Terminal access and data interaction monitoring method and system of electric power internet of things platform

Abstract

The present application relates to the field of electric power internet of things, and in particular to a terminal access and data interaction monitoring method and system of an electric power internet of things platform, which determines trusted nodes according to the operation status of the electric power internet of things platform, and distributes authentication plug-ins according to the data processing features of the trusted nodes; generates features of local data of a terminal to generate an access request, thereby ensuring multi-modal access authentication of the terminal and the platform; matches the access request and the authentication plug-ins, so that the terminal accesses the corresponding trusted nodes, listens to the data interaction dynamic features between the terminal and the trusted nodes, predicts abnormal events of data interaction, and accurately determines abnormal conditions of data caused by the terminal; according to the data processing configuration state of the trusted nodes during the occurrence of the abnormal events of data interaction, adjusts the interaction data correlation work processes of at least one of the terminal and the trusted nodes, reduces the interaction data redundancy between the terminal and the platform, and improves the stability and reliability of the electric power internet of things platform.

Description

Technical Field

[0001] This invention relates to the field of the Internet of Things (IoT) for power, and particularly to a method and system for monitoring terminal access and data interaction on a power IoT platform. Background Technology

[0002] A power IoT platform is formed by combining power systems with network IoT technology. It establishes a securely accessible IoT platform for the power system, enabling real-time and accurate monitoring and control. Power IoT platforms typically employ a cloud-edge-device three-way structure for power system operation control. The cloud and edge nodes, as the core fixed components of the power IoT platform, provide the resources for the entire platform's operation and facilitate task distribution and retrieval from the cloud to the edge nodes. The terminals (such as sensor terminals), as flexible components of the power IoT platform, need to be deployed and connected according to the actual operating conditions of the power system to ensure accurate and comprehensive analysis of the monitoring range corresponding to the terminals, based on the resources provided by the power IoT platform. Currently, terminals connect to the power IoT platform in a fixed mode and interact with data based on their actual monitoring status. This method can maintain the overall normal operation of the platform when its computing power, memory, and bandwidth resources are sufficient. However, if the power IoT platform's resources are insufficient, redundant data interaction between terminals and the platform can cause platform response delays and operational irregularities, reducing the stability and reliability of the power IoT platform. Therefore, how to regulate the interaction between terminals and the power IoT platform is of great significance for maintaining the platform's normal and efficient operation. Summary of the Invention

[0003] Considering that the interaction between terminals connected to the power IoT platform and the platform itself affects the platform's operation, especially when platform resources are insufficient, and that anomalies in nodes connecting to terminals within the platform can cause widespread paralysis, leading to platform malfunction and frequent failures, this invention addresses these issues by providing a terminal access and data interaction monitoring method for a power IoT platform that overcomes or at least partially solves these problems. The method includes:

[0004] Step S1: Obtain the real-time operation status of the power IoT platform to identify several trusted nodes within the power IoT platform; assign authentication plugins to the trusted nodes based on their data processing characteristics.

[0005] Step S2: Determine the local data generation characteristics of the terminal based on the terminal's local logs; generate an access request based on the local data generation characteristics; wherein the access request includes the terminal's multimodal certificate;

[0006] Step S3: Based on the matching relationship between the access request and the authentication plugins of all trusted nodes, connect the terminal to the corresponding trusted node; monitor the dynamic characteristics of data interaction between the terminal and the connected trusted node, and predict abnormal data interaction events;

[0007] Step S4: Obtain the data processing configuration status of the accessed trusted node during the abnormal data interaction event, and adjust the interaction data association process of at least one of the terminal and the accessed trusted node according to the data processing configuration status.

[0008] Optionally, in step S1, the real-time operation status of the power IoT platform is obtained to determine several trusted nodes within the power IoT platform; based on the data processing characteristics of the trusted nodes, authentication plugins are assigned to the trusted nodes, including:

[0009] The system acquires local task status information from the cloud within the power IoT platform and resource allocation information for each edge node. The local task generation status information includes the attribute information of the computational tasks generated locally in the cloud and the assignment information for the computational tasks distributed to all edge nodes. The resource allocation information includes the computing power and memory resources that each edge node is allowed to access.

[0010] Based on the local task status information and the resource allocation information, estimate the computing task load change trend of each edge node; based on the computing task load change trend, edge nodes that remain within the preset computing task load range are identified as trusted nodes;

[0011] The program configuration status within the trusted node is obtained to determine the processing rate and accuracy of the trusted node for several types of data; wherein, the program configuration status includes the configured program type and program bug status;

[0012] Based on the processing speed and the processing accuracy, an authentication plugin is assigned to the trusted node; wherein, the authentication plugin is an identification plugin for a specified type of data.

[0013] Optionally, in step S2, the local data generation characteristics of the terminal are determined based on the terminal's local logs; an access request is generated based on the local data generation characteristics; wherein, the access request includes the terminal's multimodal certificate, including:

[0014] Extract monitoring command response and execution records from the terminal's local logs. Based on the monitoring command response and execution records, determine the local generation port of the terminal that meets the preset data generation conditions. The preset data generation conditions include monitoring command response delay sub-conditions and monitoring command execution error sub-conditions. Based on the address of the generation port on the terminal, determine the local data generation type and local data generation traffic of the generation port.

[0015] Based on the local data generation type and the local data generation traffic, a data type modal certificate and a data traffic modal certificate are generated, and the data type modal certificate and the data traffic modal certificate are packaged to generate an access request.

[0016] Optionally, in step S3, based on the matching relationship between the access request and the authentication plugins of all trusted nodes, the terminal is connected to the corresponding trusted node; the dynamic characteristics of data interaction between the terminal and the connected trusted node are monitored, and abnormal data interaction events are predicted, including:

[0017] The data type modal certificate and data traffic modal certificate of the access request are uploaded to the authentication plugin of each trusted node for parsing, so as to obtain the matching and processing efficiency of each trusted node for the access request, thereby connecting the terminal to the trusted node with the highest matching and processing efficiency.

[0018] Monitor the dynamic characteristics of uplink and downlink data interaction traffic between the terminal and the accessed trusted node; predict abnormal data interaction events based on the response sequence time layout between the terminal and the accessed trusted node and the dynamic characteristics of uplink and downlink data interaction traffic; wherein, the abnormal data interaction events include abnormal data interaction traffic events.

[0019] Optionally, in step S4, the data processing configuration status of the accessed trusted node during the abnormal data interaction event is obtained, and the interaction data association process of at least one of the terminal and the accessed trusted node is adjusted according to the data processing configuration status, including:

[0020] Obtain the data compression status and data transfer and storage status of the accessed trusted node during the period when the abnormal data interaction event occurs;

[0021] Based on the data compression status and the data transfer and storage status, determine the retention time of data from the terminal on the access trusted node; based on the retention time and the data processing load of the power IoT platform, change the execution progress of the interaction data association process of at least one of the terminal and the access trusted node.

[0022] As one aspect of the present invention, embodiments of the present invention also provide a terminal access and data interaction monitoring system for a power IoT platform, including:

[0023] The node identification module is used to obtain the real-time operation status of the power IoT platform, thereby identifying several trusted nodes within the power IoT platform.

[0024] The plugin setting module is used to assign authentication plugins to the trusted nodes based on their data processing characteristics.

[0025] An access request generation module is used to determine the local data generation characteristics of the terminal based on the terminal's local logs; and to generate an access request based on the local data generation characteristics; wherein the access request includes the terminal's multimodal certificate;

[0026] The access processing module is used to connect the terminal to the corresponding trusted node based on the matching relationship between the access request and the authentication plugins of all trusted nodes.

[0027] The event prediction module is used to monitor the dynamic characteristics of data interaction between the terminal and the access trusted node, and predict abnormal data interaction events.

[0028] The workflow adjustment module is used to obtain the data processing configuration status of the accessed trusted node during the occurrence of the abnormal data interaction event, and adjust the interaction data association workflow of at least one of the terminal and the accessed trusted node according to the data processing configuration status.

[0029] Optionally, the node identification module is used to obtain the real-time operation status of the power IoT platform, thereby identifying several trusted nodes within the power IoT platform, including:

[0030] The system acquires local task status information from the cloud within the power IoT platform and resource allocation information for each edge node. The local task generation status information includes the attribute information of the computational tasks generated locally in the cloud and the assignment information for the computational tasks distributed to all edge nodes. The resource allocation information includes the computing power and memory resources that each edge node is allowed to access.

[0031] Based on the local task status information and the resource allocation information, estimate the computing task load change trend of each edge node; based on the computing task load change trend, edge nodes that remain within the preset computing task load range are identified as trusted nodes;

[0032] The plugin setting module is used to assign authentication plugins to the trusted node based on the data processing characteristics of the trusted node, including:

[0033] The program configuration status within the trusted node is obtained to determine the processing rate and accuracy of the trusted node for several types of data; wherein, the program configuration status includes the configured program type and program bug status;

[0034] Based on the processing speed and the processing accuracy, an authentication plugin is assigned to the trusted node; wherein, the authentication plugin is an identification plugin for a specified type of data.

[0035] Optionally, the access request generation module is used to determine the local data generation characteristics of the terminal based on the terminal's local logs; and to generate an access request based on the local data generation characteristics, including:

[0036] Extract monitoring command response and execution records from the terminal's local logs. Based on the monitoring command response and execution records, determine the local generation port of the terminal that meets the preset data generation conditions. The preset data generation conditions include monitoring command response delay sub-conditions and monitoring command execution error sub-conditions. Based on the address of the generation port on the terminal, determine the local data generation type and local data generation traffic of the generation port.

[0037] Based on the local data generation type and the local data generation traffic, a data type modal certificate and a data traffic modal certificate are generated, and the data type modal certificate and the data traffic modal certificate are packaged to generate an access request.

[0038] Optionally, the access processing module is used to connect the terminal to the corresponding trusted node based on the matching relationship between the access request and the authentication plugins of all trusted nodes, including:

[0039] The data type modal certificate and data traffic modal certificate of the access request are uploaded to the authentication plugin of each trusted node for parsing, so as to obtain the matching and processing efficiency of each trusted node for the access request, thereby connecting the terminal to the trusted node with the highest matching and processing efficiency.

[0040] The event prediction module is used to monitor the dynamic characteristics of data interaction between the terminal and the access trusted node, and to predict abnormal data interaction events, including:

[0041] Monitor the dynamic characteristics of uplink and downlink data interaction traffic between the terminal and the accessed trusted node; predict abnormal data interaction events based on the response sequence time layout between the terminal and the accessed trusted node and the dynamic characteristics of uplink and downlink data interaction traffic; wherein, the abnormal data interaction events include abnormal data interaction traffic events.

[0042] Optionally, the workflow adjustment module is used to obtain the data processing configuration status of the accessed trusted node during the abnormal data interaction event, and adjust the interaction data association workflow of at least one of the terminal and the accessed trusted node according to the data processing configuration status, including:

[0043] Obtain the data compression status and data transfer and storage status of the accessed trusted node during the period when the abnormal data interaction event occurs;

[0044] Based on the data compression status and the data transfer and storage status, determine the retention time of data from the terminal on the access trusted node; based on the retention time and the data processing load of the power IoT platform, change the execution progress of the interaction data association process of at least one of the terminal and the access trusted node.

[0045] The beneficial effects of the above-mentioned technical solutions provided in the embodiments of the present invention include at least the following:

[0046] This invention provides a method and system for monitoring terminal access and data interaction on a power IoT platform. The system determines trusted nodes based on the platform's operational status and allocates authentication plugins according to the trusted nodes' data processing characteristics. It acquires the terminal's local data generation characteristics to generate access requests, ensuring multimodal access authentication between the terminal and the platform. The system matches access requests with authentication plugins to enable the terminal to access the corresponding trusted node, monitors the dynamic characteristics of data interaction between the terminal and the trusted node, predicts abnormal data interaction events, and accurately identifies data anomalies caused by the terminal. Based on the trusted node's data processing configuration status during abnormal data interaction events, the system adjusts the data association process of at least one of the terminal and the trusted node. By performing identification and authentication, anomaly prediction, and process adjustment at the terminal access platform and terminal-node interaction levels, the system can promptly and accurately control the occurrence and spread of anomalies on the terminal side, reducing data redundancy between the terminal and the platform and improving the stability and reliability of the power IoT platform.

[0047] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description and the accompanying drawings.

[0048] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0049] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0050] Figure 1 This is a flowchart illustrating the terminal access and data interaction monitoring method of the power IoT platform provided in this embodiment of the invention.

[0051] Figure 2 This is a schematic diagram of the terminal access and data interaction monitoring system of the power IoT platform provided in this embodiment of the invention. Detailed Implementation

[0052] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0053] Please see Figure 1 As shown, an embodiment of this application provides a method for monitoring terminal access and data interaction of a power IoT platform. This method includes:

[0054] Step S1: Obtain the real-time operation status of the power IoT platform to identify several trusted nodes within the platform; assign authentication plugins to trusted nodes based on their data processing characteristics.

[0055] Step S2: Determine the local data generation characteristics of the terminal based on the terminal's local logs; generate an access request based on the local data generation characteristics; wherein, the access request includes the terminal's multimodal certificate;

[0056] Step S3: Based on the matching relationship between the access request and the authentication plugins of all trusted nodes, connect the terminal to the corresponding trusted node; monitor the dynamic characteristics of data interaction between the terminal and the connected trusted node, and predict abnormal data interaction events.

[0057] Step S4: Obtain the data processing configuration status of the trusted node that was accessed during the abnormal data interaction event, and adjust the interaction data association process of at least one of the terminal and the accessed trusted node according to the data processing configuration status.

[0058] The terminal access and data interaction monitoring method of this power IoT platform identifies and authenticates, predicts anomalies, and adjusts the working process at the terminal access platform and the terminal-node interaction level. It controls the occurrence and spread of anomalies in a timely and accurate manner on the terminal side, reduces the redundancy of interactive data between the terminal and the platform, and improves the stability and reliability of the power IoT platform.

[0059] In another embodiment, in step S1, the real-time operation status of the power IoT platform is acquired to determine several trusted nodes within the power IoT platform; based on the data processing characteristics of the trusted nodes, authentication plugins are assigned to the trusted nodes, including:

[0060] Obtain local task status information from the cloud within the power IoT platform and resource allocation information for each edge node; the local task generation status information includes the attribute information of the computing tasks generated locally in the cloud and the information on the distribution and allocation of computing tasks to all edge nodes; the resource allocation information includes the computing power resources and memory resources that each edge node is allowed to access.

[0061] Based on local task status information and resource allocation information, estimate the trend of computing task load changes for each edge node; based on the trend of computing task load changes, edge nodes that remain within the preset computing task load range are identified as trusted nodes.

[0062] Obtain the program configuration status within the trusted node to determine the processing rate and accuracy of the trusted node for several types of data; the program configuration status includes the configured program type and program bug status.

[0063] Based on processing speed and accuracy, authentication plugins are assigned to trusted nodes; among them, authentication plugins are authentication plugins for a specific type of data.

[0064] The power IoT platform comprises a cloud, several edge nodes (i.e., edge devices), and several terminals (such as sensor terminals). The cloud provides cloud computing and cloud storage services to the platform. Edge nodes are distributed across different network nodes within the IoT ecosystem, enabling distributed computing on the platform. Terminals have sensing capabilities, used to monitor different power devices in the power system in real time and obtain their operational data. To monitor the power system promptly and accurately, terminals connect to corresponding edge nodes, uploading their detected power device operational data to the edge nodes. Simultaneously, edge nodes send control commands to the terminals to adjust their operating status / mode.

[0065] Considering that edge nodes typically handle tasks distributed from the cloud, consuming their own computing and memory resources while processing these tasks, the more tasks they receive, the busier they become, and the fewer available computing and memory resources they have. This leads to significant operational instability, potentially causing lag or crashes. To ensure that connected terminals have sufficient resources for smooth and stable interaction, the following steps are taken: First, the attribute information of the computing tasks generated locally in the cloud and the task distribution information for all edge nodes are obtained. The computing task attribute information refers to the data content type involved in the computing tasks generated locally in the cloud. The task distribution information refers to the list of computing tasks distributed by the cloud to each edge node, including the data volume and distribution time of each task. Finally, the allowed computing and memory resources for each edge node are obtained, which may include the inherent computing and memory resources configured within the edge node itself. By performing a time-domain comparative analysis of local task status and resource allocation information, the task load capacity of each edge node is determined after it utilizes its own resources to process the computational tasks when tasks are distributed from the cloud to the edge node within the same time interval. Then, the time-domain change trend of the edge node's own task load capacity is predicted across all time intervals to obtain the computational task load change trend of the edge node (i.e., the change in the edge node's computational task load capacity over time). Based on this computational task load change trend, edge nodes whose computational task load capacity remains within a preset range over a predetermined future time period are identified as trusted nodes. This means that trusted nodes can maintain a stable and controllable computational task load capacity over the predetermined future time period, and will not experience excessively high computational task loads.

[0066] Furthermore, the edge nodes within the power IoT platform exhibit cluster specificity. This means the platform comprises several edge node clusters, with all edge nodes within the same cluster sharing identical hardware and software configurations. However, edge nodes in different clusters possess varying hardware and software configurations. Consequently, the program types and bug states (e.g., bug types and their locations) of edge nodes across different clusters differ. This results in varying processing rates (i.e., the amount of data processed per unit time) and accuracy rates for different data types from different edge nodes (different trusted nodes). To address this, the most suitable data type for each trusted node is determined based on its processing rate and accuracy for several data types. Then, an authentication plugin is assigned to each trusted node based on this most suitable data type, ensuring that each trusted node's authentication plugin can only authenticate a single data type. This guarantees that each trusted node can only connect to terminals that generate the specified data type, improving the uniqueness of connections between trusted nodes and terminals.

[0067] In another embodiment, in step S2, the local data generation characteristics of the terminal are determined based on the terminal's local logs; an access request is generated based on the local data generation characteristics; wherein the access request includes the terminal's multimodal certificate, including:

[0068] Extract monitoring command response and execution records from the terminal's local logs. Based on these records, determine the local data generation port on the terminal that meets the preset data generation conditions. These preset conditions include monitoring command response delay sub-conditions and monitoring command execution error sub-conditions. Determine the local data generation type and local data generation traffic of the generation port based on its address on the terminal.

[0069] Based on the local data generation type and local data generation traffic, generate data type modal certificates and data traffic modal certificates, and package the data type modal certificates and data traffic modal certificates to generate an access request.

[0070] Power systems contain diverse and complex types of electrical equipment. To achieve comprehensive and accurate monitoring, various types of terminals (sensor terminals) are deployed at different locations within the power system. These terminals exhibit varying operational states (response speed to monitoring commands and task execution status). To ensure accurate processing of the data generated during terminal monitoring, access requests need to be generated based on the data generated by the terminals. Specifically, monitoring command response and execution records are extracted from the terminal's local logs to determine the generation ports that meet the monitoring command response delay sub-condition and the monitoring command execution error sub-condition. The monitoring command response delay sub-condition refers to a response time less than a preset time threshold; the monitoring command execution error sub-condition refers to an error rate less than an error rate threshold. Based on the address of the aforementioned generation port on the terminal, the local data generation type (i.e., local data content type) and local data generation traffic (i.e., the amount of local data generated per unit time) of the aforementioned generation port are determined. Based on this, data type modal certificates and data traffic modal certificates are generated. The data type modal certificates and data traffic modal certificates are then packaged to generate an access request. In this way, the access request contains an electronic certificate that matches the data type and data traffic generated by the terminal itself, thereby achieving accurate identification of the attributes of the data generated by the terminal and providing a basis for selecting a trusted node suitable for the terminal to access.

[0071] In another embodiment, in step S3, based on the matching relationship between the access request and the authentication plugins of all trusted nodes, the terminal is connected to the corresponding trusted node; the dynamic characteristics of data interaction between the terminal and the connected trusted node are monitored, and abnormal data interaction events are predicted, including:

[0072] The data type modal certificate and data traffic modal certificate of the access request are uploaded to the authentication plugin of each trusted node for parsing, so as to obtain the matching and processing efficiency of each trusted node for the access request, and thus connect the terminal to the trusted node with the highest matching and processing efficiency.

[0073] Monitor the dynamic characteristics of uplink and downlink data interaction traffic between the monitoring terminal and the access trusted node; predict abnormal data interaction events based on the time layout of the response sequence between the terminal and the access trusted node and the dynamic characteristics of uplink and downlink data interaction traffic; among which, abnormal data interaction events include abnormal data interaction traffic events.

[0074] As described above, each trusted node is equipped with an authentication plugin, which is specifically designed for identifying a particular type of data. This means that if the data type modal certificate and data traffic modal certificate in the access request authenticated by the plugin match the specified data type, the plugin will generate an authentication pass response; otherwise, it will generate an authentication fail response. Specifically, the data type modal certificate and data traffic modal certificate of the access request are uploaded to the authentication plugin of each trusted node for parsing to determine all trusted nodes that generate authentication pass responses. Then, the matching and processing efficiency of each trusted node that generated the authentication pass response for the access request is determined (i.e., the authentication parsing speed of each trusted node for the data type modal certificate and data traffic modal certificate in the access request). This ensures that the terminal connects to the trusted node with the highest matching and processing efficiency, guaranteeing accurate and reliable connection processing after the terminal connects to the trusted node.

[0075] Furthermore, the system monitors the dynamic characteristics of uplink and downlink data interaction traffic between the monitoring terminal and the access trusted node. Considering that the terminal and the access trusted node will form a response sequence during the interaction process, the aforementioned response sequence temporal locality refers to the time distribution corresponding to the alternating responses between the terminal and the access trusted node during the interaction process. Based on the aforementioned response sequence temporal layout, the dynamic characteristics of the aforementioned uplink and downlink data interaction traffic are divided into corresponding response time intervals to obtain the uplink and downlink data traffic during the respective response actions of the terminal and the access trusted node during the interaction process. Then, based on the aforementioned division to obtain the respective uplink and downlink data traffic during the execution of all response actions, network model processing is performed to predict abnormal data interaction traffic events. The aforementioned abnormal data interaction traffic events refer to events where the increase in uplink or downlink data traffic exceeds a preset threshold within a unit of time, thereby providing a basis for subsequent adjustments to the status of the terminal and the access trusted node.

[0076] In another embodiment, step S4 involves obtaining the data processing configuration status of the trusted node accessed during the abnormal data interaction event, and adjusting the interaction data association process of at least one of the terminal and the accessed trusted node based on the data processing configuration status, including:

[0077] Obtain the data compression status and data transfer and storage status of trusted nodes accessed during abnormal data interaction events;

[0078] Based on the data compression status and data transfer and storage status, determine the retention time of data from the terminal in the access trusted node; based on the retention time and the data processing load of the power IoT platform, change the execution progress of the interactive data association process of at least one of the terminal and the access trusted node.

[0079] In practice, when a trusted node receives data from a terminal, it compresses and performs preliminary processing on the data before transferring it to the cloud. During this process, the received data remains within the trusted node. The longer this data remains within the trusted node, the more it affects the stability and reliability of the node's operation. If the terminal continues to upload data to or frequently interact with the trusted node while the data is still there, it increases the node's instability and unreliability. To maintain the normal operation of the power IoT platform, the data compression status (e.g., compression rate) and data transfer and storage status (e.g., data transfer rate) of the trusted node during abnormal data exchange events are analyzed to determine the retention time of data from the terminal within the connected trusted node. Based on the retention time and the data processing load of the power IoT platform, it is determined whether the retention time exceeds a preset time length or whether the data processing load of the power IoT platform exceeds a preset load threshold. If the retention time exceeds the preset time length, the execution progress of the terminal's interactive data association process is slowed down; if the data processing load of the power IoT platform exceeds the preset load threshold, the execution progress of the connected trusted node's interactive data association process is slowed down. If both the retention time and the data processing load of the power IoT platform exceed the preset load threshold, the execution progress of the terminal's and the connected trusted node's interactive data association process is slowed down, thereby reducing the data interaction burden between the terminal and the connected trusted node and improving the stability and reliability of the power IoT platform.

[0080] Please see Figure 2 As shown in this embodiment, a terminal access and data interaction monitoring system for a power IoT platform is provided. This power IoT platform terminal access and data interaction monitoring system includes:

[0081] The node identification module is used to obtain the real-time operation status of the power IoT platform, thereby identifying several trusted nodes within the power IoT platform.

[0082] The plugin configuration module is used to assign authentication plugins to trusted nodes based on their data processing characteristics.

[0083] The access request generation module is used to determine the local data generation characteristics of the terminal based on the terminal's local logs; and generate an access request based on the local data generation characteristics; wherein, the access request includes the terminal's multimodal certificate;

[0084] The access processing module is used to connect the terminal to the corresponding trusted node based on the matching relationship between the access request and the authentication plugins of all trusted nodes.

[0085] The event prediction module is used to monitor the dynamic characteristics of data interaction between the terminal and the access trusted node, and to predict abnormal data interaction events.

[0086] The workflow adjustment module is used to obtain the data processing configuration status of trusted nodes that have been accessed during abnormal data interaction events, and adjust the workflow of the interaction data association between the terminal and at least one of the trusted nodes based on the data processing configuration status.

[0087] The beneficial effects of the above embodiments are that the terminal access and data interaction monitoring system of the power IoT platform can identify and authenticate, predict anomalies, and adjust the working process at the terminal access platform and the terminal-node interaction level, so as to control the occurrence and spread of anomalies in a timely and accurate manner on the terminal side, reduce the redundancy of interactive data between the terminal and the platform, and improve the stability and reliability of the power IoT platform.

[0088] In another embodiment, the node identification module is used to obtain the real-time operating status of the power IoT platform, thereby identifying several trusted nodes within the power IoT platform, including:

[0089] Obtain local task status information from the cloud within the power IoT platform and resource allocation information for each edge node; the local task generation status information includes the attribute information of the computing tasks generated locally in the cloud and the information on the distribution and allocation of computing tasks to all edge nodes; the resource allocation information includes the computing power resources and memory resources that each edge node is allowed to access.

[0090] Based on local task status information and resource allocation information, estimate the trend of computing task load changes for each edge node; based on the trend of computing task load changes, edge nodes that remain within the preset computing task load range are identified as trusted nodes.

[0091] The plugin configuration module is used to assign authentication plugins to trusted nodes based on their data processing characteristics, including:

[0092] Obtain the program configuration status within the trusted node to determine the processing rate and accuracy of the trusted node for several types of data; the program configuration status includes the configured program type and program bug status.

[0093] Based on processing speed and accuracy, authentication plugins are assigned to trusted nodes; among them, authentication plugins are authentication plugins for a specific type of data.

[0094] In another embodiment, the access request generation module is used to determine the local data generation characteristics of the terminal based on the terminal's local logs; and to generate an access request based on the local data generation characteristics, including:

[0095] Extract monitoring command response and execution records from the terminal's local logs. Based on these records, determine the local data generation port on the terminal that meets the preset data generation conditions. These preset conditions include monitoring command response delay sub-conditions and monitoring command execution error sub-conditions. Determine the local data generation type and local data generation traffic of the generation port based on its address on the terminal.

[0096] Based on the local data generation type and local data generation traffic, generate data type modal certificates and data traffic modal certificates, and package the data type modal certificates and data traffic modal certificates to generate an access request.

[0097] In another embodiment, the access processing module is used to connect the terminal to the corresponding trusted node based on the matching relationship between the access request and the authentication plugins of all trusted nodes, including:

[0098] The data type modal certificate and data traffic modal certificate of the access request are uploaded to the authentication plugin of each trusted node for parsing, so as to obtain the matching and processing efficiency of each trusted node for the access request, and thus connect the terminal to the trusted node with the highest matching and processing efficiency.

[0099] The event prediction module is used to monitor the dynamic characteristics of data interaction between the terminal and the access trusted node, and to predict abnormal data interaction events, including:

[0100] Monitor the dynamic characteristics of uplink and downlink data interaction traffic between the monitoring terminal and the access trusted node; predict abnormal data interaction events based on the time layout of the response sequence between the terminal and the access trusted node and the dynamic characteristics of uplink and downlink data interaction traffic; among which, abnormal data interaction events include abnormal data interaction traffic events.

[0101] In another embodiment, the workflow adjustment module is used to obtain the data processing configuration status of the trusted node accessed during the abnormal data interaction event, and adjust the interaction data association workflow of at least one of the terminal and the accessed trusted node according to the data processing configuration status, including:

[0102] Obtain the data compression status and data transfer and storage status of trusted nodes accessed during abnormal data interaction events;

[0103] Based on the data compression status and data transfer and storage status, determine the retention time of data from the terminal in the access trusted node; based on the retention time and the data processing load of the power IoT platform, change the execution progress of the interactive data association process of at least one of the terminal and the access trusted node.

[0104] The operation and effect of the terminal access and data interaction monitoring system of the power IoT platform of the present invention are consistent with the terminal access and data interaction monitoring method of the power IoT platform described above. Therefore, the terminal access and data interaction monitoring system of the cloud power IoT platform will not be described again here.

[0105] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. This disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims. Thus, if these modifications and variations of the invention fall within the scope of the claims of the invention and their equivalents, the invention is also intended to include these modifications and variations.

Claims

1. A method for monitoring terminal access and data interaction in a power IoT platform, characterized in that, include: Step S1: Obtain the real-time operation status of the power IoT platform to determine several trusted nodes within the power IoT platform; Based on the data processing characteristics of the trusted node, an authentication plugin is assigned to the trusted node; Step S2: Determine the local data generation characteristics of the terminal based on the terminal's local logs; An access request is generated based on the local data generation characteristics; wherein the access request includes the terminal's multimodal certificate; Step S3: Based on the matching relationship between the access request and the authentication plugins of all trusted nodes, connect the terminal to the corresponding trusted node; monitor the dynamic characteristics of data interaction between the terminal and the connected trusted node, and predict abnormal data interaction events; Step S4: Obtain the data processing configuration status of the accessed trusted node during the abnormal data interaction event, and adjust the interaction data association process of at least one of the terminal and the accessed trusted node according to the data processing configuration status; In step S1, the real-time operation status of the power IoT platform is acquired to determine several trusted nodes within the power IoT platform; based on the data processing characteristics of the trusted nodes, authentication plugins are assigned to the trusted nodes, including: The system acquires local task status information from the cloud within the power IoT platform and resource allocation information for each edge node. The local task status information includes cloud-generated computation task attribute information and computation task distribution information for all edge nodes. The resource allocation information includes the computing power and memory resources that each edge node is allowed to access. Based on the local task status information and the resource allocation information, estimate the computing task load change trend of each edge node; based on the computing task load change trend, edge nodes that remain within the preset computing task load range are identified as trusted nodes; The program configuration status within the trusted node is obtained to determine the processing rate and accuracy of the trusted node for several types of data; wherein, the program configuration status includes the configured program type and program bug status; Based on the processing rate and the processing accuracy, an authentication plugin is assigned to the trusted node; wherein, the authentication plugin is an identification plugin for a specified type of data; In step S2, the local data generation characteristics of the terminal are determined based on the terminal's local logs; an access request is generated based on the local data generation characteristics; wherein, the access request includes the terminal's multimodal certificate, including: Extract monitoring command response and execution records from the terminal's local logs. Based on the monitoring command response and execution records, determine the local generation port of the terminal that meets the preset data generation conditions. The preset data generation conditions include monitoring command response delay sub-conditions and monitoring command execution error sub-conditions. Based on the address of the generation port on the terminal, determine the local data generation type and local data generation traffic of the generation port. Based on the local data generation type and the local data generation traffic, generate a data type modal certificate and a data traffic modal certificate, and package the data type modal certificate and the data traffic modal certificate to generate an access request; In step S4, the data processing configuration status of the accessed trusted node during the abnormal data interaction event is obtained, and the interaction data association process of at least one of the terminal and the accessed trusted node is adjusted according to the data processing configuration status, including: Obtain the data compression status and data transfer and storage status of the accessed trusted node during the abnormal data interaction event; Based on the data compression status and the data transfer and storage status, determine the retention time of data from the terminal on the access trusted node; based on the retention time and the data processing load of the power IoT platform, change the execution progress of the interaction data association process of at least one of the terminal and the access trusted node.

2. The terminal access and data interaction monitoring method for the power IoT platform as described in claim 1, characterized in that: In step S3, the terminal is connected to the corresponding trusted node according to the matching relationship between the access request and the authentication plugins of all trusted nodes; Monitoring the dynamic characteristics of data interaction between the terminal and the access trusted node to predict abnormal data interaction events includes: The data type modal certificate and data traffic modal certificate of the access request are uploaded to the authentication plugin of each trusted node for parsing, so as to obtain the matching and processing efficiency of each trusted node for the access request, thereby connecting the terminal to the trusted node with the highest matching and processing efficiency. Monitor the dynamic characteristics of uplink and downlink data interaction traffic between the terminal and the accessed trusted node; predict abnormal data interaction events based on the response sequence time layout between the terminal and the accessed trusted node and the dynamic characteristics of uplink and downlink data interaction traffic; wherein, the abnormal data interaction events include abnormal data interaction traffic events.

3. A terminal access and data interaction monitoring system for a power IoT platform, characterized in that, include: The node identification module is used to obtain the real-time operation status of the power IoT platform, thereby identifying several trusted nodes within the power IoT platform. The plugin setting module is used to assign authentication plugins to the trusted nodes based on their data processing characteristics. The access request generation module is used to determine the local data generation characteristics of the terminal based on the terminal's local logs. An access request is generated based on the local data generation characteristics; wherein the access request includes the terminal's multimodal certificate; The access processing module is used to connect the terminal to the corresponding trusted node based on the matching relationship between the access request and the authentication plugins of all trusted nodes. The event prediction module is used to monitor the dynamic characteristics of data interaction between the terminal and the access trusted node, and predict abnormal data interaction events. The workflow adjustment module is used to obtain the data processing configuration status of the accessed trusted node during the occurrence of the abnormal data interaction event, and adjust the interaction data association workflow of at least one of the terminal and the accessed trusted node according to the data processing configuration status. The node identification module is used to obtain the real-time operation status of the power IoT platform, thereby identifying several trusted nodes within the power IoT platform, including: The system acquires local task status information from the cloud within the power IoT platform and resource allocation information for each edge node. The local task status information includes cloud-generated computation task attribute information and computation task distribution information for all edge nodes. The resource allocation information includes the computing power and memory resources that each edge node is allowed to access. Based on the local task status information and the resource allocation information, estimate the computing task load change trend of each edge node; based on the computing task load change trend, edge nodes that remain within the preset computing task load range are identified as trusted nodes; The plugin setting module is used to assign authentication plugins to the trusted node based on the data processing characteristics of the trusted node, including: The program configuration status within the trusted node is obtained to determine the processing rate and accuracy of the trusted node for several types of data; wherein, the program configuration status includes the configured program type and program bug status; Based on the processing rate and the processing accuracy, an authentication plugin is assigned to the trusted node; wherein, the authentication plugin is an identification plugin for a specified type of data; The access request generation module is used to determine the local data generation characteristics of the terminal based on the terminal's local logs; and to generate an access request based on the local data generation characteristics, including: Extract monitoring command response and execution records from the terminal's local logs. Based on the monitoring command response and execution records, determine the local generation port of the terminal that meets the preset data generation conditions. The preset data generation conditions include monitoring command response delay sub-conditions and monitoring command execution error sub-conditions. Based on the address of the generation port on the terminal, determine the local data generation type and local data generation traffic of the generation port. Based on the local data generation type and the local data generation traffic, generate a data type modal certificate and a data traffic modal certificate, and package the data type modal certificate and the data traffic modal certificate to generate an access request; The workflow adjustment module is used to obtain the data processing configuration status of the accessed trusted node during the abnormal data interaction event, and adjust the interaction data association workflow of at least one of the terminal and the accessed trusted node according to the data processing configuration status, including: Obtain the data compression status and data transfer and storage status of the accessed trusted node during the abnormal data interaction event; Based on the data compression status and the data transfer and storage status, determine the retention time of data from the terminal on the access trusted node; based on the retention time and the data processing load of the power IoT platform, change the execution progress of the interaction data association process of at least one of the terminal and the access trusted node.

4. The terminal access and data interaction monitoring system of the power IoT platform as described in claim 3, characterized in that: The access processing module is used to connect the terminal to the corresponding trusted node based on the matching relationship between the access request and the authentication plugins of all trusted nodes, including: The data type modal certificate and data traffic modal certificate of the access request are uploaded to the authentication plugin of each trusted node for parsing, so as to obtain the matching and processing efficiency of each trusted node for the access request, thereby connecting the terminal to the trusted node with the highest matching and processing efficiency. The event prediction module is used to monitor the dynamic characteristics of data interaction between the terminal and the access trusted node, and to predict abnormal data interaction events, including: Monitor the dynamic characteristics of uplink and downlink data interaction traffic between the terminal and the accessed trusted node; predict abnormal data interaction events based on the response sequence time layout between the terminal and the accessed trusted node and the dynamic characteristics of uplink and downlink data interaction traffic; wherein, the abnormal data interaction events include abnormal data interaction traffic events.

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