Integrated management system and method for communication equipment of Internet of Things

Abstract

The invention discloses a comprehensive management system and method for communication equipment of the Internet of Things, and aims to solve the technical problems of low operation and maintenance efficiency and low intelligent degree of an existing management system. The system comprises a device discovery and access module used for scanning communication devices in the Internet of Things and identifying device types, device models and basic information of the communication devices; the configuration management and automatic deployment module is used for generating a configuration template, issuing the configuration template to the corresponding communication equipment and verifying whether the configuration is successful or not; the monitoring alarm and log analysis module is used for monitoring the performance index data of the communication equipment, analyzing the log data of the communication equipment to obtain an analysis result, and generating alarm information according to the performance index data and the analysis result; the data analysis and optimization module is used for acquiring equipment operation data of the communication equipment and optimizing the configuration template according to the equipment operation data; and the safety management and strategy control module is used for formulating a safety strategy and carrying out safety control on the communication equipment.

Description

Technical Field

[0001] The present invention relates to the technical field of Internet of Things, and in particular to an integrated management system and method for Internet of Things communication equipment. Background Art

[0002] In the field of integrated management systems for Internet of Things (IoT) communication devices, with the rapid development of IoT technology, the number of devices continues to increase, and the difficulty of management also increases. At present, there are some IoT device management systems on the market, but most systems mainly focus on the basic monitoring and remote control functions of the equipment, lacking comprehensive, efficient and automated management methods.

[0003] Specifically, the existing system has the following deficiencies:

[0004] Device discovery and access: Most systems require manual addition of device information and are unable to achieve automatic device discovery and access, resulting in low management efficiency.

[0005] Configuration management and automated deployment: Traditional configuration management methods usually rely on manual operations and cannot achieve automated distribution and verification of configurations, increasing the possibility of errors.

[0006] Monitoring, alarm and log analysis: Existing systems often only provide simple monitoring functions and lack in-depth log analysis and alarm mechanisms, making it difficult to detect potential problems in a timely manner.

[0007] Data analysis and optimization: Most systems lack data analysis capabilities and cannot provide decision support for configuration optimization, resulting in inefficient resource utilization.

[0008] Security management and policy control: In terms of security, existing systems often only provide basic identity authentication and access control, lacking encryption protection for communication data and real-time monitoring of security policies. Summary of the invention

[0009] The present invention provides an integrated management system and method for Internet of Things communication equipment, which are used to solve the technical problems of low operation and maintenance efficiency and low intelligence level of existing management systems.

[0010] The present invention provides an integrated management system for Internet of Things communication equipment, comprising:

[0011] Device discovery and access module, configuration management and automated deployment module, monitoring alarm and log analysis module, data analysis and optimization module, security management and policy control module;

[0012] The device discovery and access module is used to scan the communication devices in the Internet of Things and identify the device type, device model and basic information of the communication devices;

[0013] The configuration management and automatic deployment module is used to generate a configuration template using the device type, the device model and the basic information, send the configuration template to the corresponding communication device, and verify whether the configuration is successful;

[0014] The monitoring alarm and log analysis module is used to monitor the performance indicator data of the communication device, analyze the log data of the communication device to obtain analysis results, and generate alarm information according to the performance indicator data and the analysis results;

[0015] The data analysis and optimization module is used to obtain the device operation data of the communication device and optimize the configuration template according to the device operation data;

[0016] The security management and policy control module is used to formulate security policies and perform security control on the communication equipment.

[0017] Optionally, the device discovery and access module includes: a network scanning submodule, a device identification submodule, an API interface calling submodule, a device information integration submodule, a device access submodule, and a verification and feedback submodule;

[0018] The network scanning submodule is used to scan the Internet of Things according to preset configuration parameters to obtain active devices;

[0019] The device identification submodule is used to obtain the device type, device model and basic information of the communication device supporting the preset protocol through the preset protocol;

[0020] The API interface calling submodule is used to obtain the device type, device model and basic information of the communication device through the API interface;

[0021] The device information integration submodule is used to integrate the device type, device model and basic information of each communication device to obtain integrated information;

[0022] The device access submodule is used to generate an access script according to the integration information and configuration requirements;

[0023] The verification and feedback submodule is used to collect feedback information of the communication device based on the access script, and verify whether the communication device has successfully accessed through the feedback information.

[0024] Optionally, the configuration management and automated deployment module includes: a configuration template requirement determination submodule, a configuration template design submodule, a template engine submodule, a template engine code writing submodule, and a distribution and verification submodule;

[0025] The configuration template requirement determination submodule is used to determine the configuration template requirement;

[0026] The configuration template design submodule is used to create a configuration template file using the device type, the device model, the basic information and the configuration template requirement;

[0027] The template engine submodule is used to define dynamic variables and write conditional logic;

[0028] The template engine code writing submodule is used to render and generate a configuration template according to the dynamic variables, the conditional logic and the configuration template file;

[0029] The sending and verifying submodule is used to send the configuration template to the corresponding communication device and verify whether the configuration is successful.

[0030] Optionally, the template engine submodule includes a variable definition unit and a conditional logic writing unit;

[0031] The variable definition unit is used to define dynamic variables of the configuration template;

[0032] The conditional logic writing unit is used to write the conditional logic of the configuration template.

[0033] Optionally, the issuing and verification submodule includes: an issuing protocol selection unit, an issuing configuration unit, a configuration verification unit, and a result collection and processing unit;

[0034] The sending protocol selection unit is used to select a sending protocol according to the support status of the communication device;

[0035] The configuration sending unit is used to send the configuration template to the communication device through the sending protocol;

[0036] The configuration verification unit is used to perform application verification on the configuration template and generate a verification result;

[0037] The result collection and processing unit is used to collect the verification result and trigger an operation corresponding to the verification result.

[0038] Optionally, the monitoring alarm and log analysis module includes: a monitoring alarm submodule and a log analysis submodule;

[0039] The monitoring alarm submodule is used to monitor the performance indicator data of the communication device and trigger corresponding monitoring alarm information according to the performance indicator data;

[0040] The log analysis submodule is used to perform abnormal analysis on the log of the communication device, obtain analysis results, and generate corresponding abnormal alarm information according to the analysis results.

[0041] Optionally, the monitoring alarm submodule includes: an alarm rule definition submodule, a monitoring data collection submodule, a data preprocessing submodule, a rule matching submodule, an alarm triggering submodule, and an alarm processing submodule;

[0042] The alarm rule definition submodule is used to generate an alarm rule corresponding to the communication device;

[0043] The monitoring data collection submodule is used to collect performance indicator data of the communication device;

[0044] The data preprocessing submodule is used to perform data preprocessing on the performance indicator data to obtain preprocessed data;

[0045] The rule matching submodule is used to match the pre-processed data with the alarm rule to obtain a matching result;

[0046] The alarm triggering submodule is used to trigger monitoring alarm information when the matching result meets the preset alarm condition;

[0047] The alarm processing submodule is used to adopt corresponding processing measures according to the alarm information.

[0048] Optionally, the log analysis submodule includes: a log data collection and preprocessing unit, a normal behavior model building unit, an anomaly detection unit, an alarm generation and notification unit, and an anomaly processing and feedback unit;

[0049] The log data collection and preprocessing unit is used to collect the log data of the communication device and preprocess the log data to obtain preprocessed log data;

[0050] The normal behavior model building unit is used to build a normal behavior model of the communication device using historical log data;

[0051] The anomaly detection unit is used to input the pre-processed log data into the normal behavior model, perform anomaly detection, and obtain an analysis result;

[0052] The alarm generation and notification unit is used to generate abnormal alarm information when the analysis result shows that the log data is an abnormal log, and send the abnormal alarm information to a preset operation and maintenance personnel;

[0053] The exception processing and feedback unit is used to process the exception alarm information and feed back the exception processing result.

[0054] Optionally, the data analysis and optimization module includes: a data collection and preprocessing submodule, a time series modeling submodule, a model verification and optimization submodule, a trend prediction submodule, and an optimization submodule;

[0055] The data collection and preprocessing submodule is used to collect historical performance indicator data of the communication device; and preprocess the historical performance indicator data to obtain preprocessed performance indicator data;

[0056] The time series modeling submodule is used to establish a time series model using the preprocessing performance indicator data;

[0057] The model verification and optimization submodule is used to verify the time series model and optimize the time series model according to the verification result to obtain an optimized time series model;

[0058] The trend prediction submodule is used to input the equipment operation data into the optimized time series model to obtain performance indicator trend prediction results;

[0059] The optimization submodule is used to optimize the configuration template according to the performance indicator trend prediction result.

[0060] The present invention also provides a method for comprehensive management of Internet of Things communication equipment, comprising:

[0061] Scan the communication devices in the Internet of Things, and identify the device type, device model and basic information of the communication devices;

[0062] Generate a configuration template using the device type, the device model and the basic information, send the configuration template to the corresponding communication device, and verify whether the configuration is successful;

[0063] Monitoring performance indicator data of the communication device, analyzing log data of the communication device to obtain analysis results, and generating alarm information according to the performance indicator data and the analysis results;

[0064] Acquiring device operation data of the communication device, and optimizing the configuration template according to the device operation data;

[0065] Formulate security policies and perform security control on the communication equipment.

[0066] It can be seen from the above technical solutions that the present invention has the following advantages: by scanning the network and using a variety of communication protocols, the system can automatically discover the Internet of Things communication equipment and identify its basic information, realize the comprehensive access of the equipment, and provide a basis for subsequent management and configuration work. The present invention also greatly improves the efficiency of configuration management by designing configuration templates and realizing the automatic distribution and verification of configuration. The configuration is dynamically generated by the template engine and distributed to the device through the standard protocol, which ensures the consistency and accuracy of the configuration and reduces the errors and time costs of manual operation. The present invention also monitors the device status in real time, collects and analyzes log data, promptly discovers the abnormal situation of the device, and notifies the management personnel through the alarm mechanism. This helps to quickly respond to and handle device failures and ensure the stable operation of the Internet of Things system. The present invention also provides decision support for configuration optimization through in-depth analysis of device operation data. Using algorithms such as time series analysis and association rule mining, the performance trend of the device is predicted, and the correlation between configuration items is discovered, so as to put forward reasonable optimization suggestions and improve the operation efficiency and performance of the device. The present invention also strictly controls device access and data by formulating security policies. Use technical means such as identity authentication, access control, and data encryption to ensure that only authorized users can access equipment and management systems, effectively preventing data leaks and security threats. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0068] Figure 1 A structural block diagram of an integrated management system for Internet of Things communication equipment provided by an embodiment of the present invention;

[0069] Figure 2 A flowchart of the steps of a comprehensive management method for Internet of Things communication equipment provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0070] The embodiments of the present invention provide an integrated management system and method for Internet of Things communication equipment, which are used to solve the technical problems of low operation and maintenance efficiency and low intelligence level of existing management systems.

[0071] In order to make the purpose, features and advantages of the present invention more obvious and easy to understand, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described below are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0072] See also Figure 1 , Figure 1 A structural block diagram of an Internet of Things communication equipment integrated management system provided by an embodiment of the present invention.

[0073] The present invention provides an integrated management system for Internet of Things communication equipment, which is characterized by comprising:

[0074] Device discovery and access module 11, configuration management and automated deployment module 12, monitoring alarm and log analysis module 13, data analysis and optimization module 14, security management and policy control module 15;

[0075] The device discovery and access module 11 is used to scan the communication devices in the Internet of Things and identify the device type, device model and basic information of the communication devices;

[0076] The configuration management and automated deployment module 12 is used to generate a configuration template using the device type, device model and basic information, send the configuration template to the corresponding communication device, and verify whether the configuration is successful;

[0077] The monitoring alarm and log analysis module 13 is used to monitor the performance indicator data of the communication equipment, analyze the log data of the communication equipment to obtain the analysis results, and generate alarm information according to the performance indicator data and the analysis results;

[0078] The data analysis and optimization module 14 is used to obtain the device operation data of the communication device and optimize the configuration template according to the device operation data;

[0079] The security management and policy control module 15 is used to formulate security policies and perform security control on communication devices.

[0080] In the embodiment of the present invention, the device discovery and access module 11 includes: a network scanning submodule, a device identification submodule, an API interface calling submodule, a device information integration submodule, a device access submodule, and a verification and feedback submodule;

[0081] The network scanning submodule is used to scan the Internet of Things and obtain active devices according to preset configuration parameters;

[0082] In the specific implementation, the system first configures a network scanner (such as Nmap, Zabbix Discoverer, etc.), which can be configured with parameters such as the IP address range and port number to be scanned. The scanner will start scanning the network according to the configured parameters, trying to connect to the preset port on each IP address to discover active devices on the network.

[0083] The device identification submodule is used to obtain the device type, device model and basic information of the communication device supporting the preset protocol through the preset protocol;

[0084] In a specific implementation, once the scanner finds an active device, the scanner can try to communicate with the device using protocols such as SNMP, SSH, and MQTT.

[0085] For devices that support SNMP, the scanner sends an SNMP GET request to the device’s specific OID (Object Identifier) ​​to obtain information such as device type, device model, serial number, manufacturer, etc.

[0086] For other protocols like SSH or MQTT, the scanner attempts to connect to the corresponding port of the device and sends specific commands or requests to obtain device information.

[0087] The API interface calling submodule is used to obtain the device type, device model and basic information of the communication device through the API interface;

[0088] In a specific implementation, if the communication device supports the API interface provided by the manufacturer, the system can obtain more detailed device information by calling these APIs.

[0089] The API interface usually provides a set of functions or methods for querying device status, configuration, performance and other data.

[0090] The system obtains device information by sending HTTP or HTTPS requests to the API interface and parsing the returned data in JSON or XML format.

[0091] The device information integration submodule is used to integrate the device type, device model and basic information of each communication device to obtain integrated information;

[0092] In the specific implementation, the system will integrate the device information obtained through network scanning, protocol communication and API interface calls.

[0093] The integrated device information includes basic information such as the device's IP address, MAC address, type, model, manufacturer, serial number, etc.

[0094] The system stores this information in the database for use by subsequent configuration management, monitoring alarm, data analysis and other modules.

[0095] The device access submodule is used to generate access scripts based on the integrated information and configuration requirements;

[0096] After the device information is integrated, the system will automatically generate the corresponding configuration template or access script based on the device type and configuration requirements.

[0097] The configuration template or access script contains the parameters, authentication information, communication protocol, etc. required for device connection.

[0098] The system applies configuration templates or access scripts to devices through automation tools (such as Ansible and Puppet) to achieve automatic access to devices.

[0099] The verification and feedback submodule is used to collect feedback information from the communication device based on the access script, and verify whether the communication device has successfully accessed through the feedback information.

[0100] In the specific implementation, after the device is connected, the system will collect feedback information from the device through mechanisms such as SNMP Trap and Syslog to verify whether the communication device is successfully connected and running normally.

[0101] If the device fails to connect or operates abnormally, the system will generate a corresponding alarm notification and prompt the administrator to manually intervene or adjust the configuration.

[0102] Through the device discovery and access module, the comprehensive management system of IoT communication equipment can realize automatic discovery, identification, access and verification of equipment, providing basic support for subsequent configuration management, monitoring alarm, data analysis and other functions.

[0103] In the embodiment of the present invention, the configuration management and automated deployment module 12 includes: a configuration template requirement determination submodule, a configuration template design submodule, a template engine submodule, a template engine code writing submodule, and a distribution and verification submodule;

[0104] The configuration template requirement determination submodule is used to determine the configuration template requirement;

[0105] In a specific implementation, the configuration template requirements include the parameters that need to be configured, the relationship between configuration items, and possible conditional branches.

[0106] The configuration template design submodule is used to create a configuration template file using device type, device model, basic information, and configuration template requirements;

[0107] In the specific implementation, you can use a text editor (such as Notepad++, Sublime Text, VS Code, etc.) or a dedicated configuration management tool (such as Ansible, Chef, Puppet, etc.) to create a configuration template file. This file is usually a text file that contains static text and dynamic variables.

[0108] The template engine submodule is used to define dynamic variables and write conditional logic;

[0109] In the specific implementation, you can introduce the syntax of the template engine (such as Jinja2) in the configuration template to define dynamic variables and conditional logic. Jinja2 is a Python template engine used to dynamically generate HTML, XML or any other text-based format.

[0110] In one example, the template engine submodule includes a variable definition unit and a conditional logic writing unit;

[0111] Variable definition unit, used to define dynamic variables of configuration templates;

[0112] The conditional logic writing unit is used to write the conditional logic of the configuration template.

[0113] In the specific implementation, you can use the {{}} syntax to define dynamic variables in the configuration template. These variables can be replaced by specific values ​​when the final configuration file is generated. And use the control structures provided by the template engine (such as conditional judgment, loop, etc.) to write conditional logic in the template. This allows different configurations to be generated according to different conditions.

[0114] Template engine code writing submodule, used to render and generate configuration templates based on dynamic variables, conditional logic and configuration template files;

[0115] In the specific implementation, you can write code that interacts with the template engine in a Python script or other application. This usually includes steps such as loading template files, defining variable values, and rendering templates.

[0116] In an example, suppose there is a configuration template for a network device (such as a router) that needs to generate different configurations based on different device models and IP addresses.

[0117] Configuration template file (template.j2)

[0118]

[0119] In this example, a configuration template containing dynamic variables is defined, and Python and Jinja2 template engines are used to render the template and generate a specific configuration file. This process can generate different configuration files based on different device parameters, achieving automation and flexibility in configuration.

[0120] The sending and verification submodule is used to send the configuration template to the corresponding communication device and verify whether the configuration is successful.

[0121] In the specific implementation, the configuration template is sent to the device using protocols such as NETCONF, YANG, or TR-069, and the configuration verification results are collected through mechanisms such as SNMP Trap and Syslog.

[0122] In one example, the issuing and verification submodule includes: an issuing protocol selection unit, an issuing configuration unit, a configuration verification unit, and a result collection and processing unit;

[0123] A sending protocol selection unit, used for selecting a sending protocol according to the support status of the communication device;

[0124] In the specific implementation, NETCONF, YANG or TR-069 are selected as the communication protocol for configuration delivery according to the support of the communication equipment. These protocols provide standard mechanisms for remote management and configuration of network devices.

[0125] A configuration sending unit, used to send the configuration template to the communication device through a sending protocol;

[0126] In the specific view, when using NETCONF and YANG to deliver the configuration template, the process is as follows:

[0127] NETCONF session establishment: The management system (NMS) establishes a NETCONF session with the target device, usually using SSH as the transport layer.

[0128] YANG model: The management system needs to understand the YANG model supported by the target device in order to correctly generate and deliver configurations.

[0129] The NMS converts the configuration template into a data structure that conforms to the YANG model and sends it to the communication device through a NETCONF session.

[0130] When using TR-069 to deliver a configuration template, the process is as follows:

[0131] CWMP session establishment: The NMS establishes a TR-069 (also known as CWMP, CPE WAN Management Protocol) session with the target device.

[0132] Parameter set definition: The NMS defines a parameter set that contains configuration information.

[0133] Parameter set delivery: The NMS delivers the parameter set to the communication device through the CWMP session.

[0134] A configuration verification unit, used to perform application verification on the configuration template and generate a verification result;

[0135] In the specific implementation, after receiving the configuration, the device can try to apply the configuration. If the configuration is successfully applied, the device may send an SNMP Trap to notify the NMS of the configuration success. If the configuration fails, the device will also send an SNMP Trap to notify the NMS of the configuration failure, which may include the reason for the failure.

[0136] In another example, the communication device may also send log information during the configuration process to a Syslog server. The NMS may be configured to monitor these Syslog messages to obtain detailed information about the configuration verification.

[0137] The result collection and processing unit is used to collect the verification results and trigger operations corresponding to the verification results.

[0138] In the specific implementation, the management system (NMS) is responsible for listening to SNMP Trap and Syslog messages and collecting the results of configuration verification. Based on the collected results, the NMS can trigger corresponding operations, such as re-issuing configurations, notifying administrators, and recording logs.

[0139] In an example, suppose there is a router device and you want to use NETCONF and YANG protocols to deliver a configuration template to change its IP address.

[0140] step:

[0141] Use a text editor to write a configuration template that includes the new IP address.

[0142] The management system (NMS) establishes a NETCONF session with the router.

[0143] The NMS reads the YANG model of the router to understand how to correctly build and deliver the configuration.

[0144] The NMS converts the configuration template into a data structure that conforms to the YANG model and sends it to the router through a NETCONF session.

[0145] The router receives the configuration and tries to apply it. If successful, it sends an SNMP Trap to notify the NMS. If unsuccessful, it sends an SNMP Trap or Syslog message containing error information.

[0146] The NMS monitors and collects these messages and takes appropriate actions based on the results.

[0147] This process realizes the automatic delivery and verification of configuration, improves operation and maintenance efficiency and reduces the possibility of human error.

[0148] In the embodiment of the present invention, the monitoring alarm and log analysis module 13 includes: a monitoring alarm submodule and a log analysis submodule;

[0149] The monitoring and alarm submodule is used to monitor the performance indicator data of the communication equipment and trigger the corresponding monitoring and alarm information according to the performance indicator data;

[0150] In the embodiment of the present invention, using a rule-based alarm algorithm to trigger an alarm is one of the core functions of the monitoring alarm and log analysis module. When the performance index of a device exceeds a preset threshold, the system will generate an alarm to notify the administrator or relevant operation and maintenance personnel.

[0151] In one example, the monitoring alarm submodule includes: an alarm rule definition submodule, a monitoring data collection submodule, a data preprocessing submodule, a rule matching submodule, an alarm triggering submodule, and an alarm processing submodule;

[0152] The alarm rule definition submodule is used to generate the alarm rules corresponding to the communication equipment;

[0153] A monitoring data collection submodule is used to collect performance indicator data of communication equipment;

[0154] The data preprocessing submodule is used to preprocess the performance indicator data to obtain preprocessed data;

[0155] The rule matching submodule is used to match the pre-processed data with the alarm rules to obtain the matching results;

[0156] The alarm trigger submodule is used to trigger monitoring alarm information when the matching result meets the preset alarm condition;

[0157] The alarm processing submodule is used to take corresponding processing measures according to the alarm information.

[0158] In the specific implementation, you first need to define alarm rules. These rules include the device performance indicators to be monitored (such as CPU usage, memory usage, network bandwidth, etc.), the corresponding thresholds, and the triggering conditions of the alarm (such as exceeding the threshold for a certain period of time, exceeding the threshold instantly, etc.).

[0159] Next, use monitoring tools (such as Zabbix, Prometheus) to collect performance indicator data of IoT communication devices in real time. This data can be obtained from the device through mechanisms such as SNMP and Syslog, and stored in the system's monitoring database.

[0160] Then, the collected monitoring data is preprocessed, including data cleaning, conversion, and aggregation, to ensure the accuracy and availability of the data.

[0161] Then, the preprocessed data is matched with the defined alarm rules. All defined rules are traversed, and the corresponding performance indicators are checked to see if they meet the alarm triggering conditions. If a certain performance indicator meets the alarm triggering conditions (i.e. exceeds the preset threshold), an alarm is triggered. The alarm information can include detailed information such as device name, performance indicator name, current value, threshold, alarm time, etc. The alarm information can be sent to the administrator or relevant operation and maintenance personnel through various means such as email, SMS, and instant messaging tools. After receiving the alarm information, the administrator or operation and maintenance personnel can take corresponding processing measures according to the alarm content, such as checking the device status, adjusting the configuration, and restarting the device. The system can also automatically execute some preset alarm processing scripts or commands to quickly respond to alarm events.

[0162] In an example, suppose there is an IoT communication device and you want to monitor its CPU usage and trigger an alarm when the CPU usage exceeds 80% for more than 5 minutes.

[0163] Define alert rules:

[0164] Metric: CPU usage

[0165] Threshold: 80%

[0166] Trigger condition: exceeds the threshold for 5 consecutive minutes

[0167] Collect monitoring data:

[0168] Use monitoring tools to collect the CPU usage data of the device in real time and store it in the monitoring database.

[0169] Data preprocessing:

[0170] Clean and convert the collected CPU usage data to ensure the accuracy of the data.

[0171] Rule matching:

[0172] The system retrieves the CPU usage data of the device from the monitoring database at regular intervals (such as 1 minute) and matches it with the defined alarm rules.

[0173] If the CPU usage exceeds 80% for five consecutive times (each time at an interval of 1 minute), the alarm triggering condition is met.

[0174] Triggering the alarm:

[0175] The system triggers an alarm and generates alarm information including device name, CPU usage, threshold, alarm time, etc.

[0176] Send the alarm information to the administrator or relevant operation and maintenance personnel via email or SMS.

[0177] Alarm processing:

[0178] After receiving the alarm information, the administrator or operation and maintenance personnel will check the device status and take corresponding measures, such as adjusting the load, optimizing the program, etc.

[0179] The system can also automatically execute preset alarm processing scripts, such as restarting the device or adjusting configuration parameters.

[0180] The log analysis submodule is used to perform abnormal analysis on the logs of the communication equipment, obtain analysis results, and generate corresponding abnormal alarm information according to the analysis results.

[0181] In specific implementation, using machine learning algorithms to detect anomalies in the log data of communication equipment is an important function in the monitoring alarm and log analysis module. Through machine learning algorithms, the system can automatically learn the normal patterns of log data and identify abnormal logs that deviate from these patterns, thereby helping to identify potential equipment failures or security threats.

[0182] In one example, the log analysis submodule includes: a log data collection and preprocessing unit, a normal behavior model building unit, an anomaly detection unit, an alarm generation and notification unit, and an anomaly processing and feedback unit;

[0183] The log data collection and preprocessing unit is used to collect the log data of the communication device and preprocess the log data to obtain preprocessed log data;

[0184] In the specific implementation, log analysis tools (such as ELK Stack) can be used to collect log data of IoT communication devices. Then the log data is preprocessed, including cleaning, formatting, feature extraction and other steps. For example, features such as timestamp, log level, source IP, message content, etc. can be extracted from the log.

[0185] A normal behavior model building unit, used for building a normal behavior model of a communication device using historical log data;

[0186] In the specific implementation, unsupervised learning algorithms (such as autoencoders, isolation forests, etc.) or statistical methods (such as Z-score, IQR, etc.) can be used to build normal behavior models. And the model is trained using historical log data to allow the model to learn the characteristics and patterns of normal logs.

[0187] An anomaly detection unit, used to input the pre-processed log data into the normal behavior model, perform anomaly detection, and obtain analysis results;

[0188] In the specific implementation, the newly collected and pre-processed log data can be input into the trained normal behavior model for anomaly detection. The normal behavior model will determine whether it is abnormal based on the degree of match between the characteristics of the log data and the normal behavior model.

[0189] In the case of unsupervised learning algorithms, the normal behavior model calculates the distance or reconstruction error between the input data and the normal pattern, and those exceeding a certain threshold are considered abnormal.

[0190] An alarm generation and notification unit, used to generate abnormal alarm information when the analysis result shows that the log data is an abnormal log, and send the abnormal alarm information to a preset operation and maintenance personnel;

[0191] In the specific implementation, when an abnormal log is detected, the system will generate abnormal alarm information according to the preset alarm rules. The abnormal alarm information may include the detailed content of the abnormal log, the abnormal type, the occurrence time, etc. The alarm information will be sent to the administrator or relevant operation and maintenance personnel through email, SMS, instant messaging tools, etc.

[0192] The exception processing and feedback unit is used to process the exception alarm information and feedback the exception processing results.

[0193] In the specific implementation, after receiving the alarm information, the administrator or operation and maintenance personnel will further analyze and process the anomaly. If it is confirmed to be a device failure or security threat, appropriate measures can be taken to repair or respond. At the same time, the processing results can be fed back to the system so that the system can continuously optimize and improve the anomaly detection algorithm.

[0194] In one example, suppose an unsupervised learning algorithm, Autoencoder, is used to detect log anomalies in IoT communication devices.

[0195] First, convert the log data into a numerical vector suitable for machine learning model processing. You can use methods such as word embedding or TF-IDF to convert text logs into numerical vectors.

[0196] The autoencoder is then trained using historical normal log data. The autoencoder learns how to encode the input data into a low-dimensional representation (the encoding process) and then decode the low-dimensional representation into the original data (the decoding process). During training, the model adjusts its parameters to minimize the difference between the decoded data and the original data.

[0197] Next, the newly collected log data is converted into a numerical vector and input into the trained autoencoder. The autoencoder will try to decode the input data into the original data and calculate the difference between the decoded data and the original data (i.e., the reconstruction error). If the reconstruction error exceeds the preset threshold, the log data is considered abnormal.

[0198] For detected abnormal logs, the system generates alarm information and notifies the administrator. The administrator further analyzes the abnormality to determine whether it is a device failure or a security threat, and takes appropriate measures. The processing results are fed back to the system so that the system can continuously optimize and improve the abnormality detection algorithm.

[0199] In the embodiment of the present invention, the data analysis and optimization module includes: a data collection and preprocessing submodule, a time series modeling submodule, a model verification and optimization submodule, a trend prediction submodule, and an optimization submodule;

[0200] The data collection and preprocessing submodule is used to collect historical performance index data of the communication equipment; and preprocess the historical performance index data to obtain preprocessed performance index data;

[0201] In the specific implementation, historical performance indicator data can be collected from IoT communication devices, such as CPU usage, memory occupancy, network bandwidth, etc. The collected data is then preprocessed, including data cleaning (removing outliers, missing values, etc.), data conversion (standardization, normalization, etc.), and feature selection to ensure the quality and applicability of the data.

[0202] A time series modeling submodule is used to build a time series model using preprocessed performance indicator data;

[0203] In the specific implementation, a time series model can be established based on the preprocessed data. The time series model is used to describe the law of performance indicators changing over time. Commonly used time series models can include autoregressive model (AR), moving average model (MA), autoregressive moving average model (ARMA), autoregressive integrated moving average model (ARIMA), etc.

[0204] In practical applications, we can select a suitable time series model based on the characteristics of the data and use historical data to train the model.

[0205] The model verification and optimization submodule is used to verify the time series model and optimize the time series model according to the verification results to obtain the optimized time series model;

[0206] In the specific implementation, a part of historical data can be used as a validation set to validate the trained model and evaluate the model's prediction performance. Then, based on the validation results, the time series model can be adjusted and optimized to improve the accuracy of the prediction.

[0207] Commonly used evaluation indicators include mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), etc.

[0208] The trend prediction submodule is used to input the equipment operation data into the optimized time series model to obtain the performance indicator trend prediction results;

[0209] In the specific implementation, the trained time series model can be used to predict future performance indicators.

[0210] The optimization submodule is used to optimize the configuration template according to the performance indicator trend prediction results.

[0211] In specific implementations, based on the prediction results, we can understand the future trends of device performance, including whether performance bottlenecks may occur and whether capacity expansion is needed.

[0212] Furthermore, in the embodiment of the present invention, the prediction results can also be visualized in the form of charts, so that the administrator can intuitively understand the changing trend of device performance. Based on the prediction results, the administrator can formulate corresponding operation and maintenance strategies, such as carrying out equipment maintenance and expansion plans in advance, to ensure the stable operation of IoT communication devices.

[0213] In an example, suppose you want to predict the CPU usage trend in IoT communication devices. The specific process is as follows:

[0214] Data Collection:

[0215] Collect CPU usage data from devices every hour for the past year.

[0216] Data preprocessing:

[0217] Remove outliers and missing values ​​from the data.

[0218] Arrange the data in chronological order to form time series data.

[0219] Model selection:

[0220] Through preliminary analysis of the data, it is found that the CPU usage has seasonality and trend, so the ARIMA model is selected for modeling.

[0221] Model training:

[0222] The ARIMA model is used to train the historical CPU usage data, and the prediction performance of the model is optimized by adjusting the model parameters (such as p, d, q, etc.).

[0223] Trend prediction:

[0224] Use the trained ARIMA model to predict the CPU usage for the next week.

[0225] Result visualization:

[0226] The prediction results are visualized in the form of a line graph, so that administrators can intuitively see the future trend of CPU usage.

[0227] Decision support:

[0228] Based on the prediction results, if the CPU usage is likely to exceed the threshold in the future, the administrator can expand or optimize the device in advance to ensure stable operation of the device.

[0229] Furthermore, in the embodiment of the present invention, an association rule mining algorithm (such as Apriori algorithm) can also be used to analyze the association relationship between different configuration items, which can provide decision support for configuration optimization. The following is a specific process of analyzing the association relationship between configuration items using the association rule mining algorithm:

[0230] Data preparation:

[0231] Collect historical configuration data and related performance indicator data of IoT communication devices.

[0232] Clean data, remove redundant and erroneous information, and ensure data quality.

[0233] Treat configuration items (such as IP addresses, port numbers, protocol types, etc.) as transaction items and each configuration change as a transaction.

[0234] Data conversion:

[0235] Convert configuration item data into a format suitable for association rule mining, usually Boolean data (for example, whether a configuration item is used).

[0236] Build a transaction database where each transaction contains a set of configuration items and their corresponding status (used / unused).

[0237] Calculate the support of the itemset:

[0238] Traverse the transaction database and count the number of occurrences of each configuration item (item), as well as the number of occurrences of item sets (combinations of configuration items).

[0239] Calculate the support of the item set, that is, the frequency of the item set appearing in the transaction database.

[0240] Generate frequent itemsets:

[0241] According to the preset minimum support threshold, frequent itemsets are filtered out.

[0242] Using the candidate item set generation and pruning steps of the Apriori algorithm, starting from a single item, gradually generate longer item sets and prune those item sets whose support is lower than the threshold.

[0243] Compute association rules:

[0244] For each frequent itemset, generate all possible association rules.

[0245] The association rule is in the form of {X}->{Y}, where X and Y are non-empty subsets of the item set, and the union of X and Y is equal to the frequent item set.

[0246] Calculate the confidence of the association rule, that is, the proportion of transactions containing X that also contain Y.

[0247] Select strong association rules:

[0248] According to the preset minimum confidence threshold, strong association rules are screened out.

[0249] Strong association rules are those rules with confidence levels above a threshold, which indicate strong associations between configuration items.

[0250] Interpretation and application of results:

[0251] Explain the filtered strong association rules to understand the dependencies and associations between configuration items.

[0252] Based on association rules, decision support can be provided for configuration optimization, for example:

[0253] If the rules indicate that changes to a certain configuration item (such as a port number) are often associated with performance improvements, then this configuration item can be prioritized for optimization.

[0254] If the rules reveal conflicts or redundancies between configuration items, the configuration template can be adjusted accordingly to reduce unnecessary configurations or improve configuration compatibility.

[0255] In an example, suppose you have the following transaction database (where 1 indicates that the configuration item is used and 0 indicates that it is not used):

[0256]

[0257] After association rule mining, the following strong association rules may be obtained:

[0258]

[0259] These rules indicate that when IP address 1 and port 80 are used together, the HTTP protocol is often used, and when port 443 is used, the HTTPS protocol is always used. Based on these rules, the system can automatically recommend or set relevant configuration items during configuration to improve the consistency and accuracy of configuration.

[0260] In the embodiment of the present invention, the specific implementation process of the security management and policy control module is as follows:

[0261] Use identity authentication and access control mechanisms to ensure that only authorized users can access devices and management systems. For example, use role-based access control (RBAC) algorithms to implement fine-grained management of user permissions.

[0262] Use encryption technology to encrypt the communication data between devices to prevent data leakage. For example, use encryption algorithms such as AES and RSA to encrypt and decrypt communication data.

[0263] Formulate security strategies and monitor the security status of devices in real time to promptly detect and handle security threats. Regularly evaluate and adjust security strategies; at the same time, strengthen security monitoring and alarm mechanisms to ensure that security threats are detected and handled in a timely manner.

[0264] By scanning the network and using multiple communication protocols, the system can automatically discover the Internet of Things communication equipment and identify its basic information, realize the comprehensive access of the equipment, and provide a basis for subsequent management and configuration work. The present invention also greatly improves the efficiency of configuration management by designing configuration templates and realizing automatic distribution and verification of configuration. The configuration is dynamically generated by the template engine and distributed to the equipment through the standard protocol, which ensures the consistency and accuracy of the configuration and reduces the errors and time cost of manual operation. The present invention also monitors the device status in real time, collects and analyzes log data, promptly discovers the abnormal situation of the device, and notifies the management personnel through the alarm mechanism. This helps to quickly respond to and handle device failures and ensure the stable operation of the Internet of Things system. The present invention also provides decision support for configuration optimization through in-depth analysis of device operation data. Using algorithms such as time series analysis and association rule mining, the performance trend of the device is predicted, and the correlation between configuration items is discovered, so as to put forward reasonable optimization suggestions and improve the operation efficiency and performance of the device. The present invention also strictly controls device access and data by formulating security policies. Technical means such as identity authentication, access control, and data encryption are adopted to ensure that only authorized users can access the device and management system, effectively preventing data leakage and security threats.

[0265] See also Figure 2 , Figure 2 A flowchart of the steps of a comprehensive management method for Internet of Things communication equipment provided by an embodiment of the present invention.

[0266] The embodiment of the present invention provides a method for comprehensive management of Internet of Things communication devices, including:

[0267] Step 201, scanning communication devices in the Internet of Things, and identifying the device type, device model and basic information of the communication devices;

[0268] Step 202, generating a configuration template using the device type, device model and basic information, sending the configuration template to the corresponding communication device, and verifying whether the configuration is successful;

[0269] Step 203, monitoring the performance indicator data of the communication device, analyzing the log data of the communication device to obtain analysis results, and generating alarm information according to the performance indicator data and the analysis results;

[0270] Step 204, obtaining device operation data of the communication device, and optimizing the configuration template according to the device operation data;

[0271] Step 205 formulates a security policy to perform security control on the communication equipment.

[0272] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0273] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0274] It will be appreciated by those skilled in the art that the embodiments of the present invention may be provided as methods, devices, or computer program products. Therefore, the embodiments of the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the embodiments of the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0275] The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0276] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0277] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device so that a series of operating steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable terminal device to implement the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0278] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present invention.

[0279] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or terminal device including the elements.

[0280] 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. An integrated management system for Internet of Things communication equipment, characterized in that: include: Device discovery and access module, configuration management and automated deployment module, monitoring alarm and log analysis module, data analysis and optimization module, security management and policy control module; The device discovery and access module is used to scan the communication devices in the Internet of Things and identify the device type, device model and basic information of the communication devices; The configuration management and automatic deployment module is used to generate a configuration template using the device type, the device model and the basic information, send the configuration template to the corresponding communication device, and verify whether the configuration is successful; The monitoring alarm and log analysis module is used to monitor the performance indicator data of the communication device, analyze the log data of the communication device to obtain analysis results, and generate alarm information according to the performance indicator data and the analysis results; The data analysis and optimization module is used to obtain the device operation data of the communication device and optimize the configuration template according to the device operation data; The security management and policy control module is used to formulate security policies and perform security control on the communication equipment.

2. The IoT communication equipment integrated management system according to claim 1, characterized in that: The device discovery and access module includes: a network scanning submodule, a device identification submodule, an API interface calling submodule, a device information integration submodule, a device access submodule, and a verification and feedback submodule; The network scanning submodule is used to scan the Internet of Things according to preset configuration parameters to obtain active devices; The device identification submodule is used to obtain the device type, device model and basic information of the communication device supporting the preset protocol through the preset protocol; The API interface calling submodule is used to obtain the device type, device model and basic information of the communication device through the API interface; The device information integration submodule is used to integrate the device type, device model and basic information of each communication device to obtain integrated information; The device access submodule is used to generate an access script according to the integration information and configuration requirements; The verification and feedback submodule is used to collect feedback information of the communication device based on the access script, and verify whether the communication device has successfully accessed through the feedback information.

3. The integrated management system for Internet of Things communication equipment according to claim 1, characterized in that: The configuration management and automated deployment module includes: a configuration template requirement determination submodule, a configuration template design submodule, a template engine submodule, a template engine code writing submodule, and a distribution and verification submodule; The configuration template requirement determination submodule is used to determine the configuration template requirement; The configuration template design submodule is used to create a configuration template file using the device type, the device model, the basic information and the configuration template requirement; The template engine submodule is used to define dynamic variables and write conditional logic; The template engine code writing submodule is used to render and generate a configuration template according to the dynamic variables, the conditional logic and the configuration template file; The sending and verifying submodule is used to send the configuration template to the corresponding communication device and verify whether the configuration is successful.

4. The integrated management system for Internet of Things communication equipment according to claim 3 is characterized in that: The template engine submodule includes a variable definition unit and a conditional logic writing unit; The variable definition unit is used to define dynamic variables of the configuration template; The conditional logic writing unit is used to write the conditional logic of the configuration template.

5. The integrated management system for Internet of Things communication equipment according to claim 3 is characterized in that: The issuing and verification submodule includes: an issuing protocol selection unit, an issuing configuration unit, a configuration verification unit, and a result collection and processing unit; The sending protocol selection unit is used to select a sending protocol according to the support status of the communication device; The configuration sending unit is used to send the configuration template to the communication device through the sending protocol; The configuration verification unit is used to perform application verification on the configuration template and generate a verification result; The result collection and processing unit is used to collect the verification result and trigger an operation corresponding to the verification result.

6. The integrated management system for Internet of Things communication equipment according to claim 1, characterized in that: The monitoring alarm and log analysis module includes: a monitoring alarm submodule and a log analysis submodule; The monitoring alarm submodule is used to monitor the performance indicator data of the communication device and trigger corresponding monitoring alarm information according to the performance indicator data; The log analysis submodule is used to perform abnormal analysis on the log of the communication device, obtain analysis results, and generate corresponding abnormal alarm information according to the analysis results.

7. The integrated management system for Internet of Things communication equipment according to claim 6, characterized in that: The monitoring alarm submodule includes: an alarm rule definition submodule, a monitoring data collection submodule, a data preprocessing submodule, a rule matching submodule, an alarm triggering submodule, and an alarm processing submodule; The alarm rule definition submodule is used to generate an alarm rule corresponding to the communication device; The monitoring data collection submodule is used to collect performance indicator data of the communication device; The data preprocessing submodule is used to perform data preprocessing on the performance indicator data to obtain preprocessed data; The rule matching submodule is used to match the pre-processed data with the alarm rule to obtain a matching result; The alarm triggering submodule is used to trigger monitoring alarm information when the matching result meets the preset alarm condition; The alarm processing submodule is used to adopt corresponding processing measures according to the alarm information.

8. The integrated management system for Internet of Things communication equipment according to claim 6, characterized in that: The log analysis submodule includes: a log data collection and preprocessing unit, a normal behavior model building unit, an anomaly detection unit, an alarm generation and notification unit, and an anomaly processing and feedback unit; The log data collection and preprocessing unit is used to collect the log data of the communication device and preprocess the log data to obtain preprocessed log data; The normal behavior model building unit is used to build a normal behavior model of the communication device using historical log data; The anomaly detection unit is used to input the pre-processed log data into the normal behavior model, perform anomaly detection, and obtain an analysis result; The alarm generation and notification unit is used to generate abnormal alarm information when the analysis result shows that the log data is an abnormal log, and send the abnormal alarm information to a preset operation and maintenance personnel; The exception processing and feedback unit is used to process the exception alarm information and feed back the exception processing result.

9. The Internet of Things communication equipment integrated management system according to claim 1, characterized in that: The data analysis and optimization module includes: a data collection and preprocessing submodule, a time series modeling submodule, a model verification and optimization submodule, a trend prediction submodule, and an optimization submodule; The data collection and preprocessing submodule is used to collect historical performance indicator data of the communication device; and preprocess the historical performance indicator data to obtain preprocessed performance indicator data; The time series modeling submodule is used to establish a time series model using the preprocessing performance indicator data; The model verification and optimization submodule is used to verify the time series model and optimize the time series model according to the verification result to obtain an optimized time series model; The trend prediction submodule is used to input the equipment operation data into the optimized time series model to obtain performance indicator trend prediction results; The optimization submodule is used to optimize the configuration template according to the performance indicator trend prediction result.

10. A comprehensive management method for Internet of Things communication equipment, characterized in that: include: Scan the communication devices in the Internet of Things, and identify the device type, device model and basic information of the communication devices; Generate a configuration template using the device type, the device model and the basic information, send the configuration template to the corresponding communication device, and verify whether the configuration is successful; Monitoring performance indicator data of the communication device, analyzing log data of the communication device to obtain analysis results, and generating alarm information according to the performance indicator data and the analysis results; Acquiring device operation data of the communication device, and optimizing the configuration template according to the device operation data; Formulate security policies and perform security control on the communication equipment.

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