Intelligent gateway communication method, system and device and storage medium

Abstract

The invention discloses an intelligent gateway communication method, system and device and a storage medium, and relates to the technical field of artificial intelligence. The method comprises the following steps: when an identity authentication module identifies an access request of network flow data, performing security authentication on the network flow data, and determining the network flow data passing the security authentication as to-be-transmitted flow data; determining a target routing path of the to-be-transmitted traffic data through an intelligent routing module according to the current traffic state and the time sequence matrix of the to-be-transmitted traffic data, and feeding back the target routing path to a controller; and determining a target transmission path of the to-be-transmitted data through the service grid module according to the target routing path and the current traffic state of the network traffic data, and transmitting the target transmission path to a controller, so as to transmit the to-be-transmitted data through the controller by adopting the target transmission path. According to the technical scheme, the reliability and safety of network flow transmission can be improved.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of computer technology and can be used in the field of financial technology, especially in the field of artificial intelligence, and specifically relate to an intelligent gateway communication method, system, device and storage medium. Background Art

[0002] A gateway device is a network device that is primarily used to connect different network protocols or technologies to ensure that data can be transmitted effectively between them.

[0003] Existing gateway devices primarily rely on static rules and traditional traffic management strategies. This often proves inefficient when dealing with complex and changing network environments, making it difficult to adapt to dynamically changing network traffic. For example, in terms of routing, they only support static routing strategies, which lack flexibility and cannot adapt to dynamically changing network environments, easily leading to traffic bottlenecks and wasted resources. In the face of network attacks or traffic bursts, static routing cannot quickly adjust, resulting in degraded network performance. Summary of the Invention

[0004] The present application provides an intelligent gateway communication method, system, device and storage medium to improve the reliability and security of network traffic transmission.

[0005] According to one aspect of the present application, a smart gateway communication method is provided, which is applied to a smart gateway communication system; the smart gateway communication system includes a controller, a data bus, an identity authentication module, an intelligent routing module, and a service grid module; the controller is communicatively connected to the identity authentication module, the intelligent routing module, and the service grid module via the data bus; the method includes:

[0006] When the identity authentication module identifies an access request for network traffic data, it performs security authentication on the network traffic data and determines the network traffic data that passes the security authentication as traffic data to be transmitted;

[0007] Obtaining a time series matrix of historical traffic data and the traffic data to be transmitted from the data bus through the intelligent routing module, determining a target routing path for the traffic data to be transmitted based on a current traffic state of the traffic data to be transmitted and the time series matrix, and feeding back the target routing path to the controller;

[0008] The service grid module obtains the target routing path from the controller, determines the target transmission path of the data to be transmitted based on the target routing path and the current traffic status of the network traffic data, and transmits the target transmission path to the controller so that the controller transmits the data to be transmitted using the target transmission path.

[0009] According to another aspect of the present application, an intelligent gateway communication system is provided, comprising a controller, a data bus, an identity authentication module, an intelligent routing module, and a service grid module; the controller is communicatively connected to the identity authentication module, the intelligent routing module, and the service grid module via the data bus;

[0010] The identity authentication module is used to perform security authentication on the network traffic data when identifying an access request for network traffic data, and determine the network traffic data that passes the security authentication as traffic data to be transmitted;

[0011] The intelligent routing module is configured to obtain a time series matrix of historical traffic data and the traffic data to be transmitted from the data bus, determine a target routing path of the traffic data to be transmitted based on a current traffic state of the traffic data to be transmitted and the time series matrix, and feed the target routing path back to the controller;

[0012] The service grid module is configured to obtain the target routing path from the controller, determine a target transmission path for the data to be transmitted based on the target routing path and a current traffic state of the network traffic data, and transmit the target transmission path to the controller;

[0013] The controller is configured to transmit the data to be transmitted using the target transmission path.

[0014] According to another aspect of the present application, an electronic device is provided, comprising:

[0015] one or more processors;

[0016] a memory for storing one or more programs;

[0017] When the one or more programs are executed by the one or more processors, the one or more processors implement any one of the intelligent gateway communication methods provided in the embodiments of the present application.

[0018] According to another aspect of the present application, a computer-readable storage medium is provided, on which a computer program is stored. When the program is executed by a processor, any one of the intelligent gateway communication methods provided in the embodiments of the present application is implemented.

[0019] According to another aspect of the present application, a computer program product is provided, including a computer program, which, when executed by a processor, implements any one of the intelligent gateway communication methods provided in the embodiments of the present application.

[0020] This application performs security authentication on the network traffic data when identifying the access request of the network traffic data through the identity authentication module, and determines the network traffic data that has passed the security authentication as the traffic data to be transmitted; obtains the time series matrix of the historical traffic data and the traffic data to be transmitted from the data bus through the intelligent routing module, and determines the target routing path of the traffic data to be transmitted according to the current traffic status and the time series matrix of the traffic data to be transmitted, and feeds back the target routing path to the controller; obtains the target routing path from the controller through the service grid module, and determines the target transmission path of the data to be transmitted according to the target routing path and the current traffic status of the network traffic data, and transmits the target transmission path to the controller, so that the controller adopts the target transmission path to transmit the data to be transmitted. The above technical solution transforms the independent functions of the traditional gateway into an intelligent module, and realizes dynamic collaboration through the data bus and the controller, breaking through the limitations of the static configuration of the traditional gateway and helping to improve the reliability and security of network traffic transmission. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 This is a flow chart of an intelligent gateway communication method provided according to the first embodiment of the present application;

[0022] Figure 2 This is a flow chart of an intelligent gateway communication method provided according to the second embodiment of the present application;

[0023] Figure 3 This is a structural diagram of an intelligent gateway communication system provided according to the third embodiment of the present application;

[0024] Figure 4 It is a structural diagram of an electronic device that implements the intelligent gateway communication method of Example 4 of the present application. DETAILED DESCRIPTION

[0025] In order to enable those skilled in the art to better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of this application.

[0026] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in a sequence other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0027] In addition, it should be noted that in the technical solution of this application, the collection, storage, use, processing, transmission, provision and disclosure of relevant data such as network traffic data and historical traffic data are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0028] Example 1

[0029] Figure 1 This is a flow chart of an intelligent gateway communication method provided in accordance with the first embodiment of the present application. This embodiment is applicable to the case of automatic dynamic routing selection of intelligent gateways and can be executed by an intelligent gateway communication system. The intelligent gateway communication system can be implemented in the form of hardware and / or software. The intelligent gateway communication system can be configured in a computer device, such as an intelligent gateway communication system. The intelligent gateway communication system includes a controller, a data bus, an identity authentication module, an intelligent routing module, and a service grid module. The controller is respectively connected to the identity authentication module, the intelligent routing module, and the service grid module via a data bus. Figure 1 As shown, the method includes:

[0030] S110. When an access request for network traffic data is identified through the identity authentication module, security authentication is performed on the network traffic data, and the network traffic data that passes the security authentication is determined as traffic data to be transmitted.

[0031] In this embodiment, the controller is the core component of the intelligent gateway communication system, responsible for coordinating the operations of the system's various modules. It connects to the identity authentication module, intelligent routing module, and service mesh module via a data bus, controlling the workflow of these modules and ensuring smooth and secure data flow. The data bus serves as a communication channel between the system's modules, ensuring efficient information transmission between them. Through the data bus, the modules can share and transfer essential data, such as network traffic data and routing information. The identity authentication module performs identity and security authentication on network traffic data entering the intelligent gateway. Upon receiving an access request, it verifies the legitimacy of the data to ensure that only authenticated data can enter the system. This process helps prevent malicious attacks and data leaks. The intelligent routing module determines the optimal routing path based on historical traffic data and current traffic conditions. It uses AI algorithms to analyze the time series of historical traffic data to determine the optimal data transmission route and ensure efficient data transmission from source to destination. The service mesh module manages and optimizes network traffic in the intelligent gateway communication system, providing load balancing and traffic management capabilities. By configuring traffic policies, it controls and optimizes traffic flow between services, enabling efficient communication and management between services. Network traffic data refers to the information or data packets transmitted across a computer network; it includes data transmissions, access requests, and communication protocols. Pending traffic data refers to data that the system has determined can be transmitted after identity authentication; this data has been securely verified and is ready for transmission over the network.

[0032] Specifically, the identity authentication module receives an authentication request from the data bus, performs security authentication on the network flow data, determines the network flow data that passes the security authentication as the flow data to be transmitted, and exchanges the authentication result with the controller module.

[0033] Furthermore, the identity authentication module can be used to perform identity authentication based on machine learning algorithms, identify abnormal behaviors through behavioral analysis models, dynamically allocate and adjust rights, and implement dynamic identity authentication and rights management for access applications to ensure network security.

[0034] In this embodiment, the behavioral analysis model refers to a technology that identifies abnormal activities and potential risks by analyzing and learning user or system behavior patterns. In the field of network security, the application of behavioral analysis models can help dynamically verify identities, detect fraud, and promptly discover potential security threats. Unlike traditional security systems based on passwords or static identity authentication, behavioral analysis focuses on user behavior habits and interaction patterns for identity authentication and permission management.

[0035] S120. Obtain the time series matrix of historical traffic data and the traffic data to be transmitted from the data bus through the intelligent routing module, and determine the target routing path of the traffic data to be transmitted based on the current traffic state and the time series matrix of the traffic data to be transmitted, and feed back the target routing path to the controller.

[0036] In this embodiment, historical traffic data refers to the traffic records transmitted in the network within a certain period of time; these data include the accumulation of information such as various types of communication activities, data packet transmission volume, connection requests, etc. in the network, and are usually recorded and stored in time series. The time series matrix records the changing trends of network traffic over a period of time in the past; it helps the intelligent routing module predict future traffic changes by analyzing the changing patterns of historical traffic, thereby selecting the most suitable routing path. The current traffic status refers to the distribution and traffic level of traffic in the network at a specific moment; by monitoring the current traffic, the intelligent routing module can determine the load situation of the network and optimize the data transmission path. The target routing path is the optimal data transmission path determined by the intelligent routing module based on the current traffic status and historical traffic data; it guides the specific path for data to reach the target from the source.

[0037] For example, the intelligent routing module obtains the traffic data to be transmitted from the data bus, monitors the traffic status in real time through machine learning (such as reinforcement learning, deep learning, etc.), trains the AI ​​model, analyzes the network traffic, predicts the optimal routing path, and transmits the analysis results back to the controller module to ensure the best selection of the traffic path.

[0038] S130. Obtain a target routing path from the controller through the service grid module, determine a target transmission path for the data to be transmitted based on the target routing path and the current traffic status of the network traffic data, and transmit the target transmission path to the controller so that the controller transmits the data to be transmitted using the target transmission path.

[0039] In this embodiment, the target transmission path refers to the actual data transmission path determined by the service grid module based on the target routing path and the current traffic status; it is the actual route when data is transmitted in the network, and is intended to ensure smooth, efficient and secure data transmission.

[0040] In an optional embodiment, the intelligent gateway communication system also includes a data cache module; the data cache module is communicatively connected to the controller via a data bus; accordingly, historical traffic data is obtained from the data bus via the data cache module, and cacheable data is determined from the historical traffic data based on the data access pattern and data access frequency of the historical traffic data; cacheable data is obtained from the data bus via the data cache module and saved.

[0041] In this embodiment, the data cache module is a key component responsible for storing and managing historical traffic data; it is used to cache frequently used data. Data access patterns refer to the way and regularity in which data is accessed, including access frequency, access time, etc.; by analyzing these patterns, the system can determine which data is accessed more frequently, so that it can choose to cache these data to improve system performance. Data access frequency refers to the number of times a certain data is requested or accessed; frequently accessed data is usually cached to reduce access latency and improve system efficiency. Cacheable data refers to data that is suitable for storage in the cache due to its high access frequency or importance; caching this data can reduce the need to access remote storage, thereby speeding up data processing.

[0042] Furthermore, the data access pattern and data access frequency of the historical traffic data are weightedly summed through the data caching module to obtain the data importance score of the historical traffic data; the historical traffic data whose data importance score meets the data caching conditions is determined as cacheable data through the data caching module.

[0043] In this embodiment, the data importance score is a metric derived from a weighted summation of historical traffic data, used to measure the value of the data and its impact on system performance. Data caching conditions refer to a set of criteria or rules used to determine which data should be cached; for example, the condition may be that the data importance score is greater than or equal to an importance score threshold.

[0044] It is understandable that real-time monitoring of the cache status and dynamic adjustment of cacheable data based on factors such as changes in network traffic and access patterns can help reduce network latency and improve data transmission efficiency.

[0045] The embodiment of the present application performs security authentication on the network traffic data when identifying the access request of the network traffic data through the identity authentication module, and determines the network traffic data that has passed the security authentication as the traffic data to be transmitted; obtains the time series matrix of the historical traffic data and the traffic data to be transmitted from the data bus through the intelligent routing module, and determines the target routing path of the traffic data to be transmitted according to the current traffic status and the time series matrix of the traffic data to be transmitted, and feeds back the target routing path to the controller; obtains the target routing path from the controller through the service grid module, and determines the target transmission path of the data to be transmitted according to the target routing path and the current traffic status of the network traffic data, and transmits the target transmission path to the controller, so that the controller adopts the target transmission path to transmit the data to be transmitted. The above technical solution transforms the independent functions of the traditional gateway into an intelligent module, and realizes dynamic collaboration through the data bus and the controller, breaking through the limitations of the static configuration of the traditional gateway and helping to improve the reliability and security of network traffic transmission.

[0046] Example 2

[0047] Figure 2 This is a flow chart of an intelligent gateway communication method provided in accordance with the second embodiment of the present application. Based on the technical solutions of the above embodiments, this embodiment refines "determining the target routing path of the traffic data to be transmitted according to the current traffic status and time series matrix of the traffic data to be transmitted through the intelligent routing module" into "extracting features from the time series matrix through the intelligent routing module to obtain candidate time series features; performing tensor splicing on the candidate time series features and the real-time indicators of the current traffic status through the intelligent routing module to obtain a mixed feature vector; determining the target routing path of the traffic data to be transmitted according to the mixed feature vector, the current traffic status and the current network topology of the intelligent gateway communication system through the intelligent routing module". It should be noted that for the parts not described in detail in the embodiments of the present application, please refer to the relevant statements of other embodiments. Figure 2 As shown, the method includes:

[0048] S210. When the identity authentication module identifies an access request for network traffic data, it performs security authentication on the network traffic data and determines the network traffic data that passes the security authentication as traffic data to be transmitted.

[0049] S220 , obtaining a time series matrix of historical traffic data and traffic data to be transmitted from the data bus through an intelligent routing module, and performing feature extraction on the time series matrix to obtain candidate time series features.

[0050] In this embodiment, candidate time series features refer to preliminary features extracted from time series data. These features are representative and are used for subsequent model training or analysis. Exemplarily, the features can be statistical features, frequency domain features, autocorrelation features, trend features, time domain features, complexity features, etc.

[0051] S230. Perform tensor splicing on the candidate time series features and the real-time indicators of the current traffic state through the intelligent routing module to obtain a mixed feature vector.

[0052] In this example, tensor concatenation combines multiple tensors (i.e., multidimensional arrays) of different dimensions into a single larger tensor. This is commonly used in deep learning models to help integrate information from different sources. Hybrid feature vectors combine features from different sources (such as candidate features and real-time indicators of current traffic conditions) to form a more comprehensive feature vector for further model processing and decision-making.

[0053] S240. Determine the target routing path of the traffic data to be transmitted through the intelligent routing module according to the hybrid feature vector, the current traffic state, and the current network topology of the intelligent gateway communication system, and feed back the target routing path to the controller.

[0054] In this embodiment, the current traffic status refers to the flow of data to be transmitted, including network performance indicators such as bandwidth utilization, latency, and packet loss rate, reflecting the health of the network. The current network topology refers to the structure of the nodes (such as servers, routers, switches, etc.) and their connections in the intelligent gateway communication system network, which determines the data propagation path and efficiency in the network.

[0055] Optionally, the intelligent routing module is based on a graph search algorithm to determine at least one candidate routing path according to the current traffic status and the current network topology of the intelligent gateway communication system; the intelligent routing module is based on a reinforcement learning algorithm to determine the target routing path for the traffic data to be transmitted according to the mixed feature vector and at least one candidate routing path.

[0056] In this embodiment, the graph search algorithm is an algorithm for finding a specific path or node in a graph structure; in a network, a routing problem can usually be converted into a graph search problem, with each node of the network (such as routers, switches, etc.) serving as a node of the graph, and the network links connecting them serving as edges. The candidate routing paths are multiple possible routing paths selected by the intelligent routing module based on the current network topology, traffic status, and predetermined network goals (such as minimizing latency or maximizing bandwidth). The reinforcement learning algorithm is a machine learning method that learns strategies through interaction with the environment, enabling an intelligent agent (such as a routing module) to optimize its behavior strategy through a reward or penalty mechanism; in the scenario of network routing, the reinforcement learning algorithm can select the optimal route in real time based on the current traffic status and network topology; the routing module can gradually adjust its own strategy through interaction with the network through reinforcement learning, so that it can dynamically adapt to changes in the network environment.

[0057] Furthermore, the mixed feature vector is input into a pre-trained reinforcement learning model through the intelligent routing module to output a score value for each candidate routing path; wherein, the reinforcement learning model is trained through historical path selection decisions and corresponding network performance feedback data; and the candidate routing path whose score meets the path generation conditions is determined as the target routing path through the intelligent routing module.

[0058] In this embodiment, the score value is a numerical value obtained by evaluating each candidate routing path through a reinforcement learning model; this value reflects the quality of the path and usually includes multiple factors (such as delay, bandwidth, packet loss rate, etc.); the higher the score value, the more suitable the path is for data transmission under the current network state. Path generation conditions refer to certain specific conditions that need to be met when selecting a candidate routing path; this condition is artificially set based on actual conditions or empirical values, and this embodiment of the application does not specifically limit this; for example, the condition can be that the score value is greater than or equal to the score value threshold, the bandwidth of the path meets a certain threshold, the delay cannot be too high, the packet loss rate must be lower than a certain standard, etc.; only paths that meet these conditions will be considered valid candidate paths.

[0059] S250. Obtain a target routing path from the controller through the service grid module, determine a target transmission path for the data to be transmitted based on the target routing path and the current traffic status of the network traffic data, and transmit the target transmission path to the controller so that the controller transmits the data to be transmitted using the target transmission path.

[0060] The embodiment of the present application performs security authentication on the network traffic data when identifying an access request for network traffic data through the identity authentication module, and determines the network traffic data that has passed the security authentication as the traffic data to be transmitted; obtains the time series matrix of historical traffic data and the traffic data to be transmitted from the data bus through the intelligent routing module, and extracts features from the time series matrix to obtain candidate time series features; performs tensor splicing on the candidate time series features and the real-time indicators of the current traffic state through the intelligent routing module to obtain a mixed feature vector; determines the target routing path of the traffic data to be transmitted based on the mixed feature vector, the current traffic state and the current network topology of the intelligent gateway communication system through the intelligent routing module, and feeds the target routing path back to the controller; obtains the target routing path from the controller through the service grid module, and determines the target transmission path of the data to be transmitted based on the target routing path and the current traffic state of the network traffic data, and transmits the target transmission path to the controller so that the controller adopts the target transmission path to transmit the data to be transmitted. The above technical solution transforms the independent functions of the traditional gateway into an intelligent module, and realizes dynamic collaboration through the data bus and the controller, breaking through the limitations of the static configuration of the traditional gateway and helping to improve the reliability and security of network traffic transmission.

[0061] Example 3

[0062] Figure 3This is a structural diagram of an intelligent gateway communication system provided in accordance with the third embodiment of the present application, which is applicable to the case of automatic dynamic routing selection of intelligent gateways. The intelligent gateway communication system can be implemented in the form of hardware and / or software, and can be configured in a computer device, such as a server. Figure 3 As shown, the system includes a controller 10, a data bus 20, an identity authentication module 30, an intelligent routing module 40 and a service grid module 50; the controller 10 is respectively connected to the identity authentication module 30, the intelligent routing module 40 and the service grid module 50 via the data bus 20;

[0063] The identity authentication module 30 is used to perform security authentication on the network traffic data when identifying an access request for network traffic data, and determine the network traffic data that passes the security authentication as traffic data to be transmitted;

[0064] The intelligent routing module 40 is used to obtain the time series matrix of historical traffic data and the traffic data to be transmitted from the data bus 20, and determine the target routing path of the traffic data to be transmitted based on the current traffic state and the time series matrix of the traffic data to be transmitted, and feed the target routing path back to the controller 10;

[0065] The service grid module 50 is configured to obtain a target routing path from the controller 10, determine a target transmission path for the data to be transmitted based on the target routing path and the current traffic state of the network traffic data, and transmit the target transmission path to the controller 10;

[0066] The controller 10 is configured to transmit the data to be transmitted using a target transmission path.

[0067] The embodiment of the present application performs security authentication on the network traffic data when identifying the access request of the network traffic data through the identity authentication module, and determines the network traffic data that has passed the security authentication as the traffic data to be transmitted; obtains the time series matrix of the historical traffic data and the traffic data to be transmitted from the data bus through the intelligent routing module, and determines the target routing path of the traffic data to be transmitted according to the current traffic status and the time series matrix of the traffic data to be transmitted, and feeds back the target routing path to the controller; obtains the target routing path from the controller through the service grid module, and determines the target transmission path of the data to be transmitted according to the target routing path and the current traffic status of the network traffic data, and transmits the target transmission path to the controller, so that the controller adopts the target transmission path to transmit the data to be transmitted. The above technical solution transforms the independent functions of the traditional gateway into an intelligent module, and realizes dynamic collaboration through the data bus and the controller, breaking through the limitations of the static configuration of the traditional gateway and helping to improve the reliability and security of network traffic transmission.

[0068] Optionally, the intelligent routing module 40 includes:

[0069] The feature extraction unit is used to extract features from the time series matrix through the intelligent routing module to obtain candidate time series features;

[0070] The feature splicing unit is used to perform tensor splicing on the candidate time series features and the real-time indicators of the current traffic status through the intelligent routing module to obtain a mixed feature vector;

[0071] The path determination unit is used to determine the target routing path of the traffic data to be transmitted according to the mixed feature vector, the current traffic state and the current network topology of the intelligent gateway communication system through the intelligent routing module.

[0072] Optionally, the path determination unit includes:

[0073] A path determination subunit is configured to determine at least one candidate routing path based on a graph search algorithm using an intelligent routing module and according to a current traffic state and a current network topology of the intelligent gateway communication system;

[0074] The path screening subunit is used to determine the target routing path for the traffic data to be transmitted based on the hybrid feature vector and at least one candidate routing path through the intelligent routing module based on the reinforcement learning algorithm.

[0075] Optional, path filtering subunit, specifically used to:

[0076] The intelligent routing module inputs the mixed feature vector into a pre-trained reinforcement learning model, which outputs a score for each candidate routing path. The reinforcement learning model is trained using historical path selection decisions and corresponding network performance feedback data.

[0077] The intelligent routing module determines the candidate routing path whose score meets the path generation condition as the target routing path.

[0078] Optionally, the intelligent gateway communication system further includes a data cache module; the data cache module is communicatively connected to the controller via a data bus;

[0079] The data cache module is used to obtain historical traffic data from the data bus, determine cacheable data from the historical traffic data according to the data access mode and data access frequency of the historical traffic data, and obtain and save the cacheable data from the data bus.

[0080] Optional data cache module, specifically used for:

[0081] Perform weighted summation on the data access pattern and data access frequency of historical traffic data to obtain the data importance score of the historical traffic data;

[0082] The historical traffic data whose data importance score meets the data caching conditions is determined as cacheable data.

[0083] The intelligent gateway communication system provided in the embodiments of the present application can execute the intelligent gateway communication method provided in any embodiment of the present application, and has the corresponding functional modules and beneficial effects for executing each intelligent gateway communication method.

[0084] According to an embodiment of the present application, the present application also provides an electronic device, a readable storage medium and a computer program product.

[0085] Example 4

[0086] Figure 4 4 is a schematic diagram of the structure of an electronic device 410 that implements the intelligent gateway communication method of an embodiment of the present application. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present application described and / or required herein.

[0087] like Figure 4 As shown, the electronic device 410 includes at least one processor 411, and a memory connected to the at least one processor 411 in communication, such as a read-only memory (ROM) 412, a random access memory (RAM) 413, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 411 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 412 or the computer program loaded from the storage unit 418 to the random access memory (RAM) 413. Various programs and data required for the operation of the electronic device 410 can also be stored in the RAM 413. The processor 411, ROM 412 and RAM 413 are connected to each other via a bus 414. An input / output (I / O) interface 415 is also connected to the bus 414.

[0088] Multiple components in electronic device 410 are connected to I / O interface 415, including an input unit 416, such as a keyboard, mouse, etc.; an output unit 417, such as various types of displays, speakers, etc.; a storage unit 418, such as a magnetic disk, optical disk, etc.; and a communication unit 419, such as a network card, modem, wireless communication transceiver, etc. The communication unit 419 allows electronic device 410 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0089] The processor 411 may be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of the processor 411 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 411 executes the various methods and processes described above, such as the intelligent gateway communication method.

[0090] In some embodiments, the intelligent gateway communication method may be implemented as a computer program that is tangibly contained in a computer-readable storage medium, such as a storage unit 418. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 410 via the ROM 412 and / or the communication unit 419. When the computer program is loaded into the RAM 413 and executed by the processor 411, one or more steps of the intelligent gateway communication method described above may be performed. Alternatively, in other embodiments, the processor 411 may be configured as the intelligent gateway communication method in any other appropriate manner (e.g., by means of firmware).

[0091] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0092] The computer programs for implementing the methods of the present application can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable intelligent gateway communication device, so that when the computer programs are executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer programs can be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0093] In the context of the present application, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. A computer-readable storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. A more specific example of a machine-readable storage medium can include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0094] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0095] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0096] A computing system may include clients and servers. The clients and servers are typically remote from each other and typically interact via a communication network. This client-server relationship arises through computer programs running on the respective computers, creating a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host. This server is a hosting product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosting and VPS services.

[0097] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in this application can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of this application can be achieved. This is not limited herein.

[0098] The above specific embodiments do not constitute a limitation on the scope of protection of this application. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application shall be included within the scope of protection of this application.

Claims

1. An intelligent gateway communication method, characterized in that: Applicable to intelligent gateway communication system; the intelligent gateway communication system includes a controller, a data bus, an identity authentication module, an intelligent routing module and a service grid module; The controller is respectively connected to the identity authentication module, the intelligent routing module and the service grid module via a data bus; the method includes: When the identity authentication module identifies an access request for network traffic data, it performs security authentication on the network traffic data and determines the network traffic data that passes the security authentication as traffic data to be transmitted; Obtaining a time series matrix of historical traffic data and the traffic data to be transmitted from the data bus through the intelligent routing module, determining a target routing path for the traffic data to be transmitted based on a current traffic state of the traffic data to be transmitted and the time series matrix, and feeding back the target routing path to the controller; The service grid module obtains the target routing path from the controller, determines the target transmission path of the data to be transmitted based on the target routing path and the current traffic status of the network traffic data, and transmits the target transmission path to the controller so that the controller transmits the data to be transmitted using the target transmission path.

2. The method according to claim 1, characterized in that Determining, by the intelligent routing module, a target routing path for the traffic data to be transmitted according to the current traffic state of the traffic data to be transmitted and the time series matrix, including: Extracting features from the time series matrix using the intelligent routing module to obtain candidate time series features; Performing tensor splicing on the candidate time series features and the real-time indicators of the current traffic state through the intelligent routing module to obtain a mixed feature vector; The intelligent routing module determines the target routing path of the traffic data to be transmitted according to the hybrid feature vector, the current traffic state and the current network topology of the intelligent gateway communication system.

3. The method according to claim 2, characterized in that The determining, by the intelligent routing module, a target routing path for the traffic data to be transmitted according to the hybrid feature vector, the current traffic state, and the current network topology of the intelligent gateway communication system includes: Determining, by the intelligent routing module based on a graph search algorithm, at least one candidate routing path according to the current traffic state and the current network topology of the intelligent gateway communication system; The intelligent routing module determines the target routing path of the traffic data to be transmitted based on the hybrid feature vector and the at least one candidate routing path based on a reinforcement learning algorithm.

4. The method according to claim 3, characterized in that The step of determining, by the intelligent routing module based on a reinforcement learning algorithm and according to the hybrid feature vector and the at least one candidate routing path, a target routing path for the traffic data to be transmitted includes: The hybrid feature vector is input into a pre-trained reinforcement learning model through the intelligent routing module to output a score value for each candidate routing path; wherein the reinforcement learning model is trained using historical path selection decisions and corresponding network performance feedback data; The intelligent routing module determines the candidate routing path whose score value meets the path generation condition as the target routing path.

5. The method according to claim 1, wherein The intelligent gateway communication system further includes a data cache module; the data cache module is communicatively connected to the controller via the data bus; accordingly, the method further includes: Acquire historical traffic data from the data bus through the data cache module, and determine cacheable data from the historical traffic data based on a data access pattern and a data access frequency of the historical traffic data; The cacheable data is acquired from the data bus through the data cache module and stored.

6. The method according to claim 5, characterized in that Determining cacheable data from the historical traffic data by the data caching module according to the data access pattern and the data access frequency of the historical traffic data includes: Performing weighted summation of the data access pattern and the data access frequency of the historical traffic data by the data cache module to obtain a data importance score of the historical traffic data; The historical traffic data whose data importance score meets the data caching condition is determined as cacheable data by the data caching module.

7. An intelligent gateway communication system, characterized in that: It includes a controller, a data bus, an identity authentication module, an intelligent routing module and a service grid module; the controller is respectively connected to the identity authentication module, the intelligent routing module and the service grid module via a data bus; The identity authentication module is used to perform security authentication on the network traffic data when identifying an access request for network traffic data, and determine the network traffic data that passes the security authentication as traffic data to be transmitted; The intelligent routing module is configured to obtain a time series matrix of historical traffic data and the traffic data to be transmitted from the data bus, determine a target routing path of the traffic data to be transmitted based on a current traffic state of the traffic data to be transmitted and the time series matrix, and feed the target routing path back to the controller; The service grid module is configured to obtain the target routing path from the controller, determine a target transmission path for the data to be transmitted based on the target routing path and a current traffic state of the network traffic data, and transmit the target transmission path to the controller; The controller is configured to transmit the data to be transmitted using the target transmission path.

8. An electronic device, characterized in that: include: one or more processors; a memory for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the intelligent gateway communication method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the intelligent gateway communication method according to any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements the intelligent gateway communication method according to any one of claims 1 to 6.

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