandwidth;

[0190] Determine the nth minimum remaining bandwidth among the nth remaining bandwidths of each link;

[0191] An average value of the sum of the n minimum residual bandwidths is determined as the average residual bandwidth.

[0192] In a possible implementation, the processing module 72 is specifically configured to:

[0193] In the SDN network, determining an nth successful transmission rate of an nth data flow on each link;

[0194] Determining the packet loss rate of the nth data stream according to the product of the nth successful transmission rates on each link;

[0195] The average value of the sum of the packet loss rates of the n data streams is determined as the average packet loss rate.

[0196] In a possible implementation, the processing module 72 is specifically configured to:

[0197] In the SDN network, determining a transmission time of multiple messages in an nth data flow on each link;

[0198] The average value of the sum of the transmission time of multiple messages on each link is determined as the nth transmission delay;

[0199] An average value of the sum of the n transmission delays is determined as the average delay.

[0200] In a possible implementation, the processing module 72 is specifically configured to:

[0201] Determining, in a T-th calculation, a T-th pheromone of each link in the SDN network based on the network topology and the service identifier of the business traffic;

[0202] According to the Tth pheromone of each link in the SDN network, the pheromone matrix is ​​updated until the number of iterations reaches a preset number to obtain a target pheromone matrix;

[0203] A minimum quality of service metric value is calculated based on the target pheromone matrix.

[0204] The service traffic processing device provided in the embodiment of the present application can execute the technical solution shown in the above method embodiment. Its implementation principle and beneficial effects are similar and will not be repeated here.

[0205] Figure 8 This is a schematic diagram of the structure of the electronic device provided in the embodiment of the present application. Figure 8 The electronic device 80 may be an SDN controller, including at least one processor 81 and a memory 82. Optionally, the electronic device 80 further includes a communication component 83. The processor 81, the memory 82, and the communication component 83 are connected via a bus 84.

[0206] During the specific implementation process, at least one processor 81 executes the computer-executable instructions stored in the memory 82, so that the at least one processor 81 performs the above method.

[0207] The specific implementation process of the processor 81 can be found in the above-mentioned method embodiment. Its implementation principle and technical effects are similar and will not be repeated here in this embodiment.

[0208] In the above embodiments, it should be understood that the processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the present invention may be directly implemented by a hardware processor or implemented by a combination of hardware and software modules in the processor.

[0209] The memory may include a high-speed memory (Random Access Memory, RAM), and may also include a non-volatile memory (NVM), such as at least one disk memory.

[0210] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. Buses can be classified into address buses, data buses, and control buses. For ease of illustration, the buses in the drawings of this application are not limited to just one bus or just one type of bus.

[0211] The present application also provides a computer program product, including a computer program, which implements the above method when executed by a processor.

[0212] The present application also provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the above method is implemented.

[0213] The above-mentioned readable storage medium can be implemented by any type of volatile or non-volatile memory device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The readable storage medium can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0214] An exemplary readable storage medium is coupled to a processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be an integral part of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (ASIC). Of course, the processor and the readable storage medium can also exist in the device as discrete components.

[0215] The division of units is merely a logical functional division; actual implementations may employ alternative divisions, such as combining or integrating multiple units or components into another system, or omitting or disabling certain features. Furthermore, any direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between devices or units, either through an interface, electrical, mechanical, or other means.

[0216] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0217] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0218] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, and other media that can store program code.

[0219] Those skilled in the art will appreciate that all or part of the steps in the above-described method embodiments can be implemented using hardware associated with program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0220] Finally, it should be noted that those skilled in the art will readily identify other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses, or adaptations of the present invention that follow the general principles of the present invention and include common knowledge or customary techniques in the art not disclosed herein. The present invention is not limited to the precise structure described above and illustrated in the accompanying drawings, and various modifications and variations may be made without departing from the scope thereof. The scope of the present invention is limited solely by the appended claims.

Claims

1. A method for processing business traffic, characterized in that: include: Obtain the network topology and network performance indicators of the SDN network; Determine routing configuration information for the service traffic based on the network topology, the network performance indicators, and the service quality requirements of the service traffic, wherein the routing configuration information is used to indicate a target transmission network for the service traffic when the service quality is optimal in the SDN network; The service traffic is routed and forwarded according to the routing configuration information.

2. The method according to claim 1, characterized in that Determining the routing configuration information of the business traffic according to the network topology relationship, the network performance index, and the service quality requirement of the business traffic includes: determining the service identifier of the business traffic according to the service quality requirement of the business traffic; The network topology relationship, the network performance indicators and the service identifier of the business traffic are processed by the ant colony algorithm to determine the routing configuration information of the business traffic, wherein the routing configuration information includes the target transmission network, flow table items, metering table items and port queue information corresponding to the business traffic.

3. The method according to claim 2, characterized in that The network performance indicators include average remaining bandwidth, average packet loss rate, and average delay; the network topology relationship, the network performance indicators, and the service identifier of the business traffic are processed by the ant colony algorithm to determine the routing configuration information of the business traffic, including: Determining the average remaining bandwidth, the average packet loss rate, and the average delay; Determining a quality of service metric of the SDN network according to the average remaining bandwidth, the average packet loss rate, and the average delay; Based on the network topology relationship and the service identifier of the business traffic, the service quality metric value is iteratively calculated by the ant colony algorithm to determine the minimum service quality metric value, and the local network corresponding to the minimum service quality metric value is determined as the target transmission network in the SDN network, and the routing configuration information of the target transmission network is determined.

4. The method according to claim 3, characterized in that The determining the average remaining bandwidth includes: In the SDN network, determining an nth real-time bandwidth of an nth data flow in each link segment; Determine the nth remaining bandwidth of each link segment based on the preset bandwidth of each link segment and the nth real-time bandwidth; Determine the nth minimum remaining bandwidth among the nth remaining bandwidths of each link; An average value of the sums of the n minimum residual bandwidths is determined as the average residual bandwidth.

5. The method according to claim 3, characterized in that The determining the average packet loss rate includes: In the SDN network, determining an nth successful transmission rate of an nth data flow on each link; Determining the packet loss rate of the nth data stream according to the product of the nth successful transmission rates on each link; The average value of the sum of the packet loss rates of the n data streams is determined as the average packet loss rate.

6. The method according to claim 3, characterized in that The determining the average delay includes: In the SDN network, determining a transmission time of multiple messages in an nth data flow on each link; The average value of the sum of the transmission time of multiple messages on each link is determined as the nth transmission delay; An average value of the sum of the n transmission delays is determined as the average delay.

7. The method according to any one of claims 3 to 6, characterized in that: The iterative calculation of the service quality metric value based on the network topology relationship and the service identifier of the business traffic by using the ant colony algorithm to determine the minimum service quality metric value includes: Determining, in a T-th calculation, a T-th pheromone of each link in the SDN network based on the network topology and the service identifier of the business traffic; According to the Tth pheromone of each link in the SDN network, the pheromone matrix is ​​updated until the number of iterations reaches a preset number to obtain a target pheromone matrix; A minimum quality of service metric value is calculated based on the target pheromone matrix.

8. A device for processing business traffic, characterized in that: include: The acquisition module is used to obtain the network topology and network performance indicators of the SDN network; a processing module, configured to determine routing configuration information of the service traffic based on the network topology, the network performance indicators, and the quality of service requirements of the service traffic, wherein the routing configuration information is used to indicate a target transmission network for the service traffic when the quality of service is optimal in the SDN network; The routing and forwarding module is used to route and forward the service traffic according to the routing configuration information.

9. An electronic device, characterized in that: include: Memory, processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory, so that the processor performs the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 7 when executed by a processor.

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