Flat cloud architecture unified integration management method, device and equipment

Abstract

The present invention relates to the technical field of cloud data fusion management, and discloses a unified fusion management method, device and equipment of a flat cloud architecture. The method comprises: deploying a unified fusion management software system on a cloud virtual server; constructing an IP transmission network, connecting monitoring units that meet standard interface specifications, and obtaining verification results; according to the verification results, converting data into a data format consistent with the standard interface specifications; creating a dedicated protocol parsing module to connect various types of intelligent devices to the unified fusion management software system, and obtaining device communication data sets; performing flat unified fusion management on various types of intelligent devices and device communication data sets, and generating intelligent fusion management decision information. The present invention constructs a flat, cloud-based unified fusion management architecture to achieve centralized management of distributed monitoring units, data standardization of heterogeneous devices, efficient access of intelligent devices, and intelligent decision support based on big data.

Description

Technical Field

[0001] The present invention relates to the field of cloud data fusion management technology, and in particular to a method, device and equipment for unified fusion management of a flat cloud architecture. Background Art

[0002] With the rapid development of information technology and the continuous expansion of network coverage, the telecommunications industry is facing the challenges of widely distributed computer rooms, complex business requirements, and increasing equipment maintenance and monitoring requirements. The traditional multi-vendor, multi-platform management model has low timeliness and security issues. Since it is difficult to achieve unified management of various monitoring equipment built by different manufacturers at different times, the system standardization is low and the availability is insufficient.

[0003] In addition, existing environmental monitoring systems generally have problems such as difficulty in device access, inconsistent data formats, and complex protocol parsing, making it difficult to achieve centralized management of new and old equipment and effective use of data. At the same time, with the widespread application of smart devices, how to effectively access and manage various smart devices, optimize their communication protocols, and achieve efficient data collection and analysis has also become an urgent problem to be solved. Summary of the invention

[0004] The present invention provides a method, device and equipment for unified fusion management of a flat cloud architecture. The present invention constructs a flat, cloud-based unified fusion management architecture to achieve centralized management of distributed monitoring units, data standardization of heterogeneous devices, efficient access of intelligent devices and intelligent decision support based on big data.

[0005] In a first aspect, the present invention provides a unified integrated management method for a flat cloud architecture, the unified integrated management method for a flat cloud architecture comprising:

[0006] Deploy a unified converged management software system on cloud virtual servers;

[0007] Construct an IP-based transmission network that supports multi-level device interconnection and connects distributed monitoring units with the unified fusion management software system;

[0008] Based on the IP transmission network, a monitoring unit that complies with the standard interface specification is connected to the unified fusion management software system, and the function and communication reliability of the monitoring unit that complies with the standard interface specification are verified to obtain a verification result;

[0009] According to the verification result, the data of the online monitoring unit that does not conform to the standard interface specification is converted into a data format consistent with the standard interface specification, and the converted data is connected to the unified fusion management software system;

[0010] The monitoring unit is connected to the unified fusion management software system to create a dedicated protocol parsing module to connect various intelligent devices to the unified fusion management software system, and the communication protocols of the various intelligent devices are optimized to obtain device communication data sets;

[0011] On the unified fusion management software system, the various types of intelligent devices and the device communication data sets are managed in a flat unified fusion manner to generate intelligent fusion management decision information.

[0012] In a second aspect, the present invention provides a unified fusion management device for a flat cloud architecture, the unified fusion management device for a flat cloud architecture comprising:

[0013] A deployment module is used to deploy a unified converged management software system on a cloud virtual server;

[0014] A construction module for constructing an IP-based transmission network supporting multi-level device interconnection, connecting distributed monitoring units with the unified fusion management software system;

[0015] A verification module, used to connect the monitoring unit that complies with the standard interface specification to the unified fusion management software system based on the IP transmission network, and verify the function and communication reliability of the monitoring unit that complies with the standard interface specification to obtain a verification result;

[0016] A conversion module, used to convert the data of the online monitoring unit that does not conform to the standard interface specification into a data format consistent with the standard interface specification according to the verification result, and connect the converted data to the unified fusion management software system;

[0017] An acquisition module is used to create a dedicated protocol parsing module when the monitoring unit is connected to the unified fusion management software system to connect various intelligent devices to the unified fusion management software system, optimize the communication protocols of the various intelligent devices, and obtain device communication data sets;

[0018] The generation module is used to perform flat unified fusion management on the various types of intelligent devices and the device communication data sets on the unified fusion management software system, and generate intelligent fusion management decision information.

[0019] The third aspect of the present invention provides a computer device, comprising: a memory and at least one processor, wherein the memory stores instructions; the at least one processor calls the instructions in the memory so that the computer device executes the above-mentioned flat cloud architecture unified integration management method.

[0020] A fourth aspect of the present invention provides a computer-readable storage medium, in which instructions are stored. When the computer-readable storage medium is run on a computer, the computer executes the above-mentioned flat cloud architecture unified integration management method.

[0021] In the technical solution provided by the present invention, unified management of heterogeneous devices is achieved: by building an IP transmission network that supports multi-level device interconnection, the distributed monitoring unit is connected to the unified fusion management software system, which solves the problem that different manufacturers and different types of devices are difficult to manage in a unified manner. By converting the data of the online monitoring unit that does not meet the standard interface specification into a standard format, seamless access of new and old devices is achieved, greatly improving the compatibility and scalability of the system. A dedicated protocol parsing module is created to achieve efficient access and communication protocol optimization of various types of intelligent devices, and improve the efficiency and accuracy of data collection. By flattening and unifying the management of device communication data sets, intelligent analysis and decision support based on big data are achieved, and the predictive maintenance capability of the system is improved. The cloud deployment and multi-level network architecture are adopted to enhance the reliability and security of the system and reduce the risk of single point failure. Through a unified management platform and an intelligent fault warning and processing mechanism, the labor cost of equipment maintenance and management is greatly reduced. Through data standardization and fusion analysis, the utilization rate of data is improved, providing strong support for business decision-making and network optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0023] Figure 1 A schematic diagram of the steps of a unified integrated management method for a flat cloud architecture according to an embodiment of the present invention;

[0024] Figure 2 It is a structural diagram of a unified fusion management device for a flat cloud architecture in an embodiment of the present invention. DETAILED DESCRIPTION

[0025] Embodiments of the present invention provide a method, apparatus and device for unified converged management of a flat cloud architecture. The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including" or "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0026] For ease of understanding, the specific process of the embodiment of the present invention is described below. Figure 1 , an embodiment of the unified integration management method of the flat cloud architecture in the embodiment of the present invention includes:

[0027] Step S1: deploying a unified converged management software system on a cloud virtual server;

[0028] It is understandable that the execution subject of the present invention may be a flat cloud architecture unified fusion management device, or a terminal or a server, which is not specifically limited here. The embodiment of the present invention is described by taking a server as the execution subject as an example.

[0029] Specifically, the framework structure of the unified fusion management software system is designed based on the MVC architecture (i.e., model-view-controller), the core modules and data flows of the system are determined, and a complete software system architecture diagram is obtained. According to the architecture diagram, the target operating system is installed on the cloud virtual server, and the operating system includes operating systems such as Linux and Windows Server used in common cloud computing environments, so as to provide a basic operating environment for the management software system. A database system such as MySQL, PostgreSQL or other databases suitable for distributed management is installed in the basic operating environment to build a stable and scalable data storage environment. On this data storage environment, the unified fusion management application code is written based on the database structure. This part of the code is written according to the designed business logic, device management requirements and interface specifications, and covers functional modules such as data storage, device access, and communication protocol parsing, and generates the corresponding application source code. The application source code is compiled and linked to obtain an executable unified fusion management application. The compiled executable application is deployed on the cloud virtual server to build the initial management software system. The initial management software system is split to disperse the pressure of data storage and improve the access speed; the data cache is configured to reduce frequent access to the database and improve the response speed of the overall system; the message subscription mechanism is set to realize asynchronous communication and data update within the system; the load balancing parameters are adjusted to ensure that the system can effectively allocate resources when multiple users access it, so as to obtain better system scalability and stability. Through optimization measures, the optimized management software system is obtained. In the optimized management software system, the Nginx server is configured to handle the reverse proxy and load balancing functions of front-end requests. At the same time, the log analysis module is configured to collect and analyze key logs during the operation of the system; the heartbeat detection function is set to monitor the health status of system components in real time; capacity assessment and flow control are performed to ensure the scalability of the system and its adaptability to burst traffic. Based on the priorities of different services and devices, service classification parameters are set to ensure priority response and resource allocation of important services. Through the above configuration and optimization, a complete and functionally optimized unified integrated management software system is obtained.

[0030] Step S2: construct an IP transmission network that supports multi-level device interconnection and connects distributed monitoring units with a unified fusion management software system;

[0031] Specifically, the IP RAN network architecture is designed according to the network topology. A reasonable network layer division scheme is obtained by analyzing the distribution and communication requirements of the equipment. Based on the network layer division scheme, the TCP / IP protocol parameters of the IPRAN equipment are configured, including the allocation of IP addresses, subnet division, selection of routing protocols, etc., to form the access layer network configuration. The access layer is the first connection point between the equipment and the network, ensuring that all monitoring units can access the network through the access layer without obstacles. The access layer network configuration is verified and tested. By testing the connection status data of the access layer network, it is ensured that the equipment can correctly connect to the network and communicate. According to the network connection status data obtained by the test, the 10G circuit parameters of the first device and the second device are configured to ensure that the network can meet the high-speed data transmission requirements between the convergence layer devices, and the convergence layer network configuration is obtained. Based on the convergence layer network configuration, the routing table and forwarding rules of the third device and the fourth device are set. By setting the routing table, the network data can be forwarded according to the optimal path, thereby improving the efficiency of network communication. The setting of the forwarding rules ensures the correct transmission and distribution of network data between different devices, and the first core layer network configuration is obtained. According to the first core layer network configuration, the 100G circuit parameters and QoS policies of the fifth and sixth devices are adjusted. The adjustment of the 100G circuit parameters ensures the transmission bandwidth of the core layer when facing a large amount of data, and the configuration of the QoS policy ensures the priority of different types of data during the data transmission process, thereby improving the transmission efficiency and data transmission quality of the entire network, and obtaining the second core layer network configuration. According to the second core layer network configuration, the BGP protocol parameters and VPN tunnel configuration of the EPC CE core network device are set to obtain the core network access configuration. The BGP protocol is used to achieve efficient routing between different networks to ensure that devices across networks can be seamlessly interconnected. The VPN tunnel configuration provides a secure communication channel between the distributed monitoring units and the unified converged management software system to ensure the confidentiality and integrity of the data. The core network access configuration is tested end-to-end to verify whether the connection of each part of the network is smooth and the configuration is correct, and the network path and bandwidth allocation are adjusted according to the test results. In this way, network resources can be reasonably utilized and the path can be dynamically optimized according to the load conditions. An IP-based transmission network that supports multi-level device interconnection is formed, and the distributed monitoring units are successfully connected to the unified converged management software system.

[0032] Step S3: Based on the IP transmission network, the monitoring unit that complies with the standard interface specification is connected to the unified fusion management software system, and the function and communication reliability of the monitoring unit that complies with the standard interface specification are verified to obtain the verification result;

[0033] Specifically, a monitoring unit access test plan is formulated based on the IP transmission network and the preset interface protocol specifications. The plan should include all relevant test steps and verification methods, and form a list of test items. Based on the list of test items, the data acquisition function of the monitoring unit is tested, focusing on whether it can collect and transmit monitoring data as required, and the test results are summarized as data acquisition performance indicators, which are used to evaluate the data acquisition capability and efficiency of the monitoring unit. The four core functions of the monitoring unit, namely, remote signaling, remote control, telemetry and remote adjustment, are verified one by one. Through detailed testing of each function, the verification results of the remote signaling, remote control, telemetry and remote adjustment functions are obtained respectively. These results help to evaluate the basic operation capabilities of the monitoring unit. At the same time, the communication stability between the monitoring unit and the unified fusion management software system is monitored and tested for a long time, focusing on evaluating its communication reliability under different loads and network conditions, and obtaining reliable communication stability data. Based on the communication reliability data, different network abnormalities are simulated, such as network delay, packet loss or connection interruption, and the data retransmission function of the monitoring unit under these abnormal conditions is tested. By comparing the data transmitted normally and the data after retransmission, it is determined whether the data integrity is affected, and the results of this test are summarized as the data integrity test results. In order to ensure the stability of the monitoring unit after the device is restarted, its automatic recovery capability is tested, especially whether it can quickly restore the connection with the system and continue to perform the predetermined functions after restart. By evaluating the performance after restart, the automatic recovery capability evaluation data is obtained. When all the test and verification steps are completed, a comprehensive monitoring unit function and communication reliability comprehensive evaluation report is generated based on the data acquisition performance indicators, four remote function verification results, communication reliability data, data integrity test results and automatic recovery capability evaluation data. This report includes the performance evaluation of each functional module and analyzes the overall compatibility and communication stability of the monitoring unit with the unified integrated management system. Based on the comprehensive evaluation report, the access configuration and related parameters of the monitoring unit are optimized to ensure that it can maximize its performance under the premise of meeting the standard interface specifications. After adjustment and optimization, the corresponding verification results of the monitoring unit that meets the standard interface specifications are obtained.

[0034] Step S4: based on the verification result, convert the data of the online monitoring unit that does not conform to the standard interface specification into a data format consistent with the standard interface specification, and connect the converted data to the unified fusion management software system;

[0035] Specifically, according to the verification results, the existing monitoring units are analyzed, the monitoring units on the network that do not meet the standard interface specifications are identified, and a list of non-standard monitoring units is obtained. The protocol characteristics of each type of non-standard monitoring unit are analyzed, including parsing its communication protocol, data format and transmission mechanism to generate a protocol characteristic data set. Based on the protocol characteristic data set, a protocol conversion algorithm is designed. The core goal of the algorithm is to convert the data format of the non-standard monitoring unit into a data format that meets the standard interface specification. Through this step, a protocol conversion module is generated. In order to ensure the accuracy of the function of the module and the conversion result, a functional test is performed on it. During the test, the correctness of the conversion is verified by inputting non-standard data and observing whether its conversion result meets the standard, and the conversion function verification result is obtained. According to the conversion function verification result, the protocol conversion module is optimized and adjusted as necessary. The optimization involves improving the conversion efficiency, ensuring the real-time and accuracy of the data, etc., to form an optimized protocol conversion module. Using the optimized module, the data of all non-standard monitoring units are converted in real time so that their output data meets the standard interface specification and forms a standardized data stream. Perform data integrity checks on standardized data streams to ensure that data is not lost, damaged or tampered with during the conversion process, and generate data integrity check reports to ensure that data remains consistent before and after the conversion. Based on the check report, connect the converted data to the unified fusion management software system to confirm that it can interact with the system seamlessly, and generate access confirmation information for non-standard monitoring units.

[0036] Step S5: Connect the monitoring unit to the unified fusion management software system to create a dedicated protocol parsing module to connect various intelligent devices to the unified fusion management software system, optimize the communication protocols of various intelligent devices, and obtain device communication data sets;

[0037] Specifically, the monitoring units connected to the unified converged management software system are identified by type, and a list of intelligent device types is obtained. Through the identification process, the types and characteristics of various intelligent devices connected to the system are clarified. According to the list of intelligent device types, the communication protocol of each type of intelligent device is analyzed, the protocol characteristics of each type of device are identified, and protocol characteristic data is generated to describe the communication mode, data format and possible protocol differences of different devices. Based on the protocol characteristic data, a dedicated protocol parsing algorithm for different types of intelligent devices is designed to construct an initial protocol parsing module. The design purpose of this module is to ensure that the system can correctly parse and process data communications of various types of devices. In order to verify the effectiveness of the module, a functional test is performed on it. During the test, the accuracy and consistency of the parsing are verified by receiving and parsing the communication data from the device, and the parsing function test results are obtained. According to the test results, if the initial protocol parsing module is found to have parsing errors or efficiency problems, it is optimized and adjusted. The optimization involves the improvement of the algorithm, the improvement of the parsing speed or the enhancement of the compatibility, and finally forms an optimized dedicated protocol parsing module. This module can parse the communication data of various types of intelligent devices more efficiently and accurately, and convert the parsed data into standardized device data. Data flow analysis is performed on the standardized device data to identify inefficient communication protocols. By monitoring and analyzing the data flow during the communication process, inefficient protocols or communication bottlenecks in the communication process are identified. The identified inefficient protocols are included in the protocol optimization target list. Based on the protocol optimization target list, the identified inefficient communication protocols are optimized and designed, and their communication mechanisms, data transmission modes or protocol layers are adjusted to ensure more efficient and smooth data transmission. The optimized protocol effectively improves the communication efficiency between devices and systems, and ultimately generates a new device communication data set.

[0038] Step S6: On the unified fusion management software system, various intelligent devices and device communication data sets are managed in a flat unified fusion manner to generate intelligent fusion management decision information.

[0039] Specifically, standardize the data and communication data sets of various intelligent devices, convert the heterogeneous data of different devices into a unified format, ensure that all data conform to the same standard, and obtain a standardized data model. Build a unified device model and data model based on the standardized data model, and map the characteristics, parameters and communication data of different devices to the same structural framework to obtain a fused data structure. Perform real-time analysis on the data in the fused data structure, focusing on the operating status of various intelligent devices. By analyzing the device sensor data, operation logs and other information, evaluate the operating status of the device in real time, identify potential performance problems or hidden faults, and generate the device operating status evaluation results. Based on the evaluation results, establish a fault warning model, including common fault modes, prediction of abnormal device behavior, and generate a fault warning rule set. The rule set defines when to trigger the warning and how to process the warning information according to different fault categories. Through the fault warning rule set, the operating data of the device is monitored in real time, any abnormal behavior that meets the warning conditions is automatically captured, and the corresponding alarm information is generated. In order to ensure the efficiency and accuracy of alarm processing, the alarm information is intelligently classified and processed. According to the severity of different alarms, equipment types and their potential impacts, a hierarchical alarm processing plan is formed to provide appropriate processing procedures and response measures for alarms of different levels, so that the system can respond to equipment abnormalities quickly and orderly. According to the hierarchical alarm processing plan, a visual management interface is developed. Through the multi-dimensional data display module, users can filter and analyze equipment data from different angles, including real-time equipment status, historical data trends, alarm distribution and other information. In order to enhance the system's intelligent decision-making ability, expert maintenance experience is integrated, expert knowledge is combined with equipment data, and ultimately intelligent fusion management decision information is generated.

[0040] In the embodiment of the present invention, unified management of heterogeneous devices is achieved: by building an IP transmission network that supports multi-level device interconnection, the distributed monitoring units are connected to the unified fusion management software system, solving the problem that different manufacturers and different types of devices are difficult to manage in a unified manner. By converting the data of the online monitoring units that do not meet the standard interface specifications into a standard format, seamless access of new and old devices is achieved, greatly improving the compatibility and scalability of the system. A dedicated protocol parsing module is created to achieve efficient access and communication protocol optimization of various types of intelligent devices, and improve the efficiency and accuracy of data collection. By flattening and fusion management of device communication data sets, intelligent analysis and decision support based on big data are achieved, and the predictive maintenance capability of the system is improved. The cloud deployment and multi-level network architecture are adopted to enhance the reliability and security of the system and reduce the risk of single point failure. Through a unified management platform and an intelligent fault warning and processing mechanism, the labor cost of equipment maintenance and management is greatly reduced. Through data standardization and fusion analysis, the utilization rate of data is improved, providing strong support for business decision-making and network optimization.

[0041] In a specific embodiment, the process of executing step S1 may specifically include the following steps:

[0042] Design the framework structure of the unified fusion management software system based on the MVC architecture, obtain the software system architecture diagram, and install the target operating system on the cloud virtual server according to the software system architecture diagram to obtain the basic operating environment;

[0043] Install the database system in the basic operating environment to obtain the data storage environment, and write the unified fusion management application code based on the data storage environment to obtain the application source code;

[0044] Compile and link the application source code to obtain an executable unified fusion management application, and deploy the executable unified fusion management application to the cloud virtual server to obtain an initial management software system;

[0045] Perform database splitting, data cache configuration, message subscription settings and load balancing adjustments on the initial management software system to obtain an optimized management software system;

[0046] Configure the Nginx server in the optimized management software system, and set log analysis, heartbeat detection, capacity assessment, traffic control and service classification parameters to obtain a unified integrated management software system.

[0047] Specifically, the framework structure of the unified fusion management software system is designed based on the MVC architecture to ensure that business logic, user interface and data management can be fully separated in the system design. The design of the MVC architecture contributes to the modularity, maintainability and scalability of the system, and can effectively simplify the development process of complex systems. In the early stage of system design, a software system architecture diagram is constructed. In this architecture diagram, the model layer is responsible for data management and business logic, the view layer is responsible for presenting the user interface, and the controller is responsible for processing requests from users and forwarding them to the model or view for processing. In this way, the system can ensure that different layers are independent of each other and reduce coupling. According to the software system architecture diagram, the target operating system is installed on the cloud virtual server. The choice of operating system depends on project requirements and considerations of performance and compatibility. Through the installation of the operating system, a basic operating environment is constructed. The database system is installed in the basic operating environment. The database stores and manages all device communication data and system configuration information. Choose a relational database management system (RDBMS) such as MySQL or PostgreSQL, or a NoSQL database such as MongoDB. The specific choice depends on the system's requirements for data structure. The choice of database determines the system's data storage method and also affects the efficiency of data reading, querying and processing. Write unified converged management application code based on database structure and system requirements, including modules such as device management, communication protocol processing, data collection and analysis, and alarm system. During the development process, it is necessary to ensure that the application can interact with the database efficiently and handle concurrent requests, ensure its scalability in a large-scale distributed environment, and generate complete application source code. Compile and link the application source code. Convert high-level source code into binary files that can be directly executed by the machine. The compiler processes the source code in segments and generates efficient executable files through a series of optimization strategies. The linker integrates different modules and libraries in the code to form a complete executable unified converged management application. Deploy the executable application to the cloud virtual server to obtain the initial management software system. Optimize the initial management software system, including database splitting, data cache configuration, message subscription settings, and load balancing adjustment. Database splitting refers to splitting the database horizontally or vertically according to the frequency of data use or functional modules to improve the efficiency of database query and write. Horizontal splitting reduces the load on a single database by distributing data to multiple database instances, while vertical splitting stores different types of data in different databases to reduce the overhead of complex queries. Perform data cache configuration. In a high-concurrency environment, frequent access to the database will lead to performance bottlenecks. Use cache systems such as Redis or Memcached to temporarily store high-frequency data in memory, reduce direct access to the database, and improve the system's response speed. Message subscription settings are used to achieve asynchronous communication and data synchronization between different modules within the system.For example, use message queues (such as RabbitMQ or Kafka) to process real-time data streams in the system to ensure efficient message delivery between different subsystems. Load balancing adjustment is to reasonably distribute requests between multiple servers to avoid system crashes caused by overload of a server. Through load balancing algorithms (such as polling or minimum number of connections), dynamically adjust resource allocation to ensure efficient and stable operation of the system. In the optimized management software system, configure Nginx server as a reverse proxy server to improve the processing capacity of Web services. Nginx can handle static resource requests and distribute front-end requests through load balancing to ensure system stability and efficient response. Configure log analysis, heartbeat detection, capacity assessment, flow control and service classification parameters. The log analysis module collects and analyzes various logs generated during system operation to help discover potential problems; heartbeat detection regularly checks the health status of each module of the system to ensure the normal operation of each part of the system; capacity assessment is used to predict future resource requirements to prevent system resource exhaustion; flow control is used to prevent the system from being overwhelmed by sudden high concurrent requests, and the number of requests per second is limited through the current limiting mechanism. Service classification parameters are used to distinguish services of different priorities, ensuring that high-priority tasks are processed first.

[0048] In a specific embodiment, the process of executing step S2 may specifically include the following steps:

[0049] Design IP RAN network architecture according to network topology, obtain network layer division scheme, and configure TCP / IP protocol parameters of IPRAN equipment based on network layer division scheme to obtain access layer network configuration;

[0050] Performing a verification test on the access layer network configuration to obtain access layer network connection status data, and configuring 10G circuit parameters of the first device and the second device according to the access layer network connection status data to obtain the aggregation layer network configuration;

[0051] Based on the aggregation layer network configuration, set the routing table and forwarding rules of the third device and the fourth device to obtain the first core layer network configuration;

[0052] According to the first core layer network configuration, adjust the 100G circuit parameters and QoS policies of the fifth device and the sixth device to obtain the second core layer network configuration;

[0053] Based on the second core layer network configuration, set the BGP protocol parameters and VPN tunnel configuration of the EPC CE core network equipment to obtain the core network access configuration;

[0054] Conduct end-to-end communication testing on the core network access configuration, adjust the network path and bandwidth allocation, obtain an IP-based transmission network that supports multi-level device interconnection, and connect distributed monitoring units with a unified converged management software system.

[0055] Specifically, the IP RAN network architecture is designed according to the network topology. The IP RAN (IP-based wireless access network) architecture includes the access layer, the convergence layer, and the core layer, each of which bears different network traffic and device interconnection requirements. The core of the network layer division scheme is to ensure that the devices at each layer can be reasonably distributed according to their communication needs and performance requirements. Through division, the network can maintain efficient communication flow, reduce latency, and maximize the use of bandwidth resources. When designing the hierarchical structure, the access layer is the bottom layer, which connects various distributed monitoring units to the system, while the core layer is responsible for data aggregation and further processing. Based on the network layer division scheme, the TCP / IP protocol parameters of the IP RAN device are configured. Allocate an IP address to each access layer device, configure the subnet mask, routing information, and ensure that the devices can be interconnected through the TCP / IP protocol. Use the CIDR (Classless Inter-Domain Routing) allocation method to reduce the waste of IP addresses and ensure the scalability of the network. After setting, the access layer network configuration is obtained, which is responsible for ensuring that all monitoring units can enter the network through standardized communication protocols and start transmitting data. Verify the access layer network configuration. By sending test data packets, the connection status of each access device and the response speed of the network are detected, and the access layer network connection status data is obtained. Through network monitoring tools such as ping, traceroute and other commands, key indicators such as communication delay and packet loss rate of the access layer are evaluated. If any problems are found, the parameters are adjusted and retested to ensure that the access layer network is stable and efficient. Based on the test results, the 10G circuit parameters of the first device and the second device are configured to meet the transmission requirements of the aggregation layer, and the aggregation layer network configuration is obtained. The aggregation layer gathers data from the access layer and transmits it to the core layer, so it has high requirements for bandwidth and data transmission efficiency. By adjusting the 10G circuit parameters, it is ensured that the aggregation layer has sufficient transmission capacity. Based on the aggregation layer network configuration, the routing table and forwarding rules of the third device and the fourth device are set to complete the preliminary configuration of the core layer, and the first core layer network configuration is obtained. The routing table setting ensures that data can be transmitted between different network devices according to the optimal path, and the forwarding rule definition ensures that different types of data (such as video streams, control signals) can be reasonably distributed according to their priorities. According to the first core layer network configuration, the 100G circuit parameters and QoS policies of the fifth and sixth devices are adjusted to obtain the second core layer network configuration. The adjustment of 100G circuit parameters focuses on providing greater bandwidth to meet the needs of large data volume transmission in the core layer, while the configuration of QoS policies ensures that key business data can be transmitted preferentially under high concurrent traffic. QoS ensures the quality of service by defining the priorities of different traffic. For example, real-time monitoring video streams are set to high priority, while data recording services are set to lower priority to ensure that important services can remain smooth during congestion.Based on the second core layer network configuration, the BGP (Border Gateway Protocol) parameters and VPN (Virtual Private Network) tunnel configuration of the EPC (Evolved Packet Core) and CE (Customer Edge) core network devices are configured. The BGP protocol is used in the core network to control the routing path selection between different autonomous systems to ensure that network data can reach the target smoothly across different network domains. The VPN tunnel configuration provides encryption and security protection for the data transmission of the monitoring unit. Through the VPN tunnel, the communication between the distributed monitoring unit and the unified converged management software system is protected to ensure that the data is not intercepted or tampered with. After the configuration is completed, the core network access configuration is obtained. The core network access configuration is tested end-to-end to verify whether the full path communication from the access layer to the core network is unobstructed. If a path bottleneck or unreasonable bandwidth allocation is found during the test, the network path is replanned and the bandwidth is allocated reasonably to ensure that the system can handle high-concurrency data requests and obtain an IP-based transmission network that supports multi-level device interconnection. In this process, the optimization of bandwidth allocation and data transmission efficiency can be expressed by the following formula:.

[0056]

[0057] in, Represents the total data transfer time, is the propagation delay, which is the propagation time of the signal in the physical medium, is the transmission delay, which is the time required for a data packet to be transmitted on the link. Queuing delay is the waiting time when data is forwarded between devices. By optimizing these parameters, such as adjusting network paths, increasing bandwidth, reducing congestion and waiting, the , improving the overall transmission efficiency of the system. Through the above steps, the distributed monitoring units are interconnected with the unified fusion management software system to build a stable and reliable IP transmission network that can efficiently handle large-scale data traffic from devices at all levels.

[0058] In a specific embodiment, the process of executing step S3 may specifically include the following steps:

[0059] According to the IP transmission network and the preset interface protocol specifications, formulate the monitoring unit access test plan, obtain the test item list, and test the data collection function of the monitoring unit based on the test item list to obtain the data collection performance indicators;

[0060] Verify the remote signaling, remote control, telemetry and remote adjustment functions of the monitoring unit item by item to obtain the verification results of the four remote functions, and test the communication stability between the monitoring unit and the unified fusion management software system to obtain communication reliability data;

[0061] Based on the communication reliability data, simulate network abnormalities, test the data retransmission function of the monitoring unit, obtain data integrity test results, and evaluate the automatic recovery capability of the monitoring unit after the device is restarted to obtain automatic recovery capability evaluation data;

[0062] Generate a comprehensive evaluation report on monitoring unit functions and communication reliability based on data collection performance indicators, four-remote function verification results, communication reliability data, data integrity test results and automatic recovery capability evaluation data;

[0063] Based on the comprehensive evaluation report, access configuration and parameter optimization are performed on the monitoring unit to obtain verification results corresponding to the monitoring unit that meets the standard interface specifications.

[0064] Specifically, a complete test process is designed based on the functional characteristics and communication protocols of various monitoring units in the system to ensure that the monitoring units can work normally when connected to the IP transmission network and maintain efficient communication with the unified integrated management software system. In this process, refer to the preset interface protocol specifications to ensure that various monitoring units can seamlessly connect with the management system. The solution includes a list of test items, covering the core functions of the monitoring unit, such as data acquisition, communication, remote control, and telemetry. The list of test items defines the various functions that need to be tested and their expected performance standards. Based on the list of test items, the data acquisition function of the monitoring unit is tested to verify whether the monitoring unit can collect the required data accurately and in a timely manner. By comparing the data collected by the monitoring unit with the standard value, the performance indicators of its data acquisition are obtained, such as acquisition frequency, accuracy, delay, etc. These performance indicators can be expressed by formulas. For example, assuming that the delay of data acquisition is The accuracy of the collection is The acquisition frequency is , then the acquisition performance of the system can be expressed by the comprehensive formula:

[0065]

[0066] in, Represents the overall performance of data acquisition, The higher the value, the better the acquisition accuracy. and Represent the delay and frequency of collection respectively. The smaller the delay and the higher the frequency, the better the collection performance. The remote signaling, remote control, telemetry and remote adjustment functions of the monitoring unit are verified item by item to obtain the verification results of the four remote functions. The remote signaling function is responsible for the remote signal transmission of the equipment status, the remote control function allows the remote control of the equipment, the telemetry function is used to collect the measurement data of the equipment, and the remote adjustment function is responsible for adjusting the operating parameters of the equipment. By verifying these four remote functions item by item, it is ensured that the monitoring unit can maintain accuracy and stability in remote communication. Test the communication stability between the monitoring unit and the unified fusion management software system. Communication stability determines whether the monitoring unit can maintain the reliability and consistency of data transmission in different network environments. At this stage, by simulating high concurrency scenarios, network jitter or bandwidth fluctuations, the system's anti-interference ability is tested to obtain communication reliability data, including the response time, packet loss rate and network connection stability of the monitoring unit under high load. The formula for communication stability can be expressed as:

[0067]

[0068] in, For communication reliability, is the number of packets successfully transmitted, is the communication delay, is the network load. The more data packets are successfully transmitted, the lower the delay and load, and the higher the communication reliability. In order to verify the robustness of the monitoring unit, based on the communication reliability data, different network abnormalities are simulated, and the data retransmission function of the monitoring unit in these situations is tested. The data retransmission function is the key to ensure that the lost data can be resent and successfully arrive when the network is abnormal. By testing its data recovery ability under abnormal conditions, the data integrity test results are obtained, which measures the recovery rate after data loss and whether the integrity of the data can be guaranteed after retransmission. The automatic recovery ability of the monitoring unit after the device is restarted is evaluated. The automatic recovery function is the stability guarantee of the system. Especially after the device is restarted, the monitoring unit must be able to quickly restore communication with the management system and continue to perform the collection task. By testing the automatic recovery time after the device is restarted and the data transmission status after recovery, the automatic recovery ability evaluation data is obtained, which reflects the recovery speed and reliability of the system under abnormal conditions. After completing all the above tests, a comprehensive evaluation report on the monitoring unit function and communication reliability is generated based on various data, including data acquisition performance indicators, four remote function verification results, communication reliability data, data integrity test results and automatic recovery ability evaluation data. Based on the comprehensive evaluation report, the monitoring unit is accessed and configured and parameters are optimized. By analyzing the data in the report, the deficiencies in the actual use of the monitoring unit are found, and its overall performance is improved by optimizing communication parameters, adjusting data collection frequency, or optimizing network connection settings. Through the above test and optimization steps, the final verification result of the monitoring unit that meets the standard interface specifications is obtained, ensuring that the monitoring unit can seamlessly cooperate with the unified integrated management system in the IP transmission network, and can cope with various complex network situations to achieve reliable data transmission and efficient management.

[0069] In a specific embodiment, the process of executing step S4 may specifically include the following steps:

[0070] Analyze the verification results, identify the online monitoring units that do not meet the standard interface specifications, and obtain a list of non-standard monitoring units;

[0071] According to the list of non-standard monitoring units, protocol characteristics analysis is performed on each type of non-standard monitoring unit to obtain a protocol characteristics data set;

[0072] Based on the protocol characteristic data set, a protocol conversion algorithm is designed to obtain a protocol conversion module, and a functional test is performed on the protocol conversion module to verify the correctness of the data format conversion and obtain the conversion function verification result;

[0073] According to the conversion function verification result, the protocol conversion module is optimized and adjusted to obtain an optimized protocol conversion module, and the optimized protocol conversion module is used to perform real-time conversion on the data of the non-standard monitoring unit to obtain a data stream that meets the standard interface specification;

[0074] Perform a data integrity check on the data stream that complies with the standard interface specification to obtain a data integrity check report, and based on the data integrity check report, connect the converted data to the unified fusion management software system to obtain access confirmation information for the non-standard monitoring unit.

[0075] Specifically, the verification results are analyzed to identify the online monitoring units that do not meet the standard interface specifications. This process involves checking the communication protocol, data format, transmission delay, etc. of the device. If the device does not match the standard expected by the system, it is marked as a non-standard monitoring unit and included in the list of non-standard monitoring units. According to the list of non-standard monitoring units, the protocol characteristics of each model of non-standard monitoring units are analyzed. Different devices use different communication protocols, which may involve the data format, transmission method, encoding scheme, etc. of the device. The protocol characteristics of each device are analyzed to understand its specific behavior and characteristics in data transmission. Through analysis, a protocol characteristic data set is formed to record information such as the communication specification, data packet format, and transmission mechanism of the device. Based on the protocol characteristic data set, a protocol conversion algorithm is designed to convert the data format of the non-standard monitoring unit into a data format that meets the standard interface specification. According to the information in the protocol characteristic data set, corresponding conversion rules are designed for the protocols of different devices. For example, if a certain device uses a custom binary protocol, and the standard interface specification uses the JSON format, then the conversion algorithm needs to parse and convert the data of the device from the binary format to the JSON format. By writing the corresponding conversion rules and logic, a protocol conversion module is obtained. The protocol conversion module is functionally tested to verify the correctness of the data format conversion. In the functional test, the data of the non-standard monitoring unit is input into the conversion module to observe whether the converted data meets the standard interface specifications. The test process needs to cover all possible communication scenarios and data types to ensure that the conversion module can handle multiple situations and accurately convert all data formats. According to the verification results of the functional test, the protocol conversion module is optimized and adjusted. The goal of optimization is to improve conversion efficiency, reduce latency, and ensure the accuracy of conversion. For example, the performance of the module can be optimized by improving the data parsing algorithm, reducing unnecessary conversion steps, or adding a cache mechanism. After optimization, the final optimized protocol conversion module is obtained. The data of the non-standard monitoring unit is converted in real time using the optimized protocol conversion module to ensure that the data stream generated by it meets the standard interface specifications. This process requires the conversion module to be able to handle the real-time data input from the device and quickly and efficiently convert it into a standard data format that meets the system requirements. The data stream that meets the standard interface specifications is checked for data integrity to obtain a data integrity check report to ensure that the converted data is not lost, damaged, or deformed. The inspection process is completed by comparing the content, length, and structure of the original data with the converted data. Based on the data integrity check report, the converted data is formally connected to the unified fusion management software system. In this process, the legitimacy and format of the data are verified to ensure that it can be processed and analyzed together with other standard monitoring unit data. When the system successfully receives and processes these converted data, it generates access confirmation information for non-standard monitoring units.In order to quantify the effect of system optimization, a formula is introduced to express the efficiency improvement of data conversion. Assume that the processing time of the original conversion module is. , the optimized processing time is , the efficiency improvement rate can be expressed by the following formula:

[0076]

[0077] in, Represents the percentage of efficiency improvement, is the processing time of the original conversion module, is the processing time of the optimized conversion module. The performance improvement of the optimized conversion module is measured by the formula. For example, assuming that the original conversion time of a monitoring unit is 10 milliseconds, and the optimized conversion time is 5 milliseconds, then the efficiency improvement rate is:

[0078]

[0079] This means that the optimized protocol conversion module has increased efficiency by 50% and can handle data conversion tasks from non-standard monitoring units more quickly.

[0080] In a specific embodiment, the process of executing step S5 may specifically include the following steps:

[0081] Identify the types of monitoring units connected to the unified integrated management software system to obtain a list of smart device types, and analyze the communication protocol of each type of smart device based on the list of smart device types to obtain protocol feature data;

[0082] Based on the protocol feature data, design a dedicated protocol parsing algorithm for various types of smart devices, obtain the initial protocol parsing module, and perform functional testing on the initial protocol parsing module to verify its parsing accuracy and obtain the parsing function test results;

[0083] According to the analysis function test results, the initial protocol analysis module is optimized to obtain a dedicated protocol analysis module, and the dedicated protocol analysis module is used to analyze the communication data of various smart devices to obtain standardized device data;

[0084] Perform data flow analysis on standardized device data to identify inefficient communication protocols, obtain a list of protocol optimization targets, and optimize the design of the identified inefficient communication protocols based on the list of protocol optimization targets, and obtain the device communication data set.

[0085] Specifically, all monitoring units connected to the system are scanned and preliminarily identified. Monitoring units are usually divided into multiple types, such as sensors, cameras, actuators, etc., and each type of device has unique communication characteristics and functions. By identifying the types of these devices, a list of smart device types is generated. For example, sensors are based on the MODBUS protocol, while cameras use the RTSP streaming protocol. Identifying different device types helps to design an adaptive protocol parsing mechanism. The communication protocol of each type of smart device is analyzed. The protocol used by each smart device has its specific format, field, and data structure. For example, some devices use a simple TCP / IP-based transmission protocol, while other devices involve complex application layer protocols. By analyzing the communication protocols of various types of devices, a protocol feature data set is formed. The data set contains information such as the communication mode, data format, and handshake process of the device. For example, for sensors with MODBUS protocol, the protocol feature data includes key information such as function code, register address, and data length; while for cameras, the protocol feature data set includes information such as frame rate and encoding method. Based on the protocol feature data, a dedicated protocol parsing algorithm adapted to various types of smart devices is designed. The raw data sent by the device is converted into a standardized data format that the system can understand. This process involves parsing the communication data, extracting fields, and converting data types. For example, for MODBUS sensor devices, the protocol parsing algorithm extracts register values ​​from the data packet and converts them into meaningful measurement data; for RTSP protocol camera devices, the parsing algorithm needs to process the video stream and extract key metadata information. The initial protocol parsing module is formed by combining the protocol feature data and the communication specification. After the initial protocol parsing module is designed, functional testing is performed to verify its parsing accuracy. During the test, different types of devices are connected to the system, actual communication data is sent, and the parsing module is verified to correctly extract and convert this data. The functional test results show the performance of the parsing module when processing different device protocols, and record key indicators such as error rate, data loss, and processing time. Based on the parsing functional test results, the initial protocol parsing module is optimized. The optimization goals include improving parsing efficiency, reducing processing delays, and improving data conversion accuracy. For example, if the functional test finds that the communication data parsing speed of some devices is slow, the processing is accelerated by introducing parallel processing or optimizing data caching. The optimized and adjusted dedicated protocol parsing module will be more efficient and able to handle the communication data streams of multiple devices. The optimized module improves the overall performance of the system and enhances its stability in high-concurrency data scenarios. The optimized dedicated protocol parsing module is used to parse the communication data of various smart devices in real time to obtain standardized device data. For example, the raw register data from the MODBUS sensor is converted into standard physical quantity data such as temperature or humidity, while the real-time streaming data of the camera is standardized into an image or video stream in a specific format.Data flow analysis is performed on standardized data to identify inefficient communication protocols that exist during system operation. In data flow analysis, the focus is on data transmission delay, data packet size, frequency, and interaction delay between devices. If some protocols show obvious inefficiency in data transmission, such as frequent handshakes, redundant data packets, or unnecessary retransmissions, these protocols will be identified as optimization targets. Through this analysis, a list of protocol optimization targets is generated, listing the protocols that affect the overall efficiency of the system. Based on the list of protocol optimization targets, the identified inefficient communication protocols are optimized. Optimization can be carried out from multiple angles, such as improving transmission efficiency by simplifying the handshake process in the protocol, compressing data packets, or merging repeatedly transmitted data streams. For some devices, their communication performance can be significantly improved by introducing more efficient communication protocols (such as switching from old serial protocols to modern IP protocols). For example, if it is found that the MODBUS protocol of some sensors causes network congestion due to excessively high data frequency, its performance can be optimized by adjusting the transmission frequency or transmitting data in batches. Through optimized design, communication delays are significantly reduced, the overall efficiency of data transmission is improved, and an optimized device communication data set is formed. In order to quantify the effect of protocol optimization, the following formula is used to measure the improvement in communication efficiency:.

[0086]

[0087] in, Indicates the percentage of improvement in communication efficiency, is the data transmission delay before optimization, is the optimized data transmission delay. Through this formula, the performance improvement effect brought by the optimization is obtained. For example, assuming that in the initial state, the delay caused by the MODBUS communication protocol of a certain device is 100ms, and the delay is reduced to 50ms through the optimized design, then the efficiency improvement is:

[0088] This shows that after the protocol is optimized, the communication efficiency is increased by 50%, which greatly improves the overall performance of the system. Through the above steps, the standardized management and optimization of communication protocols for various smart devices can be finally achieved.

[0089] In a specific embodiment, the process of executing step S6 may specifically include the following steps:

[0090] Perform data standardization on various smart devices and device communication data sets to obtain a standardized data model, and build a unified device model and data model based on the standardized data model to obtain a fused data structure;

[0091] Perform real-time analysis on the data in the fusion data structure to obtain the equipment operation status evaluation results, and establish a fault warning model based on the equipment operation status evaluation results to obtain a fault warning rule set;

[0092] Based on the fault warning rule set, the equipment operation data is monitored in real time to obtain alarm information, and the alarm information is intelligently classified and processed to obtain a hierarchical alarm processing solution;

[0093] According to the hierarchical alarm processing plan, a visual management interface is developed to obtain a multi-dimensional data display module. Based on the multi-dimensional data display module, expert maintenance experience is integrated to generate intelligent fusion management decision information.

[0094] Specifically, data standardization is performed on various smart devices and device communication data sets. For example, some sensors transmit data in binary format, while cameras use the RTSP protocol to transmit video streams, converting data from different devices into a unified format. During the standardization process, the key fields, data types, and units of the data are converted to ensure that all data can be processed and analyzed on a unified platform to obtain a standardized data model. Based on the standardized data model, a unified device model and data model are constructed. The device model describes the physical properties, functions, and working status of each device, while the data model describes the structure and meaning of the data generated by the device. For example, the device model of a temperature sensor contains the type, location, and current status of the sensor, while the data model describes the unit of the temperature value, the measurement time, etc. A fused data structure is formed by unifying and integrating the models and data structures of different devices. The data in the fused data structure is analyzed in real time to evaluate the operating status of the device. By analyzing the data stream of the device in real time, the health status, working efficiency, and potential failure points of the device can be detected. For example, the historical data of the temperature sensor shows an abnormally high temperature trend, which indicates that the device is overheating or about to fail. Through data mining and analysis algorithms, the evaluation results of the device's operating status are generated. Various parameters of equipment operation, such as operating temperature, response time, power consumption, etc., are important indicators for evaluating equipment status. Based on the evaluation results of equipment operation status, a fault warning model is established. The warning model predicts potential faults through the historical data and current status of the equipment. For example, if the operating temperature of a device exceeds the normal range and the temperature continues to rise, it can be analyzed based on historical data that it will fail within a certain period of time. By analyzing the key parameters and abnormal patterns of the equipment, a fault warning rule set is generated to define which device parameter abnormalities may cause failures, and set warning thresholds based on different parameters. The establishment of the rule set enables the system to issue a warning before the equipment fails, so that preventive measures can be taken in advance to reduce the risk of equipment damage. Based on the fault warning rule set, the equipment operation data is monitored in real time. When the operating parameters of the equipment exceed the preset threshold, an alarm message is triggered. The alarm message is intelligently classified. By analyzing the severity, impact range and importance of the alarm message, a hierarchical alarm processing solution is generated, providing different processing processes and priorities for each type of alarm, ensuring that the system can efficiently respond to various problems. According to the hierarchical alarm processing scheme, a visual management interface is developed to intuitively display the various types of equipment in the system and their operating status, and provide real-time visual feedback based on the hierarchical alarm situation. Through the multi-dimensional data display module, the operating data of the equipment can be viewed from multiple angles. For example, the historical temperature data of the equipment can be viewed through a line chart, the workload of different devices in the network can be observed through a heat map, and the health status of the equipment can be monitored in real time through the warning indicator.In order to enhance the intelligence of the system, based on the multi-dimensional data display module, the expert maintenance experience is integrated to generate intelligent fusion management decision information to provide the best handling suggestions for each fault. For example, when the alarm of a certain device is triggered, a specific maintenance operation plan is proposed by referring to the fault history of similar devices and combining the advice of experts. Through the intelligent decision-making mechanism, not only can faults be prevented, but also an optimized maintenance plan can be provided for the long-term operation of the equipment. In this process, the performance and alarm efficiency of the system are measured by the following formula. Assume that the real-time response time of the system is. , the accuracy of fault warning is , the alarm processing efficiency is , then the efficiency of the overall system can be expressed as:

[0095]

[0096] in, Represents the overall efficiency of the system, The higher it is, the higher the accuracy of system fault warning is; The lower it is, the faster the system responds; The efficiency of alarm processing is measured. The higher the efficiency, the faster the system can process alarm information. For example, if the system's fault warning accuracy is 90%, the response time is 2 seconds, and the alarm processing efficiency is 80%, then the overall efficiency of the system can be calculated as:

[0097]

[0098] In this way, the overall efficiency of the system in dealing with equipment failures is quantified.

[0099] Furthermore, the execution step performs real-time analysis on the data in the fused data structure to obtain the equipment operation status evaluation result, and establishes a fault warning model based on the equipment operation status evaluation result. The process of obtaining the fault warning rule set can specifically include the following steps: performing data stratification processing on the fused data structure to obtain a three-layer data structure of the equipment layer, the system layer and the business layer; based on the equipment layer data, constructing an equipment status evaluation neural network model, the equipment status evaluation neural network model includes an input layer, three hidden layers and an output layer, each hidden layer uses a ReLU activation function and Dropout regularization, and the output layer uses a Softmax function; inputting the equipment layer data into the equipment status evaluation neural network model, and obtaining the equipment status evaluation result through a forward propagation algorithm; according to the system layer data and the equipment status evaluation result, establishing a system performance evaluation decision tree model, the decision tree model adopts the C4.5 algorithm, uses the information gain ratio as the feature selection criterion, and constructs the decision tree structure through a recursive method; inputting the system layer data and the equipment status evaluation result into the system performance evaluation decision tree model, and obtaining the system performance evaluation result through a depth-first search algorithm Based on the business layer data, equipment status assessment results and system performance assessment results, a business impact analysis support vector machine model is constructed. The support vector machine model adopts radial basis kernel function and is trained using sequence minimum optimization algorithm. The business layer data, equipment status assessment results and system performance assessment results are input into the business impact analysis support vector machine model, and the business impact analysis results are obtained through kernel function mapping and maximum interval classification. According to the equipment status assessment results, system performance assessment results and business impact analysis results, a fuzzy logic reasoning system is used to generate comprehensive risk assessment indicators. The fuzzy logic reasoning system includes four parts: input fuzzification, fuzzy rule base, fuzzy reasoning engine and output defuzzification. Based on the comprehensive risk assessment indicators, the time series analysis method is used to construct the ARIMA prediction model, the model parameters are estimated by the least squares method, and the Box-Jenkins method is used for model identification, parameter estimation and model verification. The historical comprehensive risk assessment indicator data is input into the ARIMA prediction model, and the fault warning rule set is obtained through the iterative prediction algorithm. The fault warning rule set includes warning threshold, warning level and warning trigger condition.

[0100] Furthermore, the execution step is based on the fault warning rule set to monitor the equipment operation data in real time, obtain alarm information, and intelligently classify and process the alarm information to obtain a hierarchical alarm processing solution. The process can specifically include the following steps: parsing the fault warning rule set, extracting the alarm trigger conditions and thresholds, and obtaining an alarm monitoring rule base; based on the alarm monitoring rule base, building a real-time data stream processing engine, using the Apache Flink framework, setting parallelism and checkpoint mechanism, and obtaining an alarm detection module; inputting the equipment operation data into the alarm detection module, and processing the data in real time through the sliding window algorithm to obtain the original alarm event; deduplication and aggregation processing of the original alarm event, using the time series correlation analysis method to obtain a related alarm set; based on the related alarm set, building an alarm classification model, using the random forest algorithm, optimizing the model parameters through feature engineering and cross-validation, and obtaining an alarm classifier; inputting the related alarm set into the alarm classifier, and obtaining the classified alarm information through multi-level classification processing; according to the classified alarm information, Establish an alarm severity assessment model, use fuzzy comprehensive evaluation method, set weight coefficients and membership functions, and obtain alarm level assessment results; based on the alarm level assessment results, design the alarm processing process, use workflow engine technology to define processing steps and role allocation, and obtain the alarm processing workflow; integrate the alarm processing workflow with the existing operation and maintenance system, realize data interaction and task distribution through API interface, and obtain the integrated alarm processing system; based on the integrated alarm processing system, generate an alarm processing solution template library, use case-based reasoning algorithm, and obtain graded alarm processing solutions through historical processing experience matching and dynamic updating.

[0101] The above describes the unified integration management method of the flat cloud architecture in the embodiment of the present invention. The following describes the unified integration management device of the flat cloud architecture in the embodiment of the present invention. Figure 2 In an embodiment of the present invention, an embodiment of a unified integrated management device for a flat cloud architecture includes:

[0102] A deployment module is used to deploy a unified converged management software system on a cloud virtual server;

[0103] Building modules are used to build IP-based transmission networks that support multi-level device interconnection and connect distributed monitoring units with a unified integrated management software system;

[0104] A verification module is used to connect the monitoring unit that complies with the standard interface specification to the unified converged management software system based on the IP transmission network, and verify the function and communication reliability of the monitoring unit that complies with the standard interface specification to obtain the verification result;

[0105] A conversion module is used to convert the data of the online monitoring unit that does not conform to the standard interface specification into a data format consistent with the standard interface specification according to the verification result, and connect the converted data to the unified fusion management software system;

[0106] The acquisition module is used to create a dedicated protocol parsing module when the monitoring unit is connected to the unified fusion management software system to connect various intelligent devices to the unified fusion management software system, optimize the communication protocols of various intelligent devices, and obtain the device communication data set;

[0107] The generation module is used to perform flat unified integration management of various intelligent devices and device communication data sets on the unified integration management software system, and generate intelligent integration management decision information.

[0108] Through the collaboration of the above components, unified management of heterogeneous devices is achieved: by building an IP transmission network that supports multi-level device interconnection, the distributed monitoring units are connected to the unified fusion management software system, solving the problem of difficulty in unified management of devices of different manufacturers and types. By converting the data of online monitoring units that do not meet the standard interface specifications into a standard format, seamless access of new and old devices is achieved, greatly improving the compatibility and scalability of the system. By creating a dedicated protocol parsing module, efficient access and communication protocol optimization of various intelligent devices are achieved, and the efficiency and accuracy of data collection are improved. By flattening and fusion management of device communication data sets, intelligent analysis and decision support based on big data are achieved, and the predictive maintenance capability of the system is improved. The cloud deployment and multi-level network architecture enhance the reliability and security of the system and reduce the risk of single point failure. Through a unified management platform and intelligent fault warning and processing mechanism, the labor cost of equipment maintenance and management is greatly reduced. Through data standardization and fusion analysis, the utilization rate of data is improved, providing strong support for business decision-making and network optimization.

[0109] The present invention also provides a computer device, which includes a memory and a processor, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the processor executes the steps of the flat cloud architecture unified integration management method in the above-mentioned embodiments.

[0110] The present invention also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. Instructions are stored in the computer-readable storage medium. When the instructions are executed on a computer, the computer executes the steps of the flat cloud architecture unified fusion management method.

[0111] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems, systems and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0112] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or the whole or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store program code.

[0113] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A unified integrated management method for a flat cloud architecture, characterized in that: The method comprises: Deploy a unified converged management software system on cloud virtual servers; Construct an IP-based transmission network that supports multi-layer device interconnection, and connect the distributed monitoring units to the unified converged management software system; specifically include: designing an IP RAN network architecture according to the network topology structure to obtain a network layer division plan, and based on the network layer division plan, configuring the TCP / IP protocol parameters of the IP RAN device to obtain the access layer network configuration; verifying the access layer network configuration to obtain access layer network connection status data, and configuring the 10G circuit parameters of the first device and the second device according to the access layer network connection status data to obtain the aggregation layer network configuration; based on the aggregation layer network configuration, setting the routing table and forwarding rules of the third device and the fourth device to obtain the first core layer network configuration; based on the first core layer network configuration, adjusting the 100G circuit parameters and QoS policy of the fifth device and the sixth device to obtain the second core layer network configuration; based on the second core layer network configuration, setting the EPC The BGP protocol parameters and VPN tunnel configuration of the CE core network equipment are used to obtain the core network access configuration; an end-to-end communication test is performed on the core network access configuration, the network path and bandwidth allocation are adjusted, an IP-based transmission network supporting multi-level device interconnection is obtained, and the distributed monitoring units are connected to the unified converged management software system; Based on the IP transmission network, a monitoring unit that complies with the standard interface specification is connected to the unified fusion management software system, and the function and communication reliability of the monitoring unit that complies with the standard interface specification are verified to obtain a verification result; According to the verification result, the data of the online monitoring unit that does not conform to the standard interface specification is converted into a data format consistent with the standard interface specification, and the converted data is connected to the unified fusion management software system; The monitoring unit is connected to the unified fusion management software system to create a dedicated protocol parsing module to connect various intelligent devices to the unified fusion management software system, and the communication protocols of the various intelligent devices are optimized to obtain device communication data sets; On the unified fusion management software system, the various types of intelligent devices and the device communication data sets are managed in a flat unified fusion manner to generate intelligent fusion management decision information.

2. The method for unified integration management of flat cloud architecture according to claim 1, characterized in that: The deployment of a unified converged management software system on a cloud virtual server includes: Design a framework structure of a unified fusion management software system based on the MVC architecture to obtain a software system architecture diagram, and install a target operating system on a cloud virtual server according to the software system architecture diagram to obtain a basic operating environment; Installing a database system in the basic operating environment to obtain a data storage environment, and writing a unified fusion management application code based on the data storage environment to obtain an application source code; Compiling and linking the application source code to obtain an executable unified fusion management application, and deploying the executable unified fusion management application to the cloud virtual server to obtain an initial management software system; Perform database splitting, data cache configuration, message subscription settings and load balancing adjustment on the initial management software system to obtain an optimized management software system; The Nginx server is configured in the optimized management software system, and log analysis, heartbeat detection, capacity assessment, flow control and service classification parameters are set to obtain a unified integrated management software system.

3. The method for unified integration management of flat cloud architecture according to claim 1, characterized in that: Based on the IP-based transmission network, the monitoring unit that complies with the standard interface specification is connected to the unified fusion management software system, and the function and communication reliability of the monitoring unit that complies with the standard interface specification are verified to obtain the verification result, including: According to the IP transmission network and the preset interface protocol specification, a monitoring unit access test plan is formulated to obtain a test item list, and based on the test item list, the data acquisition function of the monitoring unit is tested to obtain data acquisition performance indicators; Verify the remote signaling, remote control, remote measurement and remote adjustment functions of the monitoring unit item by item to obtain the verification results of the four remote functions, and test the communication stability between the monitoring unit and the unified fusion management software system to obtain communication reliability data; Based on the communication reliability data, simulate network abnormalities, test the data retransmission function of the monitoring unit to obtain data integrity test results, and evaluate the automatic recovery capability of the monitoring unit after the device is restarted to obtain automatic recovery capability evaluation data; Generate a comprehensive evaluation report on monitoring unit function and communication reliability based on the data acquisition performance index, the four remote function verification results, the communication reliability data, the data integrity test results and the automatic recovery capability evaluation data; Based on the comprehensive evaluation report, access configuration and parameter optimization are performed on the monitoring unit to obtain verification results corresponding to the monitoring unit that meet the standard interface specifications.

4. The method for unified integration management of flat cloud architecture according to claim 1, characterized in that: The step of converting the data of the online monitoring unit that does not conform to the standard interface specification into a data format consistent with the standard interface specification according to the verification result, and connecting the converted data to the unified fusion management software system includes: Analyze the verification results, identify the online monitoring units that do not meet the standard interface specifications, and obtain a list of non-standard monitoring units; According to the non-standard monitoring unit list, a protocol characteristic analysis is performed on each type of non-standard monitoring unit to obtain a protocol characteristic data set; Based on the protocol characteristic data set, a protocol conversion algorithm is designed to obtain a protocol conversion module, and a functional test is performed on the protocol conversion module to verify the correctness of the data format conversion and obtain a conversion function verification result; According to the conversion function verification result, the protocol conversion module is optimized and adjusted to obtain an optimized protocol conversion module, and the optimized protocol conversion module is used to perform real-time conversion on the data of the non-standard monitoring unit to obtain a data stream that meets the standard interface specification; A data integrity check is performed on the data stream that complies with the standard interface specification to obtain a data integrity check report, and based on the data integrity check report, the converted data is connected to the unified fusion management software system to obtain access confirmation information of the non-standard monitoring unit.

5. The method for unified integration management of flat cloud architecture according to claim 1, characterized in that: The monitoring unit is connected to the unified fusion management software system to create a dedicated protocol parsing module to connect various intelligent devices to the unified fusion management software system, and the communication protocols of the various intelligent devices are optimized to obtain device communication data sets, including: Identify the types of monitoring units connected to the unified fusion management software system to obtain a list of smart device types, and analyze the communication protocol of each type of smart device according to the list of smart device types to obtain protocol feature data; Based on the protocol feature data, a dedicated protocol parsing algorithm for various types of smart devices is designed to obtain an initial protocol parsing module, and a functional test is performed on the initial protocol parsing module to verify its parsing accuracy and obtain a parsing function test result; According to the analysis function test results, the initial protocol analysis module is optimized to obtain a dedicated protocol analysis module, and the dedicated protocol analysis module is used to analyze the communication data of various smart devices to obtain standardized device data; Perform data flow analysis on the standardized device data to identify inefficient communication protocols, obtain a protocol optimization target list, and optimize the identified inefficient communication protocols based on the protocol optimization target list, and obtain a device communication data set.

6. The method for unified integration management of flat cloud architecture according to claim 1, characterized in that: The unified fusion management software system performs flat unified fusion management on the various intelligent devices and the device communication data sets to generate intelligent fusion management decision information, including: Performing data standardization processing on the various types of smart devices and the device communication data sets to obtain a standardized data model, and constructing a unified device model and data model based on the standardized data model to obtain a fused data structure; Performing real-time analysis on the data in the fused data structure to obtain equipment operation status evaluation results, and establishing a fault warning model based on the equipment operation status evaluation results to obtain a fault warning rule set; Based on the fault warning rule set, the equipment operation data is monitored in real time to obtain alarm information, and the alarm information is intelligently classified and processed to obtain a hierarchical alarm processing solution; According to the hierarchical alarm processing solution, a visual management interface is developed to obtain a multi-dimensional data display module, and based on the multi-dimensional data display module, expert maintenance experience is integrated to generate intelligent fusion management decision information.

7. A unified integrated management device for a flat cloud architecture, characterized in that: Used to execute the unified fusion management method of the flat cloud architecture according to any one of claims 1 to 6, the flat cloud architecture unified fusion management device comprises: A deployment module is used to deploy a unified converged management software system on a cloud virtual server; A construction module for constructing an IP-based transmission network supporting multi-level device interconnection, connecting distributed monitoring units with the unified fusion management software system; A verification module, used to connect the monitoring unit that complies with the standard interface specification to the unified fusion management software system based on the IP transmission network, and verify the function and communication reliability of the monitoring unit that complies with the standard interface specification to obtain a verification result; A conversion module, used to convert the data of the online monitoring unit that does not conform to the standard interface specification into a data format consistent with the standard interface specification according to the verification result, and connect the converted data to the unified fusion management software system; An acquisition module is used to create a dedicated protocol parsing module when the monitoring unit is connected to the unified fusion management software system to connect various intelligent devices to the unified fusion management software system, optimize the communication protocols of the various intelligent devices, and obtain device communication data sets; The generation module is used to perform flat unified fusion management on the various types of intelligent devices and the device communication data sets on the unified fusion management software system, and generate intelligent fusion management decision information.

8. A computer device, characterized in that: It includes a memory and a processor, the memory stores a computer program that can be run on the processor, and is characterized in that when the processor executes the computer program, it implements the flat cloud architecture unified integration management method described in any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the processor executes the flat cloud architecture unified fusion management method according to any one of claims 1 to 6.

Images