An enterprise information data management and warning method and system

Abstract

The present invention relates to the field of data transmission, and particularly to an enterprise information data management and warning method and system. The method includes: determining the associated device categories according to whether the data to be uploaded by each associated device is in a sensitive state; determining the transmission adjustment method for the corresponding processing node according to the proportion of a certain type of device in each processing node; the transmission adjustment method includes performing transmission task scheduling for the processing node or performing data optimization on the data to be uploaded by each device of a certain type; determining the task scheduling method according to the distribution state of the devices of a certain type in the processing node, and the task scheduling method includes determining the target scheduling node according to the proportion of the aggregation area of each processing node or the number of similar devices; determining whether to perform preferred device screening according to whether there is a set of similar devices; and completing the transmission of the data to be uploaded according to the task scheduling result and the data optimization result. The present invention improves the security of device data during the transmission process.

Description

Technical Field

[0001] The present invention relates to the field of data transmission, and particularly to a method and system for managing and warning enterprise information data. Background Art

[0002] The photovoltaic data of power enterprises contains a large amount of sensitive information, such as equipment status, energy output, and equipment distribution. Information leakage during the transmission process will have a serious impact on the safety and stability of photovoltaic power stations. Data management and warning can ensure the security of data and thus protect the interests of enterprises. However, the existing data management and warning methods often fail to consider the targeted protection of equipment data leakage and equipment layout data. Therefore, how to ensure the confidentiality of equipment-related data of power enterprises is an urgent problem for those skilled in the art.

[0003] Chinese Patent Publication No. CN118157958A discloses a distributed photovoltaic data transmission system and method. The system includes: a terminal acquisition layer, a federated learning layer, and a blockchain network layer. The terminal acquisition layer is used to acquire distributed photovoltaic data; the blockchain network layer is used to receive a data transmission request sent by a data requester and verify whether the data transmission request is valid. When the request is valid, according to the data type and communication requirements of the data transmission request, retrieve the registration information and historical transmission and transaction information of each terminal node in the blockchain network, and select a federated learning pool in the federated learning layer from the relevant nodes according to the reputation and privacy level of each relevant node in the relevant node set, and send a data transmission request to the federated learning pool; the federated learning layer responds to the data transmission request and controls each federated node in the federated learning pool to send the distributed photovoltaic data to the data requester according to the transmission rules. The above solution has the following problems: it is impossible to determine a targeted transmission adjustment method according to the proportion of devices with sensitive information in the data to be uploaded in the actual working scenario, resulting in the data content of a single transmission being likely to disclose the layout of photovoltaic devices, and thus the security of equipment data during the transmission process is low. Summary of the Invention

[0004] Therefore, the present invention provides a method and system for managing and warning enterprise information data to overcome the problem in the prior art that it is impossible to determine a targeted transmission adjustment method according to the proportion of devices with sensitive information in the data to be uploaded in the actual working scenario, resulting in the data content of a single transmission being likely to disclose the layout of photovoltaic devices, and thus the security of equipment data during the transmission process is low.

[0005] To achieve the above object, the present invention provides a method for managing and warning enterprise information data, including:

[0006] Obtain the data to be uploaded of each associated device, and determine the category of the associated device according to whether the data to be uploaded of each associated device is in a sensitive state;

[0007] Determine the transmission adjustment method corresponding to the processing node according to the proportion of a certain type of device in each processing node, where the transmission adjustment method includes performing transmission task scheduling for the processing node or optimizing the data to be uploaded for each device of the certain type;

[0008] If transmission task scheduling is performed, determine the task scheduling method according to the distribution state of the devices of the certain type in the processing node, and the task scheduling method includes determining the target scheduling node according to the proportion of the aggregation area of each processing node or the number of similar devices;

[0009] If data optimization is performed, determine whether to perform preferred device screening according to whether there is a set of similar devices in each processing node;

[0010] Complete the transmission of the data to be uploaded according to the task scheduling result and the data optimization result.

[0011] Furthermore, periodically detect whether the data to be uploaded of each associated device of each processing node is in a sensitive state, and determine the category of the associated device according to whether the data to be uploaded of each associated device is in a sensitive state. If the data to be uploaded is in a sensitive state, mark the corresponding associated device as a device of the certain type.

[0012] Furthermore, the sensitive state is determined according to whether the data to be uploaded of the associated device contains location information and performance information;

[0013] If the data to be uploaded of the associated device contains location information or performance information, it is determined that the data to be uploaded of the associated device is in a sensitive state.

[0014] Furthermore, for a single processing node, if the proportion of the devices of the certain type in the processing node is greater than the preset proportion, it is determined to perform transmission task scheduling for the processing node, and determine the task scheduling method according to the distribution state of the devices of the certain type in the processing node;

[0015] The task scheduling method includes performing task scheduling for the data to be uploaded corresponding to the devices of the certain type in the aggregation area and determining whether to perform task scheduling for the data to be uploaded of the device of the certain type according to the performance similarity between the device of the certain type and the associated device in the corresponding processing node;

[0016] The distribution state is determined according to the number of devices of the certain type within the preset range of each device of the certain type, and the distribution state includes an aggregation state and a discrete state.

[0017] Furthermore, for a single device of the certain type, if the device of the certain type is in an aggregation state, perform task scheduling for the data to be uploaded corresponding to the devices of the certain type in the aggregation area where the device of the certain type is located, and determine several target scheduling nodes according to the proportion of the aggregation area of each processing node;

[0018] For any type of device that needs to perform task scheduling, determine the target scheduling node for the corresponding type of device according to the number of similar devices among the associated devices of each processing node;

[0019] The number of the target scheduling nodes has a positive correlation with the number of devices of a certain type within the aggregation area;

[0020] The aggregation area is a set of preset ranges of each device of a certain type with overlapping preset ranges, and the preset range of any device of a certain type within the set area intersects with the preset range of at least one device of a certain type.

[0021] Furthermore, for a single device of a certain type, if the device of a certain type is in a discrete state, determine whether to perform task scheduling on the data to be uploaded for the device of a certain type according to the performance similarity reference value of the device of a certain type within its corresponding processing node;

[0022] If the performance similarity reference value of the device of a certain type is greater than the preset performance similarity reference value, perform task scheduling on the data to be uploaded for the device of a certain type, and determine the target scheduling node for the device of a certain type according to the amount of data to be transmitted in the current cycle of each processing node.

[0023] Furthermore, for a single processing node, if the proportion of devices of a certain type in the processing node is less than or equal to the preset proportion, perform data optimization on the data to be uploaded for each device of a certain type, and determine whether to perform preferred device screening according to the existence of a set of similar devices;

[0024] The set of similar devices is determined according to the device interval distance and the performance similarity.

[0025] Furthermore, if there is a set of similar devices among the devices of a certain type in the processing node, determine the preferred devices with a preset preferred number according to the preferred transmission coefficients of each device of a certain type within the set of similar devices. During the current data transmission cycle, for the devices of a certain type within the set of similar devices, only transmit the data to be uploaded of the preferred devices;

[0026] The preferred transmission coefficient is determined according to the position difference reference value and the operating data change value.

[0027] Furthermore, for the data to be uploaded corresponding to the devices of a certain type other than the set of similar devices in each processing node, set the delay transmission time of the corresponding data to be uploaded according to the operating data change value of each device of a certain type;

[0028] The duration of the delay transmission time has a negative correlation with the operating data change value of each device of a certain type.

[0029] The present invention also provides an enterprise information data management warning system, including:

[0030] A data monitoring module, which is used to periodically detect whether the data to be uploaded of each associated device of each processing node is in a sensitive state, and determine the associated device category;

[0031] A transmission analysis module, which is connected to the data monitoring module, and is used to determine the transmission adjustment method of the corresponding processing node according to the proportion of a certain type of device in each processing node;

[0032] A task scheduling module, which is connected to the transmission analysis module, and is used to determine the task scheduling method according to the distribution state of a certain type of device in the processing node;

[0033] A data optimization module, which is connected to the transmission analysis module, and is used to determine whether to perform preferred device screening according to whether there is a set of similar devices;

[0034] A data transmission module, which is respectively connected to the task scheduling module and the data optimization module, and is used to complete the transmission of the data to be uploaded according to the task scheduling result and the data optimization result.

[0035] Compared with the prior art, the beneficial effect of the present invention is that in the technical solution of the present invention, the associated device category is determined according to whether the data to be uploaded of each associated device is in a sensitive state, and the transmission adjustment method of the corresponding processing node is determined according to the proportion of a certain type of device in each processing node, so that the selected transmission method conforms to the actual working scenario, ensuring the security of the data transmission process while also ensuring the data transmission efficiency. The present invention improves the security of device data during the transmission process.

[0036] Furthermore, the present invention determines the task scheduling method according to the distribution state of a certain type of device in the processing node. If a certain type of device is in an aggregated state, task scheduling is performed on the data to be uploaded corresponding to the certain type of device in the aggregated area where the certain type of device is located, which can ensure that the position correlation between the device data transmitted by the processing node at one time is relatively low, so as to avoid the leakage of the position distribution of photovoltaic devices due to the leakage of device data. The present invention improves the security of device data during the transmission process.

[0037] Furthermore, when a certain type of device is in a discrete state, the present invention determines whether to perform task scheduling on the data to be uploaded of the certain type of device according to the performance similarity between the certain type of device and the associated device in the corresponding processing node, ensuring that the device performance correlation between the device data transmitted by the target scheduling node after task scheduling is relatively low, and avoiding the leakage of the performance of devices of the same model due to the leakage of device data. The present invention improves the security of device data during the transmission process.

[0038] Further, it is determined whether to perform preferred device screening based on the existence of a set of similar devices. If there is a set of similar devices, preferred devices with a preset preferred quantity are determined according to the preferred transmission coefficients of each type of device within the set of similar devices, which can reduce the data transmission content and improve the data transmission efficiency while avoiding the disclosure of the device layout. For the data to be uploaded corresponding to the type of device other than the set of similar devices, the delay transmission time of the corresponding data to be uploaded is set according to the performance change value of each type of device, which can ensure the real-time performance of abnormal data transmission while ensuring data security. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a schematic diagram of the enterprise information data management and warning method of the present invention;

[0040] Figure 2 It is a flowchart of the present invention for determining the transmission adjustment method of the corresponding processing node according to the proportion of a type of device of each processing node;

[0041] Figure 3 It is a flowchart of the present invention for determining the task scheduling method according to the distribution state of a type of device of the processing node;

[0042] Figure 4 It is a module connection diagram of the enterprise information data management and warning system of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0043] In order to make the objectives and advantages of the present invention clearer, the present invention will be further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0044] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are only used to explain the technical principle of the present invention and do not limit the protection scope of the present invention.

[0045] It should be noted that in the description of the present invention, the terms indicating the direction or positional relationship such as "upper", "lower", "left", "right", "inner", "outer", etc. are based on the direction or positional relationship shown in the drawings. This is only for convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation of the present invention.

[0046] In addition, it should be noted that in the description of the present invention, unless otherwise clearly defined and limited, the terms "installation", "connection", and "coupling" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, and it can be the communication inside two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations.

[0047] Please refer to Figures 1 to 3 As shown, the present invention provides an enterprise information data management and warning method, including:

[0048] Obtaining the data to be uploaded of each associated device, and determining the category of the associated device according to whether the data to be uploaded of each associated device is in a sensitive state;

[0049] Determining the transmission adjustment method corresponding to the processing node according to the proportion of a certain type of device in each processing node, where the transmission adjustment method includes performing transmission task scheduling for the processing node or performing data optimization for the data to be uploaded of each certain type of device;

[0050] If transmission task scheduling is performed, then determining the task scheduling method according to the distribution state of a certain type of device in the processing node, and the task scheduling method includes determining the target scheduling node according to the proportion of the aggregation area of each processing node or the number of similar devices;

[0051] If data optimization is performed, then determining whether to perform preferred device screening according to whether there is a set of similar devices in each processing node;

[0052] Completing the transmission of the data to be uploaded according to the task scheduling result and the data optimization result.

[0053] Among them, in the present invention, there are several photovoltaic device areas, and each photovoltaic device area is correspondingly provided with a processing node and several photovoltaic devices. The photovoltaic devices in the photovoltaic device area corresponding to each processing node are the associated devices of the processing node. In the present invention, each processing node periodically sends device data to the user. The device data that each associated device needs to send to the user within a single cycle is the data to be uploaded of the corresponding associated device. The data to be uploaded is various device information of the associated devices within a data transmission cycle of each associated device, and the content of the device information includes but is not limited to the photoelectric conversion efficiency, fill factor, power generation of the device, installation location, and installation angle of the device;

[0054] In the present invention, a cyclic data transmission period is applied, and the duration of the data transmission period can be determined by the user himself. The higher the user's real-time requirement for data transmission, the shorter the duration of the data transmission period. A duration of the data transmission period is provided, and the data transmission period is 15 minutes. At the end of each data transmission period, the data monitoring module analyzes the data to be uploaded of each associated device of each processing node to determine the associated device category, and the transmission analysis module adjusts the transmission process according to the proportion of a certain type of device, and transmits the data to be uploaded of each photovoltaic device in the current data transmission period. After completing the task scheduling and data optimization, the data transmission module transmits the data to be uploaded of each photovoltaic device in this data transmission period.

[0055] Specifically, periodically detect whether the data to be uploaded of each associated device of each processing node is in a sensitive state, and determine the associated device category according to whether the data to be uploaded of each associated device is in a sensitive state. If the data to be uploaded is in a sensitive state, mark the corresponding associated device as a certain type of device.

[0056] Specifically, the sensitive state is determined according to whether the data to be uploaded of the associated device contains location information and performance information;

[0057] If the data to be uploaded of the associated device contains location information or performance information, it is determined that the data to be uploaded of the associated device is in a sensitive state.

[0058] Among them, the location information includes but is not limited to the installation location, installation angle and orientation of the photovoltaic device, and the performance information includes but is not limited to the conversion efficiency, fill factor and irradiance response of the photovoltaic device. The user can make adaptive settings for the location information and performance information according to actual needs.

[0059] Specifically, for a single processing node, if the proportion of a certain type of device of the processing node is greater than a preset proportion, it is determined that the transmission task scheduling is performed for the processing node, and the task scheduling method is determined according to the distribution state of the certain type of device of the processing node;

[0060] The task scheduling method includes task scheduling for the data to be uploaded corresponding to a certain type of device in the aggregation area and determining whether to perform task scheduling for the data to be uploaded of the certain type of device according to the performance similarity between the certain type of device and the associated device in the corresponding processing node;

[0061] The distribution state is determined according to the number of a certain type of device within the preset range of each certain type of device, and the distribution state includes an aggregation state and a discrete state.

[0062] Among them, for a single processing node, the proportion of a certain type of device corresponding to it is the ratio of the number of a certain type of device corresponding to the processing node to the number of associated devices. The value of the preset proportion can be set by the user according to actual needs and historical records. The higher the user's requirement for the security of device data during the data transmission process, the smaller the value of the preset proportion. A method for obtaining the value of the preset proportion is provided. The historical records without task scheduling are recorded as reference records. Among the reference records that meet the user's requirement for the security of device data during the data transmission process, the proportion of a certain type of device of each processing node is recorded as the preset proportion. In this embodiment, the preferred value of the preset proportion is 30%.

[0063] The preset range is a circular area with the location of each certain type of device as the center and the preset area length as the radius. The value of the preset area length can be set by the user according to actual needs and historical records. The higher the user's requirement for the security of device data during the data transmission process, the larger the preset area length. A method for obtaining the value of the preset area length is provided. The average value of the interval distances between each certain type of device in the aggregation area in the historical records that meet the user's requirement for the security of device data during the data transmission process is recorded as the preset area length.

[0064] If the number of a certain type of device within the preset range of a certain type of device is greater than the preset number of a certain type of device, the certain type of device is in an aggregated state. If the number of a certain type of device within the preset range of a certain type of device is less than or equal to the preset number of a certain type of device, the certain type of device is in a discrete state. The value of the preset number of a certain type of device is set by the user according to actual needs and historical records. The higher the user's requirement for the security of device data during the data transmission process, the smaller the preset number of a certain type of device. A method for obtaining the value of the preset number of a certain type of device is provided. The value of the preset number of a certain type of device is 30% of the average value of the number of associated devices within each preset range.

[0065] Specifically, for a single certain type of device, if the certain type of device is in an aggregated state, task scheduling is performed on the data to be uploaded corresponding to the certain type of device within the aggregation area where the certain type of device is located, and several target scheduling nodes are determined according to the aggregation area proportion of each processing node.

[0066] For any certain type of device that needs to perform task scheduling, the target scheduling node of the corresponding certain type of device is determined according to the number of similar devices among the associated devices of each processing node.

[0067] The number of the target scheduling nodes has a positive correlation with the number of a certain type of device within the aggregation area.

[0068] The aggregation area is a set of the preset ranges of each certain type of device with overlapping preset ranges, and the preset range of any certain type of device within the set area intersects with the preset range of at least one certain type of device.

[0069] Among them, the proportion of the aggregation area = the area of the aggregation area within the photovoltaic device area corresponding to each processing node / the area of the photovoltaic device area corresponding to the corresponding processing node. Since the processing nodes with aggregation areas all need to perform task scheduling, selecting the processing node with a larger proportion of the aggregation area can avoid excessive data transmission tasks of the processing node after the task scheduling is completed, resulting in low data transmission efficiency. Therefore, the processing node with a larger proportion of the aggregation area is preferentially selected as the target scheduling node;

[0070] For any type of device that needs to perform task scheduling, the similar device is the one corresponding to this type of device. Specifically, for a single type of device, if the type of device is in a discrete state, it is determined whether to perform task scheduling for the data to be uploaded of this type of device according to the performance similarity reference value of the type of device in its corresponding processing node;

[0071] If the performance similarity reference value of this type of device is greater than the preset performance similarity reference value, task scheduling is performed for the data to be uploaded of this type of device, and the target scheduling node of this type of device is determined according to the amount of data to be transmitted in the current cycle of each processing node.

[0072] Among them, the performance similarity reference value is the average value of the performance similarities of each type of device in a type of device and its corresponding processing node. The user can set the value of the preset performance similarity reference value according to actual needs and historical records. The higher the user's requirement for the device data security during the data transmission process, the smaller the value of the preset performance similarity reference value. In this embodiment, a method for obtaining the value of the preset performance similarity reference value is provided. The average value of the performance similarities of each type of device when each processing node performs data transmission in the historical records that meet the user's requirement for the device data security during the data transmission process is recorded as the preset performance similarity reference value. The amount of data to be transmitted is the sum of the amounts of data to be uploaded that each processing node needs to transmit.

[0073] Specifically, for a single processing node, if the proportion of a type of device in the processing node is less than or equal to the preset proportion, data optimization is performed on the data to be uploaded of each type of device, and it is determined whether to perform preferred device screening according to whether there is a set of similar devices;

[0074] The set of similar devices is determined according to the device interval distance and the performance similarity.

[0075] Among them, the performance similarity between any two types of devices in the set of similar devices is greater than the preset performance similarity, and the device interval distance between any two adjacent types of devices is less than or equal to the preset device interval distance. The performance similarity is determined according to the conversion efficiency difference value and the fill factor difference value. The performance similarity X = e h +e t, where h is the conversion efficiency difference value and t is the fill factor difference value. The conversion efficiency difference value is the absolute value of the difference in the photoelectric conversion efficiencies of two photovoltaic devices, and the fill factor difference value is the absolute value of the difference in the fill factors of two photovoltaic devices. The fill factor is the ratio of the maximum power of the battery of the photovoltaic device to the product of the open-circuit voltage and the short-circuit current;

[0076] The values of the preset performance similarity and the preset device spacing can be set by the user according to actual needs and historical records. The higher the user's requirement for the integrity of the optimized device data, the larger the value of the preset performance similarity and the smaller the preset device spacing. A method for obtaining the value of the preset performance similarity is provided, where the average value of the performance similarities within each set of similar devices in the historical records that meet the user's requirement for the integrity of the optimized device data is recorded as the preset performance similarity. A method for obtaining the value of the preset device spacing is provided, where the average value of the device spacings between adjacent devices of the same type within each set of similar devices in the historical records that meet the user's requirement for the integrity of the optimized device data is recorded as the preset device spacing.

[0077] Specifically, if there is a set of similar devices among the devices of the same type at a processing node, the preferred devices with a preset preferred quantity are determined according to the preferred transmission coefficients of the devices of the same type within the set of similar devices. During the current data transmission cycle, for the devices of the same type within the set of similar devices, only the data to be uploaded of the preferred devices is transmitted;

[0078] The preferred transmission coefficient is determined according to the position difference reference value and the operating data change value.

[0079] Among them, the preferred transmission coefficient is the natural logarithm of the ratio of the operating data change value to the position difference reference value. The operating data change value is the absolute value of the difference between the device power generation in the current cycle and the device power generation in the previous cycle for each device of the same type. The position difference reference value for each device of the same type is the average value of the spacing between the device and other devices of the same type within its set of similar devices;

[0080] The devices of the same type with a larger preferred transmission coefficient are selected as the preferred devices. The value of the preset preferred quantity can be set by the user according to actual needs. The higher the user's requirement for the security of device data during the data transmission process, the smaller the value of the preset preferred quantity. A method for obtaining the value of the preset preferred quantity is provided, and the value of the preset preferred quantity is 10% of the number of devices of the same type within the set of similar devices.

[0081] Specifically, for the data to be uploaded corresponding to the devices of the same type other than the set of similar devices at each processing node, the delay transmission time of the corresponding data to be uploaded is set according to the operating data change value of each device of the same type;

[0082] The duration of the delayed transmission time is negatively correlated with the change value of the operation data of each type-I device.

[0083] Among them, if there is no similar device set in the type-I devices of the processing node, or there are still type-I devices in the processing node except for the similar device set, the data to be uploaded of the type-I devices that have not undergone data optimization is delayed for transmission, and the data to be uploaded is adjusted to be transmitted within a subsequent data transmission cycle. The delayed transmission time is the time interval between the termination moment of the current data transmission cycle and the start moment of the data transmission cycle for the adjusted data transmission.

[0084] Please refer to Figure 4 As shown, it is a module connection diagram of the enterprise information data management and warning system of the present invention. The present invention also provides an enterprise information data management and warning system, including:

[0085] A data monitoring module, used to periodically detect whether the data to be uploaded of each associated device of each processing node is in a sensitive state and determine the associated device category;

[0086] A transmission analysis module, connected to the data monitoring module, used to determine the transmission adjustment method of the corresponding processing node according to the proportion of type-I devices of each processing node;

[0087] A task scheduling module, connected to the transmission analysis module, used to determine the task scheduling method according to the distribution state of type-I devices of the processing node;

[0088] A data optimization module, connected to the transmission analysis module, used to determine whether to perform preferred device screening according to the existence of a similar device set;

[0089] A data transmission module, respectively connected to the task scheduling module and the data optimization module, used to complete the transmission of the data to be uploaded according to the task scheduling result and the data optimization result.

[0090] So far, the technical solution of the present invention has been described in combination with the preferred embodiments shown in the drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0091] The above are only the preferred embodiments of the present invention and are not used to limit the present invention; for those skilled in the art, the present invention can have various changes and modifications. Any modification, equivalent substitution, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An enterprise information data management and warning method, characterized in that Including: Obtain the data to be uploaded of each associated device, periodically detect whether the data to be uploaded of each associated device of each processing node is in a sensitive state, and determine the associated device category according to whether the data to be uploaded of each associated device is in a sensitive state. If the data to be uploaded is in a sensitive state, mark the corresponding associated device as a type-1 device; Determine the transmission adjustment method corresponding to the processing node according to the proportion of type-1 devices in each processing node. The transmission adjustment method includes performing transmission task scheduling for the processing node or performing data optimization on the data to be uploaded of each type-1 device; If transmission task scheduling is performed, determine the task scheduling method according to the distribution state of type-1 devices in the processing node. The task scheduling method includes determining the target scheduling node according to the proportion of the aggregation area of each processing node or the number of similar devices; If data optimization is performed, determine whether to perform preferred device screening according to whether there is a set of similar devices in each processing node; Complete the transmission of the data to be uploaded according to the task scheduling result and the data optimization result.

2. The enterprise information data management and warning method according to claim 1, wherein The sensitive state is determined according to whether the data to be uploaded of the associated device contains location information and performance information; If the data to be uploaded of the associated device contains location information or performance information, it is determined that the data to be uploaded of the associated device is in a sensitive state.

3. The enterprise information data management and warning method according to claim 2, wherein For a single processing node, if the proportion of type-1 devices in the processing node is greater than the preset proportion, it is determined to perform transmission task scheduling for the processing node, and determine the task scheduling method according to the distribution state of type-1 devices in the processing node; The task scheduling method includes performing task scheduling for the data to be uploaded corresponding to type-1 devices in the aggregation area and determining whether to perform task scheduling for the data to be uploaded of the type-1 device according to the performance similarity between the type-1 device and the associated devices in the corresponding processing node; The distribution state is determined according to the number of type-1 devices within the preset range of each type-1 device, and the distribution state includes an aggregation state and a discrete state.

4. The enterprise information data management and warning method according to claim 3, wherein For a single type-1 device, if the type-1 device is in an aggregation state, perform task scheduling for the data to be uploaded corresponding to the type-1 devices in the aggregation area where the type-1 device is located, and determine several target scheduling nodes according to the proportion of the aggregation area of each processing node; For any type-1 device that needs to perform task scheduling, determine the target scheduling node of the corresponding type-1 device according to the number of similar devices among the associated devices of each processing node; The number of the target scheduling nodes is in a positive correlation with the number of type-1 devices in the aggregation area; The aggregation area is a set of the preset ranges of each type-1 device with overlapping preset ranges, and the preset range of any type-1 device within the set area intersects with the preset range of at least one type-1 device.

5. The enterprise information data management and warning method according to claim 4, characterized in that For a single type-1 device, if the type-1 device is in a discrete state, determine whether to perform task scheduling for the data to be uploaded of the type-1 device according to the performance similarity reference value between the type-1 device and the type-1 devices in its corresponding processing node; If the performance similarity reference value of the type-1 device is greater than the preset performance similarity reference value, perform task scheduling for the data to be uploaded of the type-1 device, and determine the target scheduling node of the type-1 device according to the amount of data to be transmitted in each processing node in the current period.

6. The enterprise information data management and warning method according to claim 5, characterized in that, For a single processing node, if the proportion of a certain type of device in the processing node is less than or equal to a preset proportion, data optimization is performed on the data to be uploaded for each device of the certain type, and whether to perform preferred device screening is determined according to the existence of a similar device set; The similar device set is determined according to the device interval distance and the performance similarity.

7. The enterprise information data management and warning method according to claim 6, characterized in that If there is a similar device set among the devices of a certain type in the processing node, preferred devices with a preset preferred quantity are determined according to the preferred transmission coefficients of the devices of a certain type in the similar device set. During the current data transmission period, for the devices of a certain type in the similar device set, only the data to be uploaded of the preferred devices is transmitted; The preferred transmission coefficient is determined according to the position difference reference value and the operating data change value.

8. The enterprise information data management and warning method according to claim 7, characterized in that For the data to be uploaded corresponding to the devices of a certain type other than the similar device set for each processing node, the delay transmission time of the corresponding data to be uploaded is set according to the operating data change value of each device of the certain type; The duration of the delay transmission time has a negative correlation with the operating data change value of each device of the certain type.

9. An early warning system applying the enterprise information data management early warning method according to any one of claims 1 to 8, characterized in that, Including: A data monitoring module for periodically detecting whether the data to be uploaded of each associated device of each processing node is in a sensitive state and determining the associated device category; A transmission analysis module connected to the data monitoring module for determining the transmission adjustment method of the corresponding processing node according to the proportion of the devices of a certain type in each processing node; A task scheduling module connected to the transmission analysis module for determining the task scheduling method according to the distribution state of the devices of a certain type in the processing node; A data optimization module connected to the transmission analysis module for determining whether to perform preferred device screening according to the existence of a similar device set; A data transmission module respectively connected to the task scheduling module and the data optimization module for completing the transmission of the data to be uploaded according to the task scheduling result and the data optimization result.

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