Heterogeneous network unified management method and system

Abstract

The invention provides a heterogeneous network unified management method and system. The method comprises the following steps: S1, setting a physical hardware network; s2, building a virtual control platform; s3, abstractly generating a virtual logic network on the upper layer of the physical hardware network; s4, deploying an agent program to collect data and packaging the data into standardized data; and S5, a control channel and a data channel are established, the controller issues tasks to the agent program through the control channel, and the agent program returns the standardized data through the data channel. According to the method, a physical hardware network is set to be compatible with a matching heterogeneous network, a unified centralized non-intrusive management system of business nodes special for brokerages is constructed, decoupling of a logic layer and a physical layer is achieved through an upper layer abstract technology, physical position dependence is eliminated, a virtual control platform is synchronously built, an agent program is deployed, and node data is collected in real time; and standardized protocol packaging is adopted to bypass limitation of a brokerage private protocol, so that intercommunication of heterogeneous networks is realized, and a reliable transaction environment with unified management and efficient operation and maintenance is constructed.

Description

Technical Field

[0001] The present application relates to the technical field of financial data processing, and in particular to a method and system for unified management of heterogeneous networks. Background Art

[0002] Brokerage firms play a crucial role in modern financial transactions. Investors rely on brokerage networks to obtain market information and conduct real-time transactions, significantly improving transaction efficiency. However, with the financial industry's increasing emphasis on network security, brokerage firms have built a large number of heterogeneous, closed network nodes based on their own standards. This heterogeneity is reflected not only in differences in hardware and software protocols, but also in diverging process systems and management standards across brokerage networks, making deep integration of hardware and software difficult. This, in turn, leads to a highly fragmented managed network environment.

[0003] Faced with the complex and ever-changing network environment of brokerage firms, the current mainstream approach is to develop customized network management and operations systems for each brokerage's managed network. This approach adapts to the closed nodes and protocol specifications of a specific brokerage firm to enable local network monitoring and trading channel maintenance. For example, dedicated physical equipment or customized interfaces are deployed to ensure data connectivity and trading instruction transmission with a single brokerage firm. This approach, based on the principle of divide and conquer, attempts to meet the heterogeneous needs of different brokerage firms through decentralized management, achieving basic functional operations in the short term.

[0004] Obviously, this independent development model has limitations. On the one hand, each brokerage system operates independently, lacking a unified control system. This leads to inefficient and fragmented management, resulting in skyrocketing O&M costs and difficulties in cross-network collaboration. On the other hand, reliance on customized development makes it difficult to adapt to the continuous iteration of brokerage networks, unable to quickly respond to new node management or security policy changes, and lacks scalability. Furthermore, the separation of physical layer devices from upper-layer software monitoring leads to a disconnect between software and hardware, making it difficult to achieve end-to-end reliability, dynamically optimize resource allocation, or quickly locate cross-layer faults. Therefore, there is an urgent need for a heterogeneous network system that can not only penetrate closed nodes one by one in a changing network environment, but also ensure low latency and high stability in transactions, creating a reliable trading environment with unified management and efficient O&M. Summary of the Invention

[0005] To solve the above problems, the first aspect of the present application provides a method for unified management of heterogeneous networks, comprising the following steps:

[0006] S1: Establishing a physical hardware network compatible with the heterogeneous network, wherein the physical hardware network includes a main line, a backup line, and a managed node connected to the main line or the backup line;

[0007] S2: Building a virtual control platform consisting of a controller and a logical resource pool, wherein the controller is used to dynamically schedule the logical resource pool;

[0008] S3: Perform upper-layer abstraction on the physical hardware network to generate a virtual logical network, and configure the virtual logical network to the logical resource pool;

[0009] S4: deploying an agent program in the hosting node, wherein the agent program is used to collect data of the corresponding hosting node and encapsulate it into standardized data according to a standardized protocol; and

[0010] S5: establishing a control channel and a data channel, wherein the controller issues tasks to the agent program via the control channel, and the agent program transmits the standardized data back to the controller via the data channel.

[0011] In some optional implementation methods, step S3 further includes:

[0012] S31: Using network overlay technology to build a logical network layer covering the physical hardware network;

[0013] S32: Mapping the managed nodes one by one to logical resources and merging them into the logical resource pool; and

[0014] S33: Map the physical topology of the physical hardware network to the virtual logical network in the logical network layer, and synchronize the virtual logical network to the logical resource pool.

[0015] In some optional implementation methods, relay nodes are further deployed at the access points of the main line and the backup line, and the standardized data is forwarded to the data channel via the relay node to be transmitted back to the controller.

[0016] In some optional implementation methods, the data channel further includes a line channel corresponding to a physical connection to the physical hardware network, and the allocation of traffic configuration resources for the line channel further includes the following steps:

[0017] S51: Deploy traffic controllers in the relay node and the hosting node to monitor local traffic status in real time;

[0018] S52: Allocate the line channel to the relay node and the hosting node preferentially according to the registration information of the relay node and the hosting node and the current network load;

[0019] S53: Counting the minimum value of data traffic of all relay nodes and the hosting node connected to the line channel within a recent preset period, adjusting the transmission priority of each relay node and the hosting node based on the local traffic status and service type of all relay nodes and the hosting node, allocating initial traffic configuration resources to the corresponding relay node or the hosting node, and sending the initial traffic configuration resources to the corresponding traffic controller;

[0020] S54: periodically collecting data traffic from all relay nodes and hosting nodes connected to the line channel according to the preset period, establishing a data traffic prediction model, and generating a traffic configuration resource allocation strategy in real time based on the prediction results; and

[0021] S55: Counting the sum of traffic configuration resources required by all relay nodes and hosting nodes according to the allocation strategy; when the sum exceeds the maximum resource capacity of the line channel, adaptively adjusting the resource capacity of the line channel according to the dynamic expansion strategy.

[0022] In some optional implementation methods, the step of establishing a data traffic prediction model and generating a real-time traffic configuration resource allocation strategy based on the prediction results further includes the following steps:

[0023] S541: Building a traffic configuration resource prediction model based on the traffic configuration resource data historically allocated to each relay node and / or the hosting node and the time series data of the real-time data traffic;

[0024] S542: Using a random time series model to capture the temporal autocorrelation of the relay node and / or the hosting node, and predicting future data traffic distribution; and

[0025] S543: Calculate traffic configuration resources that meet predetermined conditions for each relay node and / or hosting node according to the future data traffic distribution.

[0026] In some optional implementation methods, the adaptively adjusting the resource capacity of the line channel according to the dynamic capacity expansion strategy further includes the following steps:

[0027] S551: Establish a Sigmoid function, use the peak delay of the line channel as input of the Sigmoid function, and convert the peak delay into a capacity expansion coefficient normalized to the (0, 1) interval;

[0028] S552: Mapping the capacity expansion coefficient to an increase or decrease ratio of the resource capacity of the line channel;

[0029] S553: ​​Dynamically adjust the allocation of the resource capacity according to the increase / decrease ratio, and when the real-time data traffic of the line channel exceeds the limit value, trigger the capacity expansion strategy and increase the traffic configuration resources of all the relay nodes and the hosting nodes in the line channel in order of priority; and

[0030] S554: When the real-time data traffic of the line channel recovers to below the limit value, the rollback expansion strategy is triggered to smoothly roll back the traffic configuration resources currently obtained by the relay node and the hosting node to the initial traffic configuration resources.

[0031] In some optional implementation methods, the standardized data is transmitted in the data channel in the form of a data packet, and the transmission of the standardized data further includes the following steps:

[0032] S71: Prioritize and classify the standardized data according to business type;

[0033] S72: Setting different DSCP fields corresponding to different categories of the standardized data; and

[0034] S73: Write the DSCP field into the header of the corresponding data packet.

[0035] In some optional implementation methods, the agent program collecting data of the corresponding hosting node further includes the following steps:

[0036] S41: Divide the data of the hosting node into three data types: real-time data, continuous data, and offline data;

[0037] S42: The agent program actively collects data from the hosting node and encapsulates the data in a standardized protocol; and

[0038] S43: After receiving the standardized data transmitted back from the data channel, the controller pushes the standardized data to a designated storage server in the logical resource pool according to the data type.

[0039] In some optional implementation methods, the controller is divided into a master controller and a slave controller, there is only one master controller, and the slave controllers can switch roles based on instructions. The controller used to receive the returned standardized data is the slave controller.

[0040] A second aspect of the present application provides a heterogeneous network unified management system for executing the heterogeneous network unified management method according to any one of the above items.

[0041] This application has at least the following technical effects:

[0042] 1) The first aspect of the present application provides a method for unified management of heterogeneous networks. By establishing a physical hardware network compatible with and matching heterogeneous networks, it supports network equipment and protocols from different manufacturers, builds a unified centralized non-intrusive management system for brokerage-specific business nodes, and adopts a master-slave dual-line redundant design to avoid single point failures and ensure business continuity. On this basis, the physical hardware network is mapped into a virtual logical network through upper-layer abstraction technology to achieve decoupling of the logical layer and the physical layer, so that the virtual logical network can be freed from the constraints of the physical topology and dynamically adjusted according to business needs without the need to reconstruct the physical link, thus getting rid of the dependence on physical location and rigid configuration. The system significantly improves network flexibility and scalability by simultaneously building a virtual control platform, integrating virtualized resource pools and centrally managing virtual logical networks, thus achieving centralized management and global monitoring across heterogeneous networks. By deploying standardized agent programs, it collects managed node data in real time and encapsulates it using standardized protocols before transmitting it back. Finally, it builds a two-way communication mechanism between the control channel and the data channel. The control channel implements configuration policy delivery in seconds, while the data channel ensures efficient transmission of encrypted business flows, thus meeting the low-latency requirements of quantitative trading and ensuring data security through protocol-level encryption, thus building a reliable trading environment with unified management and efficient operation and maintenance.

[0043] 2) The second aspect of the present application provides a unified management system for heterogeneous networks. Based on the above-mentioned unified management method for heterogeneous networks, the unified management system for heterogeneous networks in the present application has the characteristics of being able to centrally manage closed nodes of heterogeneous networks in a penetrating manner, decoupling logic and physics, and getting rid of physical location dependence and rigid configuration, thereby achieving the purpose of building a low-latency, highly reliable trading environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments of the present application. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0045] Figure 1 This is a flow chart of a method for unified management of heterogeneous networks provided by this application;

[0046] Figure 2 This is a schematic diagram of a unified management system for heterogeneous networks provided by this application. DETAILED DESCRIPTION

[0047] The following will be combined with the drawings in the embodiments of this specification to clearly and completely describe the technical solutions in the embodiments of this specification. Obviously, the embodiments described are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments in this specification, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of this invention.

[0048] It should be noted that the terms "including" and "having" and any variations thereof in the present invention are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes 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 are inherent to these processes or methods.

[0049] Various exemplary embodiments, features, and aspects of the present application will be described in detail below with reference to the accompanying drawings. The word "exemplary" is used herein to mean "serving as an example, embodiment, or illustration." Any embodiment described herein as "exemplary" is not necessarily to be construed as superior or preferred over other embodiments.

[0050] In addition, in order to better illustrate the present application, numerous specific details are provided in the specific embodiments below. Those skilled in the art should understand that the present application can also be implemented without certain specific details. In addition, in some examples, some general concepts are illustrated by "such as..." to facilitate understanding, but the general concepts should also include other devices or means familiar to those skilled in the art. In some examples, methods and means familiar to those skilled in the art are not described in detail in order to highlight the main purpose of the present application.

[0051] See also Figure 1 , a first aspect of the present application provides a unified management method for heterogeneous networks, comprising the following steps: S1: establishing a physical hardware network compatible with the heterogeneous network, the physical hardware network comprising a main line, a backup line, and a managed node connected to the main line or the backup line;

[0052] S2: Building a virtual control platform consisting of a controller and a logical resource pool, wherein the controller is used to dynamically schedule the logical resource pool;

[0053] S3: Perform upper-layer abstraction on the physical hardware network to generate a virtual logical network, and configure the virtual logical network to the logical resource pool;

[0054] S4: deploying an agent program in the hosting node, wherein the agent program is used to collect data of the corresponding hosting node and encapsulate it into standardized data according to a standardized protocol; and

[0055] S5: establishing a control channel and a data channel, wherein the controller issues tasks to the agent program via the control channel, and the agent program transmits the standardized data back to the controller via the data channel.

[0056] Establish a physical hardware network compatible with heterogeneous networks and support network equipment and protocols from different manufacturers. Network equipment includes routers, switches, firewalls, wireless network equipment, gateways, etc. Protocols include SNMP protocol, TLS protocol, etc., to build a unified centralized non-intrusive management system for brokerage firm's dedicated business nodes. In addition, a master-slave dual-line redundant design is adopted, such as BGP automatic switching, to avoid single point failures and ensure business continuity.

[0057] The upper layer of the physical hardware network is further abstracted into a virtual logical network to achieve logical and physical decoupling. The virtual logical network can be dynamically adjusted according to business needs without the need to reconstruct physical links, and get rid of physical location dependence and rigid configuration. In the specific implementation process, when a new brokerage node is added, it only needs to be included in the existing physical hardware network management without the need to reconstruct the physical link.

[0058] Build a virtual control platform to synchronously configure virtual logical networks to achieve centralized management and status monitoring across heterogeneous networks. During the specific implementation process, the virtual logical network mapping is synchronized to the virtual control platform, and the network topology is performed based on the virtual logical network.

[0059] Deploy an agent program to collect managed node data in real time, encapsulate it using a standardized protocol, and transmit it back. During the specific implementation process, a lightweight agent design can be used to make the agent program's CPU usage less than 5%, avoiding occupying the bandwidth of the business channel and ensuring the smooth operation of the core business.

[0060] A two-way communication mechanism is established between the control channel and the data channel. The control channel implements configuration policy delivery in seconds, while the data channel ensures the efficient transmission of encrypted business flows. This not only meets the low-latency requirements of quantitative trading, but also ensures data security through protocol-level encryption. During the specific implementation process, the Ansible network plug-in is used to establish communication with the hosting node through a compatible protocol (such as SSH, HTTPS, or TLS) and select the corresponding line as the control channel based on preset conditions and current network conditions. The policy entry delay is ≤200ms. Standardized data uses the Kafka streaming data return mechanism with a return throughput of ≥100,000 records / second. Hot and cold data are separated to ensure low-latency access.

[0061] In some optional implementation methods, step S3 further includes:

[0062] S31: Using network overlay technology to build a logical network layer covering the physical hardware network;

[0063] S32: Mapping the managed nodes one by one to logical resources and merging them into the logical resource pool; and

[0064] S33: Map the physical topology of the physical hardware network to the virtual logical network in the logical network layer, and synchronize the virtual logical network to the logical resource pool.

[0065] Furthermore, network encapsulation and tunneling protocol technologies are used to standardize the encapsulation of the original data packets from the managed nodes. This standardized data can be transparently transmitted across physical links. Standardized encapsulation bypasses the limitations of brokerage firms' proprietary protocols, enabling interoperability across heterogeneous networks. During the logical mapping process, each virtual logical network is assigned a unique identifier. Managed nodes are mapped to logical resources and integrated into a logical resource pool, which is then uniformly controlled by a controller. These logical resources include storage resources (such as vSAN) and computing resources (such as virtual machines or containers).

[0066] In some optional implementations, relay nodes are deployed at the access points of the primary and backup lines, and the standardized data is forwarded to the data channel via the relay nodes for transmission back to the controller. The relay nodes, on the one hand, serve as a transit hub for the physical hardware network, monitoring link status (such as latency and packet loss rate) in real time. When a primary line fails, such as when latency or packet loss exceeds a threshold, the relay nodes trigger the primary-backup line switching logic to ensure business continuity. On the other hand, the relay nodes receive data streams from the managed nodes and forward them to the virtual control platform via the optimal path.

[0067] In some optional implementation methods, the data channel further includes a line channel corresponding to a physical connection to the physical hardware network, and the allocation of traffic configuration resources for the line channel further includes the following steps:

[0068] S51: Deploy traffic controllers in the relay node and the hosting node to monitor local traffic status in real time;

[0069] S52: Allocate the line channel to the relay node and the hosting node preferentially according to the registration information of the relay node and the hosting node and the current network load;

[0070] S53: Counting the minimum value of data traffic of all relay nodes and the hosting node connected to the line channel within a recent preset period, adjusting the transmission priority of each relay node and the hosting node based on the local traffic status and service type of all relay nodes and the hosting node, allocating initial traffic configuration resources to the corresponding relay node or the hosting node, and sending the initial traffic configuration resources to the corresponding traffic controller;

[0071] S54: periodically collecting data traffic from all relay nodes and hosting nodes connected to the line channel according to the preset period, establishing a data traffic prediction model, and generating a traffic configuration resource allocation strategy in real time based on the prediction results; and

[0072] S55: Counting the sum of traffic configuration resources required by all relay nodes and hosting nodes according to the allocation strategy; when the sum exceeds the maximum resource capacity of the line channel, adaptively adjusting the resource capacity of the line channel according to the dynamic expansion strategy.

[0073] It can be understood that the local traffic status includes: data throughput, delay and packet loss rate, etc. The registration information of the relay node and the hosting node can include basic device information (such as device type, device ID, MAC address), network configuration information (such as link status, supported protocol types), resource information (number of CPU cores, memory capacity, local storage capacity), etc., and preferentially allocate relatively stable and idle line channels. The preset period can be one minute, one hour, half a day, one day, etc. The traffic configuration resources include bandwidth quota, computing resources and storage resources in the logical resource pool, etc.

[0074] Furthermore, the establishment of a data traffic prediction model and the generation of a real-time allocation strategy for traffic configuration resources based on the prediction results further include the following steps:

[0075] S541: Building a traffic configuration resource prediction model based on the traffic configuration resource data historically allocated to each relay node and / or the hosting node and the time series data of the real-time data traffic;

[0076] S542: Using a random time series model to capture the temporal autocorrelation of the relay node and / or the hosting node, and predicting future data traffic distribution; and

[0077] S543: Calculate traffic configuration resources that meet predetermined conditions for each relay node and / or hosting node according to the future data traffic distribution.

[0078] Using historical traffic allocation resource data to predict future traffic allocation resource requirements, and quantifying financial market activity using indicators such as transaction volume, turnover rate, and futures positions, deep learning is used to analyze the temporal autocorrelations of financial market activity to predict future data traffic distribution and implement optimal traffic allocation strategies. In specific implementations, the predefined conditions should be bandwidth redundancy ≥ 20% and a historical failure rate < 0.1%.

[0079] Furthermore, the adaptively adjusting the resource capacity of the line channel according to the dynamic expansion strategy further includes the following steps:

[0080] S551: Establish a Sigmoid function, use the peak delay of the line channel as input of the Sigmoid function, and convert the peak delay into a capacity expansion coefficient normalized to the (0, 1) interval;

[0081] S552: Mapping the capacity expansion coefficient to an increase or decrease ratio of the resource capacity of the line channel;

[0082] S553: ​​Dynamically adjust the allocation of the resource capacity according to the increase / decrease ratio, and when the real-time data traffic of the line channel exceeds the limit value, trigger the capacity expansion strategy and increase the traffic configuration resources of all the relay nodes and the hosting nodes in the line channel in order of priority; and

[0083] S554: When the real-time data traffic of the line channel recovers to below the limit value, the rollback expansion strategy is triggered to smoothly roll back the traffic configuration resources currently obtained by the relay node and the hosting node to the initial traffic configuration resources.

[0084] Peak latency is normalized and fed into a Sigmoid function to generate a capacity expansion coefficient. This coefficient correlates peak latency with traffic bottlenecks, accurately mapping capacity expansion needs. Priorities are determined based on local traffic conditions and service types, and resources are allocated accordingly, prioritizing hosting nodes with high-volume, high-value core services, such as those hosting financial market transactions, to maximize throughput. Furthermore, the smoothness of the Sigmoid function mitigates the impact of sudden resource increases and decreases on the virtual control platform, improving platform availability and stability. Because the Sigmoid function's output responds exponentially to changes in the input value, the capacity expansion ratio increases or decreases exponentially with even small changes in latency near zero. Therefore, capacity expansion strategies can be automatically initiated in the early stages of rapid data traffic growth, before congestion occurs on the line channel. This allows for rapid response to service demand and automatic increase of network resources, reducing the likelihood of network congestion and improving data transmission stability. Furthermore, when data traffic declines, network resources added by the previous capacity expansion strategy can be rolled back, smoothing the time it takes for multiple nodes to compete for line channel resources and maximizing line channel resource capacity utilization.

[0085] In some optional implementation methods, the standardized data is transmitted in the data channel in the form of a data packet, and the transmission of the standardized data further includes the following steps:

[0086] S71: Prioritize and classify the standardized data according to business type;

[0087] S72: Setting different DSCP fields corresponding to different categories of the standardized data; and

[0088] S73: Write the DSCP field into the header of the corresponding data packet.

[0089] The DSCP field can be located in the first 6 bits of the TOS field of the IPv4 / header or the Traffic Class field of the IPv6 header. Different fields can represent different service levels. In the specific implementation process, four service levels can be established, with priority from low to high:

[0090] 000001: file transfer;

[0091] 000010: Customized risk control data;

[0092] 000011: core monitoring data;

[0093] 000100: Operation and maintenance control signal.

[0094] According to the four service levels mentioned above, the controller assigns different processing priorities based on DSCP classification, implementing different forwarding behaviors for data of different levels according to preset policies. Furthermore, corresponding service quality requirements can be set for data packets of different priorities, such as latency requirements and packet loss priority selection flags. Taking latency priority as an example, the controller can simulate the lower limit of bandwidth required for service provision under the constraints of given latency requirements and packet loss rate upper limit, thereby providing an effective parameter reference for traffic resource allocation during actual transmission. This not only ensures better service support for core services, but also avoids unnecessary BAC active packet loss for edge services.

[0095] In some optional implementation methods, the agent program collecting data of the corresponding hosting node further includes the following steps:

[0096] S41: Divide the data of the hosting node into three data types: real-time data, continuous data, and offline data;

[0097] S42: The agent program actively collects data from the hosting node and encapsulates the data in a standardized protocol; and

[0098] S43: After receiving the standardized data transmitted back from the data channel, the controller pushes the standardized data to a designated storage server in the logical resource pool according to the data type.

[0099] Data from managed nodes is divided into three categories: real-time, continuous, and offline. Different collection strategies can be adapted as needed to push collected data by type to designated storage servers. Real-time data, which may include transaction status and instantaneous CPU / memory metrics, is prioritized via control channels. Continuous data, which may include application log streams, is transmitted in batches via data channels with high throughput for easy retrieval and analysis. Offline data, which may include historical transaction records, is pushed offline via asynchronous transmission channels. Pushing collected data by type to designated storage servers eliminates manual pull requests, eliminates the need for widespread user authorization, and mitigates security risks caused by generalized permissions.

[0100] In some optional implementation methods, the controller is divided into a master controller and a slave controller, there is only one master controller, and the slave controllers can switch roles based on instructions. The controller used to receive the returned standardized data is the slave controller.

[0101] There is only one master controller, which ensures the uniqueness of the client command queue and the sequential execution of commands. The slave controllers monitor messages and cache standardized data collected and packaged by the proxy. If the master controller fails, the first-priority slave controller automatically assumes the master role, achieving automated master-slave switchover. Furthermore, when a client issues a role reversal command, the original master controller automatically switches to a slave controller, avoiding role conflicts and switching the command target to the master controller.

[0102] The second aspect of the present application provides a unified management system for heterogeneous networks. Figure 2 , used to execute the heterogeneous network unified management method according to any of the above items. Based on the above heterogeneous network unified management method, the heterogeneous network unified management system in this application has the characteristics of being able to centrally manage the closed nodes of heterogeneous networks in a penetrating manner, decoupling logic and physics to get rid of physical location dependence and rigid configuration, and build a low-latency, highly reliable trading environment.

[0103] Throughout this specification, references to terms such as "some embodiments," "for example," or "example" indicate that a specific feature or characteristic described in conjunction with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of these terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0104] Although the present embodiment has been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and variations may be made without departing from the principles and spirit of the present embodiment, the scope of which is defined by the claims and their equivalents.

Claims

1. A method for unified management of heterogeneous networks, characterized in that: The following steps are involved: S1: Establishing a physical hardware network compatible with the heterogeneous network, wherein the physical hardware network includes a main line, a backup line, and a managed node connected to the main line or the backup line; S2: Building a virtual control platform consisting of a controller and a logical resource pool, wherein the controller is used to dynamically schedule the logical resource pool; S3: Perform upper-layer abstraction on the physical hardware network to generate a virtual logical network, and configure the virtual logical network to the logical resource pool; S4: deploying an agent program in the hosting node, wherein the agent program is used to collect data of the corresponding hosting node and encapsulate it into standardized data according to a standardized protocol; as well as S5: establishing a control channel and a data channel, wherein the controller issues tasks to the agent program via the control channel, and the agent program transmits the standardized data back to the controller via the data channel.

2. The method for unified management of heterogeneous networks according to claim 1, characterized in that: The step S3 further comprises: S31: Using network overlay technology to build a logical network layer covering the physical hardware network; S32: Mapping the managed nodes one by one to logical resources and merging them into the logical resource pool; and S33: Map the physical topology of the physical hardware network to the virtual logical network in the logical network layer, and synchronize the virtual logical network to the logical resource pool.

3. The method for unified management of heterogeneous networks according to claim 2, characterized in that: Relay nodes are also deployed at the access points of the main line and the backup line, and the standardized data is forwarded to the data channel via the relay nodes to be transmitted back to the controller.

4. The method for unified management of heterogeneous networks according to claim 3, characterized in that: The data channel also includes a line channel corresponding to a physical connection to the physical hardware network, and the allocation of traffic configuration resources of the line channel further includes the following steps: S51: Deploy traffic controllers in the relay node and the hosting node to monitor local traffic status in real time; S52: Allocate the line channel to the relay node and the hosting node preferentially according to the registration information of the relay node and the hosting node and the current network load; S53: Counting the minimum value of data traffic of all relay nodes and the hosting node connected to the line channel within a recent preset period, adjusting the transmission priority of each relay node and the hosting node based on the local traffic status and service type of all relay nodes and the hosting node, allocating initial traffic configuration resources to the corresponding relay node or the hosting node, and sending the initial traffic configuration resources to the corresponding traffic controller; S54: periodically collecting data traffic from all relay nodes and hosting nodes connected to the line channel according to the preset period, establishing a data traffic prediction model, and generating a traffic configuration resource allocation strategy in real time based on the prediction results; and S55: Counting the sum of traffic configuration resources required by all relay nodes and hosting nodes according to the allocation strategy; when the sum exceeds the maximum resource capacity of the line channel, adaptively adjusting the resource capacity of the line channel according to the dynamic expansion strategy.

5. The method for unified management of heterogeneous networks according to claim 4, characterized in that: The method of establishing a data traffic prediction model and generating a real-time traffic configuration resource allocation strategy based on the prediction results further includes the following steps: S541: Building a traffic configuration resource prediction model based on the traffic configuration resource data historically allocated to each relay node and / or the hosting node and the time series data of the real-time data traffic; S542: Using a random time series model to capture the temporal autocorrelation of the relay node and / or the hosting node, and predicting future data traffic distribution; and S543: Calculate traffic configuration resources that meet predetermined conditions for each relay node and / or hosting node according to the future data traffic distribution.

6. The method for unified management of heterogeneous networks according to claim 4, characterized in that: Adaptively adjusting the resource capacity of the line channel according to the dynamic capacity expansion strategy further includes the following steps: S551: Establish a Sigmoid function, use the peak delay of the line channel as input of the Sigmoid function, and convert the peak delay into a capacity expansion coefficient normalized to the (0, 1) interval; S552: Mapping the capacity expansion coefficient to an increase or decrease ratio of the resource capacity of the line channel; S553: ​​Dynamically adjust the allocation of the resource capacity according to the increase / decrease ratio, and when the real-time data traffic of the line channel exceeds the limit value, trigger the capacity expansion strategy and increase the traffic configuration resources of all the relay nodes and the hosting nodes in the line channel in order of priority; and S554: When the real-time data traffic of the line channel recovers to below the limit value, the rollback expansion strategy is triggered to smoothly roll back the traffic configuration resources currently obtained by the relay node and the hosting node to the initial traffic configuration resources.

7. The method for unified management of heterogeneous networks according to claim 1, characterized in that: The standardized data is transmitted in the data channel in the form of a data packet, and the transmission of the standardized data further comprises the following steps: S71: Prioritize and classify the standardized data according to business type; S72: Setting different DSCP fields corresponding to different categories of the standardized data; and S73: Write the DSCP field into the header of the corresponding data packet.

8. The method for unified management of heterogeneous networks according to claim 1, characterized in that: The agent program collecting the data of the corresponding hosting node also includes the following steps: S41: Divide the data of the hosting node into three data types: real-time data, continuous data, and offline data; S42: The agent program actively collects data from the hosting node and encapsulates the data in a standardized protocol; and S43: After receiving the standardized data transmitted back from the data channel, the controller pushes the standardized data to a designated storage server in the logical resource pool according to the data type.

9. The method for unified management of heterogeneous networks according to claim 1, wherein: The controller is divided into a master controller and a slave controller. There is only one master controller. The slave controllers can switch roles with each other according to instructions. The controller used to receive the returned standardized data is the slave controller.

10. A unified management system for heterogeneous networks, characterized in that: Used to execute the heterogeneous network unified management method according to any one of claims 1-9.

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