An office data management method and system based on edge computing

Abstract

The present application relates to an office data management method and system based on edge computing, the method includes obtaining the office data of each management terminal of the enterprise and converting the data format, converting the office data of each management terminal to generate enterprise office data in a unified data format and storing it in a management cloud, associating the terminal business association relationship between the enterprise office data related to each terminal business, constructing a data reuse model between the management cloud and several management terminals according to the terminal business association relationship, calculating the load computing power value of each management terminal, inputting the load computing power value into the data reuse model, performing computing power resource matching processing on each management terminal, calling the computing power resources of the management cloud according to the computing power resource matching result to coordinately allocate all management terminals, and processing the terminal business of each management terminal according to the resource allocation result. The present application has the effect of improving the management convenience of enterprise office data.

Description

Technical Field

[0001] The present invention relates to the technical field of office management, and in particular to an office data management method and system based on edge computing. Background Art

[0002] At present, with the popularization of information technology, traditional paper-based office is gradually being replaced by paperless office. Unified management of all affairs of the entire enterprise through an integrated paperless office system has become a hot topic in current office management. In the process of unified management of enterprise affairs, higher requirements are placed on the orderly management of office data.

[0003] The existing office data management method is mainly divided into multiple management systems according to department functions. The multiple management systems are independent of each other and manage the office data of the corresponding departments respectively. For example, the OA system manages enterprise personnel data, the financial system manages enterprise asset data, and the office system manages enterprise terminal business data. However, the personnel, assets and terminal businesses of the enterprise all work in coordination with each other. The independent management model is not conducive to the comprehensive management of the enterprise. In addition, there are information barriers between different management systems, making it difficult to centrally manage all enterprise data. Management personnel are required to check the data of each system one by one and make manual comprehensive judgments. Each management system cannot reasonably allocate the computing power resources in the business processing process, resulting in the inconvenience of the enterprise's office management. Summary of the invention

[0004] In order to improve the convenience of managing enterprise office data, the present application provides an office data management method and system based on edge computing.

[0005] In the first aspect, the above-mentioned invention objective of the present application is achieved through the following technical solutions:

[0006] An office data management method based on edge computing, comprising:

[0007] Obtain the office data of each management terminal of the enterprise and convert the data format, convert the office data of each management terminal into enterprise office data in a unified data format, and store it in the management cloud;

[0008] Constructing a terminal business association relationship between enterprise office data related to each terminal business, and constructing a data reuse model between the management cloud and a plurality of management terminals based on the terminal business association relationship;

[0009] Calculate the load computing power value of each management terminal, input the load computing power value into the data reuse model, and perform computing power resource matching processing on each management terminal;

[0010] According to the computing power resource matching results, the computing power resources of the management cloud are called to coordinate allocation to all management terminals, and the terminal business of each management terminal is processed according to the resource allocation results.

[0011] By adopting the above technical solution, the data format of the office data of each management terminal is converted, and the convenience of calling business data on the management cloud is improved by unifying the data format. The enterprise office data associated with each terminal business is business-associated with the terminal business as the association point to obtain the terminal business association relationship, and further construct a data reuse model between the management cloud and multiple management terminals, so that the computing tasks of the management cloud can be sent to multiple management terminals through the data reuse model, reducing the computing pressure of the management cloud, and synchronously calling the enterprise office data of multiple business-related management terminals through the data reuse model, which is convenient for the centralized management of enterprise office data, and accurate computing power resource matching is performed according to the load computing power value of each management terminal, so as to improve the balance of computing power resource allocation on the management cloud, and accurately allocate the management of computing power resources to each terminal business of each management terminal, thereby improving the convenience of enterprise office data management.

[0012] In a preferred example, the present application may be further configured as follows: the calculation of the load computing power value of each management terminal specifically includes:

[0013] The load computing power value of each management terminal is calculated by formula (1), which is as follows:

[0014] (1);

[0015] in, Indicates the load computing power value of the management terminal, n indicates the number of connected loads of the current management terminal, Indicates the load factor of the current management terminal. Indicates the node load value of each business node of the management terminal. Indicates the terminal load value of the management terminal. Indicates the resource idle value of the management terminal. Indicates the sum of the computing power required for each business of the current management terminal. It is the number of routing hops between the business node and the management cloud.

[0016] In a preferred example, the present application may be further configured as follows: the load computing power value is input into the data reuse model, and computing power resource matching processing is performed on each management terminal, specifically including:

[0017] Calculate the sum of the load computing power values ​​input into the data reuse model at the same time and the remaining computing power resources of the management cloud;

[0018] According to the data reuse model, determining whether the remaining computing power resources meet the operation requirements of the total load computing power value;

[0019] If yes, then calculate the load computing power value ratio of the newly connected loads connected to the management cloud at the same time according to the load computing power value;

[0020] According to the proportion of the load computing power value, the remaining computing power resources are proportionally allocated to several management terminals connected at the same time for computing power resource matching processing.

[0021] By adopting the above technical solution, the energy consumption of mobilizing computing resources is controlled within the minimum range through the calculation of the load computing power value of the management terminal, reducing the pressure of data transmission, and using the computing power required for the terminal access load of the data reuse model to distribute the remaining computing power resources of the current management cloud in proportion, and to coordinate computing power resource allocation for multiple management terminals connected at the same time at the same time, thereby improving the rate of resource matching.

[0022] In a preferred example, the present application may be further configured as follows: judging whether the remaining computing power resources meet the operation requirements of the total load computing power value according to the data reuse model, further comprising:

[0023] If not, searching for an associated management terminal that matches the terminal service type in the data reuse model according to the terminal service type of the current management terminal, and obtaining the idle computing power value of each associated management terminal;

[0024] According to the computing power idle value, calculate the sum of the computing power idle values ​​of all associated management terminals, and determine whether the sum of the computing power idle values ​​meets the operation requirement of the sum of the load computing power value;

[0025] If yes, then calculating the number of resource call routing hops between each associated management terminal and the current management terminal, and adjusting the computing power calling order of the idle computing power resources according to the number of resource call routing hops;

[0026] The idle computing resources of each associated management terminal are called in turn according to the computing power calling order to perform computing power resource compensation processing on the current management terminal.

[0027] By adopting the above technical solution, the business type is used as the search tag, the association matching of the associated management terminals is performed in the data reuse model, and the degree of adaptation between the sum of the idle computing power values ​​and the sum of the load computing power values ​​is used to determine whether the sum of the idle computing power values ​​meets the operation requirements of the sum of the load computing power values, so as to reasonably plan the calling path of the idle computing power resources, adjust the computing power calling sequence in combination with the number of resource calling routing hops between the associated management terminal and the current management terminal, reduce the calling energy consumption of the computing power resources, and call the idle computing power resources of each associated management terminal in turn according to the computing power calling sequence to compensate the current management terminal for computing power resources. When the idle computing power of the management cloud cannot support the operation requirements of the current management terminal, the computing power resources are compensated in a timely and orderly manner through other associated management terminals, so as to further improve the coordination of the calling of computing power resources.

[0028] In a preferred example, the present application may be further configured as follows: the sum of idle computing power values ​​of each associated management terminal is calculated, and the sum of idle computing power values ​​is judged whether the sum of idle computing power values ​​meets the operation requirements of the sum of load computing power values, and further includes:

[0029] If not, then obtaining the current running business progress of each of the associated management terminals, and analyzing the expiration release computing power and computing power release time nodes of the associated management terminals according to the current running business progress;

[0030] Optimizing the computing power calling sequence of the associated management terminal according to the computing power release time node, and calling the corresponding expired released computing power according to the optimized computing power calling sequence to perform computing power resource compensation processing on the current management terminal;

[0031] The data reuse model calls the computing resources of the current management terminal through formula (2), which is as follows:

[0032] (2);

[0033] in, Indicates the current idle computing resource value of the management cloud. Represents the total load computing power value in the data reuse model. Indicates the load computing power value of the current management terminal. It means managing the remaining computing resources in the cloud. Indicates the idle computing power value of the associated management terminal. Indicates the number of associated management terminals corresponding to the sum of the idle computing power values ​​of the associated management terminals required to meet the computing power resource compensation. The number of associated management terminals corresponding to the expired released computing power required to meet the computing power resource compensation, Indicates the expired released computing power value corresponding to each computing power release time node.

[0034] By adopting the above technical solution, when the idle computing power resources of the associated management terminal cannot meet the computing power requirements of the current management terminal, the computing power release time node and the expired released computing power resources of each running business are analyzed according to the current running business progress of the associated management terminal. When the computing power release time node is reached, the computing power call sequence of the corresponding associated management terminal is timely optimized, and the corresponding expired released computing power is called to supplement the computing power resources of the current management terminal, which helps to make timely and reasonable use of the expired released computing power.

[0035] In a preferred example, the present application may be further configured as follows: the acquisition of office data of each management terminal of the enterprise and conversion of the data format, converting the office data of each management terminal into the enterprise office data in a unified data format, specifically includes:

[0036] Obtaining the management function of each management terminal of the enterprise, and classifying the business of the management terminal according to the management function;

[0037] Plan the business scope of each business node in the current management terminal according to the business classification results, and mark the business management authority of each business node according to the planned business scope;

[0038] The business classification and the business management authority are used as data format prefixes, and the data format of the office data of the management terminal is converted to generate enterprise office data in which the business classification, business management authority and office data are sequentially associated.

[0039] By adopting the above technical solution, business classification is performed according to the management functions of the enterprise management terminal, and the business scope of each business node in the current management terminal is classified and planned, so as to accurately mark the actual management authority of each business node, and use business classification and business management authority as prefixes for data format conversion, and perform unified data format conversion on the office data of each management terminal. Through the multi-label combination of business classification, business management authority and office data, the uniqueness of the data after data format conversion is improved, which facilitates the unique storage of enterprise office data and reduces data call errors.

[0040] In the second aspect, the above invention objective of the present application is achieved through the following technical solutions:

[0041] An office data management system based on edge computing, comprising:

[0042] The data conversion module is used to obtain the office data of each management terminal of the enterprise and convert the data format, convert the office data of each management terminal into enterprise office data in a unified data format, and store it in the management cloud;

[0043] A model building module, used to associate the terminal business association relationship between the enterprise office data related to each terminal business, and build a data reuse model between the management cloud and a plurality of management terminals according to the terminal business association relationship;

[0044] A resource matching module, used to calculate the load computing power value of each management terminal, input the load computing power value into the data reuse model, and perform computing power resource matching processing on each management terminal;

[0045] The business processing module is used to call the computing resources of the management cloud to coordinate allocation to all management terminals according to the computing resource matching results, and process the terminal business of each management terminal according to the resource allocation results.

[0046] By adopting the above technical solution, the data format of the office data of each management terminal is converted, and the convenience of calling business data on the management cloud is improved by unifying the data format. The enterprise office data associated with each terminal business is business-associated with the terminal business as the association point to obtain the terminal business association relationship, and further construct a data reuse model between the management cloud and multiple management terminals, so that the computing tasks of the management cloud can be sent to multiple management terminals through the data reuse model, reducing the computing pressure of the management cloud, and synchronously calling the enterprise office data of multiple business-related management terminals through the data reuse model, which is convenient for the centralized management of enterprise office data, and accurate computing power resource matching is performed according to the load computing power value of each management terminal, so as to improve the balance of computing power resource allocation on the management cloud, and accurately allocate the management of computing power resources to each terminal business of each management terminal, thereby improving the convenience of enterprise office data management.

[0047] On the third aspect, the above-mentioned purpose of the present application is achieved through the following technical solutions:

[0048] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the above-mentioned office data management method based on edge computing are implemented.

[0049] Fourthly, the above-mentioned purpose of the present application is achieved through the following technical solutions:

[0050] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the above-mentioned office data management method based on edge computing.

[0051] In summary, the present application includes at least one of the following beneficial technical effects:

[0052] 1. Perform data format conversion on the office data of each management terminal, improve the convenience of calling business data on the management cloud by unifying the data format, associate the enterprise office data associated with each terminal business with the terminal business as the association point, obtain the terminal business association relationship, and further build a data reuse model between the management cloud and multiple management terminals, so that the computing tasks of the management cloud can be sent to multiple management terminals through the data reuse model, reducing the computing pressure of the management cloud, and synchronously call the enterprise office data of multiple business-related management terminals through the data reuse model, which is convenient for the centralized management of enterprise office data, and accurately match the computing power resources according to the load computing power value of each management terminal, so as to improve the balance of computing power resource allocation on the management cloud, accurately allocate the management of computing power resources to the needs of each terminal business of each management terminal, and improve the convenience of enterprise office data management;

[0053] 2. By calculating the load computing power value of the management terminal, the energy consumption of mobilizing computing power resources is controlled to the minimum range, reducing the pressure of data transmission. The computing power required for the terminal access load of the data reuse model is proportionally allocated to the remaining computing power resources of the current management cloud. At the same time, collaborative computing power resources are allocated to multiple management terminals connected at the same time to improve the rate of resource matching;

[0054] 3. Use the business type as the search tag to match the association of the associated management terminals in the data reuse model, and judge whether the sum of the idle computing power values ​​meets the operating requirements of the total load computing power values ​​according to the degree of adaptation between the sum of the idle computing power values ​​and the total load computing power values, so as to reasonably plan the calling path of the idle computing power resources, and adjust the computing power calling sequence in combination with the number of resource calling routing hops between the associated management terminal and the current management terminal to reduce the calling energy consumption of the computing power. In accordance with the computing power calling sequence, call the idle computing power resources of each associated management terminal in turn to compensate the current management terminal for computing power resources. When the idle computing power of the management cloud cannot support the operating requirements of the current management terminal, timely and orderly compensate for the computing power resources through other associated management terminals to further improve the coordination of the calling of computing power resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 This is a flow chart of an implementation of an office data management method based on edge computing in this embodiment.

[0056] Figure 2 This is a flowchart for implementing step S10 of an office data management method based on edge computing in this embodiment.

[0057] Figure 3 This is a flowchart for implementing computing power resource matching of an office data management method based on edge computing in this embodiment.

[0058] Figure 4 This is another implementation flowchart of step S302 of the office data management method based on edge computing in this embodiment.

[0059] Figure 5 This is another implementation flowchart of step S3022 of the office data management method based on edge computing in this embodiment.

[0060] Figure 6 This is a structural block diagram of an office data management system based on edge computing in this embodiment.

[0061] Figure 7 It is a schematic diagram of the internal structure of a computer device used to implement an office data management method based on edge computing. DETAILED DESCRIPTION

[0062] The present application is further described in detail below in conjunction with the accompanying drawings.

[0063] In one embodiment, if Figure 1 As shown, the present application discloses an office data management method based on edge computing, which specifically includes the following steps:

[0064] S10: Obtain the office data of each management terminal of the enterprise and convert the data format, convert the office data of each management terminal into enterprise office data in a unified data format, and store it in the management cloud.

[0065] Specifically, Figure 2 As shown, step S10 specifically includes:

[0066] S101: Obtain the management function of each management terminal of the enterprise, and classify the business of the management terminals according to the management function.

[0067] Specifically, the management terminals are classified according to their management functions such as human resources management, asset management, business management, etc. For example, personnel transfer business includes personnel transfer, asset transfer corresponding to personnel, and business changes for personnel, or sales personnel allocation, sales asset changes, and sales business line changes in sales tasks. Different management functions correspond to different business classifications, among which business classifications include human resources, asset finance and taxation, and corporate business.

[0068] S102: Plan the service scope of each service node in the current management terminal according to the service classification result, and mark the service management authority of each service node according to the planned service scope.

[0069] Specifically, according to the business classification results, the current management terminal such as personnel calls the corresponding OA management terminal, and plans the business scope of each business node in the OA management terminal, including multiple business nodes such as personnel transfer nodes, approval nodes, review nodes and coordination nodes. For example, the personnel node is the transferred personnel, the approval node is the approval of the personnel transfer application by the human resources department, the review node is the review of the current personnel transfer business by the department management position, and the coordination node is the overall management of the entire process of current personnel transfer and review by the enterprise leader. The business scope is planned according to business capabilities, and the management scope of each business node is divided and marked with authority.

[0070] S103: Using the business classification and business management authority as data format prefixes, converting the data format of the office data of the management terminal, and generating enterprise office data in which the business classification, business management authority and office data are sequentially associated.

[0071] Specifically, the keywords corresponding to the business classification and business management authority are converted into binary, and the converted business classification and business management authority are used as data format prefixes to be spliced ​​with the office data. The spliced ​​data is encrypted and transcoded using a preset encryption algorithm such as AES, DES, etc., so as to obtain enterprise office data spliced ​​in sequence with business classification, business management authority and office data. The enterprise office data is encrypted and transmitted according to the information channel between each management terminal and the management cloud, and the enterprise office data is centrally stored through the management cloud.

[0072] S20: Associating the terminal business association relationship between the enterprise office data related to each terminal business, and building a data reuse model between the management cloud and several management terminals based on the terminal business association relationship.

[0073] Specifically, terminal business is used as a key tag for searching, and enterprise office data related to terminal business is searched in all management terminals. The enterprise office data of multiple management terminals whose data formats are prefixed with terminal business are associated together to obtain terminal business association relationships. The terminal business association relationships of all existing terminal businesses are integrated together to obtain a data reuse model between the management cloud and multiple management terminals, wherein in the data reuse model, a one-to-many data association relationship is formed between the management cloud and multiple management terminals.

[0074] S30: Calculate the load computing power value of each management terminal, input the load computing power value into the data reuse model, and perform computing power resource matching processing on each management terminal.

[0075] Specifically, the calculation of the load computing power value of each management terminal in step S30 specifically includes:

[0076] The load computing power value of each management terminal is calculated by formula (1), which is as follows:

[0077] (1);

[0078] in, Indicates the load computing power value of the management terminal, n indicates the number of connected loads of the current management terminal, Indicates the load factor of the current management terminal. Indicates the node load value of each business node of the management terminal. Indicates the terminal load value of the management terminal. Indicates the resource idle value of the management terminal. Indicates the sum of the computing power required for each business of the current management terminal. It is the number of routing hops between the business node and the management cloud.

[0079] Specifically, Figure 3 As shown, in step S30, the load computing power value is input into the data reuse model, and computing power resource matching processing is performed on each management terminal, specifically including:

[0080] S301: Calculate the total load computing power value of the input data reuse model at the same time and manage the remaining computing power resources in the cloud.

[0081] Specifically, according to the load access time of the data reuse model, the load computing power values ​​of the management terminals accessing the data reuse model at the same time are calculated by formula (1), and the load computing power values ​​accessed at the same time are summarized according to the number of terminals accessed to obtain the total load computing power value. The maximum computing power value of the cloud is determined by the hardware performance of the management cloud server, and the remaining computing power resources are comprehensively calculated in combination with the running computing power value of the management cloud that has been connected or is running. For example, the remaining computing power value is equal to the maximum computing power value minus the running computing power value.

[0082] S302: According to the data reuse model, determine whether the remaining computing power resources meet the operating requirements of the total load computing power value.

[0083] Specifically, in the data reuse model, the remaining computing power resources are compared with the total load computing power value, and the comparison result is used to determine whether the remaining computing power resources can meet the operating requirements of the total load computing power value.

[0084] S303: If yes, then calculate the load computing power value ratio of the newly connected loads connected to the management cloud at the same time according to the load computing power value.

[0085] Specifically, when the remaining computing power resources are sufficient to meet the operating requirements of the total load computing power value, the total load computing power accessed at the same time is calculated according to the access time of each newly connected load, i.e., the management terminal, and the proportion of the load computing power value of each newly connected load is equal to the ratio between the load computing power value of a single newly connected load and the total load computing power.

[0086] S304: According to the proportion of load computing power value, the remaining computing power resources are proportionally distributed to several management terminals connected at the same time to perform computing power resource matching processing.

[0087] Specifically, the remaining computing power resources are allocated to multiple management terminals connected at the same time according to the proportion of load computing power value, and the computing power resources are matched and allocated to the corresponding business nodes according to the operation requirements of each business node.

[0088] In one embodiment, if Figure 4 As shown, step S302 also includes:

[0089] S3021: If not, then according to the terminal service type of the current management terminal, search for an associated management terminal that matches the terminal service type in the data reuse model, and obtain the idle computing power value of each associated management terminal.

[0090] Specifically, if the remaining computing power resources cannot meet the operating requirements of the total load computing power value, then combined with the terminal business type of the current management terminal, such as human resources management business, sales management business, asset management business, etc., find the associated management terminal that is compatible with the terminal business type of the current management terminal in the data reuse model. For example, in the sales management business, in the parallel management of business line A and business line B, business line B is used as the associated management terminal of business line A. When the computing power resources of business line A are insufficient, such as insufficient sales personnel, the operating computing power resources of idle personnel or idle unused assets of business line B are used as the computing power idle value of the management terminal of business line B.

[0091] S3022: Calculate the sum of the idle computing power values ​​of all associated management terminals according to the idle computing power value, and determine whether the sum of the idle computing power values ​​meets the operating requirements of the sum of the load computing power values.

[0092] Specifically, according to the computing power idle value of the associated management terminal, the computing power idle values ​​of all associated management terminals are superimposed to obtain the sum of the computing power idle values. The difference between the sum of the computing power idle values ​​and the sum of the load computing power values ​​is calculated through the data reuse model. According to the calculated difference, it is judged again whether the sum of the computing power idle values ​​meets the operating requirements of the sum of the load computing power values.

[0093] S3023: If yes, then calculate the resource call routing hop count between each associated management terminal and the current management terminal, and adjust the computing power call sequence of the idle computing power resources according to the resource call routing hop count.

[0094] When the sum of the idle computing power values ​​is greater than or equal to the sum of the load computing power values, it means that the sum of the idle computing power values ​​plus the idle computing power resources of the management cloud can meet the operating requirements of the total load computing power value. The number of resource call routing hops between each associated management terminal and the current management terminal is calculated, that is, the number of associated nodes between each associated management terminal and the current management terminal is counted, and each associated node is one hop, so the number of resource call routing hops is obtained. The resource call routing hops are sorted from small to large to obtain the computing power call order of the idle computing power resources of the associated management terminal.

[0095] S3024: Call the idle computing resources of each associated management terminal in turn according to the computing power calling order to perform computing power resource compensation processing on the current management terminal.

[0096] Specifically, the idle computing resources of each associated management terminal are called in turn according to the computing power calling order, and the idle computing resources are allocated to the current management terminal through the data reuse model to compensate the current management terminal for computing power resources.

[0097] In one embodiment, if Figure 5 As shown, step S3022 also includes:

[0098] S3025: If not, obtain the current running business progress of each associated management terminal, and analyze the expired release computing power and computing power release time node of the associated management terminal according to the current running business progress.

[0099] Specifically, when the sum of the idle computing power values ​​cannot meet the operating requirements of the sum of the load computing power values, the current operating business progress of each associated management terminal is obtained, and the business end time of the current operating business progress is analyzed, and the business end time of each operating business is sorted in sequence to obtain the computing power release time node sorting of multiple associated management terminals, and the computing power occupied resources of the expired business are used as the expired release computing power.

[0100] S3026: Optimize the computing power calling sequence of the associated management terminal according to the computing power release time node, and call the corresponding expired released computing power according to the optimized computing power calling sequence to perform computing power resource compensation processing on the current management terminal.

[0101] Specifically, when the computing power release time node is reached, the computing power call priority of the corresponding associated management terminal is adjusted to the highest, and inserted into the original computing power call order, the original computing power call order is optimized, and the expired released computing power of the associated management terminal that reaches the computing power release time node is preferentially called according to the optimized computing power call order, and the computing power resources of the current management terminal are compensated through the expired released computing power.

[0102] The data reuse model calls the computing resources of the current management terminal through formula (2), which is as follows:

[0103] (2);

[0104] in, Indicates the current idle computing resource value of the management cloud. Represents the total load computing power value in the data reuse model. Indicates the load computing power value of the current management terminal. It manages the remaining computing resources in the cloud. Indicates the idle computing power value of the associated management terminal. Indicates the number of associated management terminals corresponding to the sum of the idle computing power values ​​of the associated management terminals required to meet the computing power resource compensation. The number of associated management terminals corresponding to the expired released computing power required to meet the computing power resource compensation, Indicates the expired released computing power value corresponding to each computing power release time node.

[0105] S40: Call the computing resources of the management cloud to coordinate allocation to all management terminals according to the computing resource matching result, and process the terminal business of each management terminal according to the resource allocation result.

[0106] Specifically, the computing resources of the management cloud are called according to the computing resource matching results, and are allocated to each management terminal according to the matching ratio. The operation requirements of the terminal business are processed by the computing resources allocated to each management terminal.

[0107] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0108] In one embodiment, an office data management system based on edge computing is provided, and the office data management system based on edge computing corresponds one-to-one to the office data management method based on edge computing in the above embodiment. Figure 6 As shown in the figure, the office data management system based on edge computing includes a data conversion module, a model building module, a resource matching module and a business processing module. The detailed description of each functional module is as follows:

[0109] The data conversion module is used to obtain the office data of each management terminal of the enterprise and convert the data format, convert the office data of each management terminal into enterprise office data in a unified data format, and store it in the management cloud.

[0110] The model building module is used to associate the terminal business association relationship between the enterprise office data related to each terminal business, and build a data reuse model between the management cloud and several management terminals based on the terminal business association relationship.

[0111] The resource matching module is used to calculate the load computing power value of each management terminal, input the load computing power value into the data reuse model, and perform computing power resource matching processing for each management terminal.

[0112] The business processing module is used to call the computing resources of the management cloud to coordinate allocation to all management terminals according to the computing resource matching results, and process the terminal business of each management terminal according to the resource allocation results.

[0113] Preferably, calculating the load computing power value of each management terminal specifically includes:

[0114] The load computing power value of each management terminal is calculated by formula (1), which is as follows:

[0115] (1);

[0116] in, Indicates the load computing power value of the management terminal, n indicates the number of connected loads of the current management terminal, Indicates the load factor of the current management terminal. Indicates the node load value of each business node of the management terminal. Indicates the terminal load value of the management terminal. Indicates the resource idle value of the management terminal. Indicates the sum of the computing power required for each business of the current management terminal. It is the number of routing hops between the business node and the management cloud.

[0117] Preferably, the load computing power value is input into the data reuse model, and computing power resource matching processing is performed on each management terminal, specifically including:

[0118] The data computing submodule is used to calculate the total load computing power value of the input data reuse model at the same time and manage the remaining computing power resources in the cloud.

[0119] The operation analysis submodule is used to determine whether the remaining computing power resources meet the operation requirements of the total load computing power value based on the data reuse model.

[0120] The proportion calculation submodule is used to calculate the proportion of the load computing power value of the newly connected load connected to the management cloud at the same time according to the load computing power value.

[0121] The resource matching submodule is used to distribute the remaining computing power resources in proportion to several management terminals connected at the same time according to the proportion of load computing power value to perform computing power resource matching processing.

[0122] Preferably, the operation analysis submodule further includes:

[0123] The idle data search submodule is used to search for associated management terminals that match the terminal service type in the data reuse model according to the terminal service type of the current management terminal, and obtain the idle computing power value of each associated management terminal.

[0124] The idle matching judgment submodule is used to calculate the sum of the idle computing power values ​​of all associated management terminals according to the idle computing power value, and to judge whether the sum of the idle computing power values ​​meets the operating requirements of the sum of the load computing power values.

[0125] The call adjustment submodule is used to calculate the resource call routing hop count between each associated management terminal and the current management terminal, and adjust the computing power call order of the idle computing power resources according to the resource call routing hop count.

[0126] The computing power compensation submodule is used to call the idle computing power resources of each associated management terminal in turn according to the computing power call order to perform computing power resource compensation processing on the current management terminal.

[0127] Preferably, the idle matching judgment submodule further includes:

[0128] The progress analysis unit is used to obtain the current running business progress of each associated management terminal if not, and analyze the expired release computing power and computing power release time node of the associated management terminal according to the current running business progress.

[0129] The expired resource processing unit is used to optimize the computing power calling sequence of the associated management terminal according to the computing power release time node, and call the corresponding expired released computing power according to the optimized computing power calling sequence to perform computing power resource compensation processing on the current management terminal.

[0130] The data reuse model calls the computing resources of the current management terminal through formula (2), which is as follows:

[0131] (2);

[0132] in, Indicates the current idle computing resource value of the management cloud. Represents the total load computing power value in the data reuse model. Indicates the load computing power value of the current management terminal. It means managing the remaining computing resources in the cloud. Indicates the idle computing power value of the associated management terminal. Indicates the number of associated management terminals corresponding to the sum of the idle computing power values ​​of the associated management terminals required to meet the computing power resource compensation. The number of associated management terminals corresponding to the expired released computing power required to meet the computing power resource compensation, Indicates the expired released computing power value corresponding to each computing power release time node.

[0133] Preferably, the data conversion module specifically includes:

[0134] The classification submodule is used to obtain the management function of each management terminal of the enterprise and classify the business of the management terminal according to the management function.

[0135] The authority division submodule is used to plan the business scope of each business node in the current management terminal according to the business classification result, and mark the business management authority of each business node according to the planned business scope.

[0136] The data conversion submodule is used to convert the data format of the office data of the management terminal by taking the business classification and business management authority as data format prefixes, and generate enterprise office data in which the business classification, business management authority and office data are sequentially associated.

[0137] For the specific limitations of the office data management system based on edge computing, please refer to the limitations of the office data management method based on edge computing above, which will not be repeated here. Each module in the above-mentioned office data management system based on edge computing can be implemented in whole or in part through software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0138] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 7 As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store intermediate files in the process of office data processing. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, an office data management method based on edge computing is implemented.

[0139] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned office data management method based on edge computing are implemented.

[0140] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0141] Those skilled in the art will clearly understand that for the sake of convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above.

[0142] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. An office data management method based on edge computing, characterized in that: include: Obtain the office data of each management terminal of the enterprise and convert the data format, convert the office data of each management terminal into enterprise office data in a unified data format, and store it in the management cloud; Associating the terminal business association relationship between the enterprise office data related to each terminal business, and constructing a data reuse model between the management cloud and a plurality of management terminals according to the terminal business association relationship; Calculate the load computing power value of each management terminal, input the load computing power value into the data reuse model, and perform computing power resource matching processing on each management terminal; Based on the computing resource matching results, the computing resources of the management cloud are called to coordinate allocation to all management terminals, and the terminal services of each management terminal are processed according to the resource allocation results; The calculation of the load computing power value of each management terminal specifically includes: The load computing power value of each management terminal is calculated by formula (1), which is as follows: （1）； in, Indicates the load computing power value of the management terminal, n indicates the number of connected loads of the current management terminal, Indicates the load factor of the current management terminal. Indicates the node load value of each business node of the management terminal. Indicates the terminal load value of the management terminal. Indicates the resource idle value of the management terminal. Indicates the sum of the computing power required for each business of the current management terminal. The number of routing hops between the business node and the management cloud; The step of inputting the load computing power value into the data reuse model and performing computing power resource matching processing on each management terminal specifically includes: Calculate the sum of the load computing power values ​​input into the data reuse model at the same time and the remaining computing power resources of the management cloud; According to the data reuse model, determining whether the remaining computing power resources meet the operation requirements of the total load computing power value; If yes, then calculate the load computing power value ratio of the newly connected loads connected to the management cloud at the same time according to the load computing power value; According to the proportion of the load computing power value, the remaining computing power resources are proportionally distributed to several management terminals connected at the same time for computing power resource matching processing; Wherein, judging whether the remaining computing power resources meet the operation requirement of the total load computing power value according to the data reuse model further includes: If not, searching for an associated management terminal that matches the terminal service type in the data reuse model according to the terminal service type of the current management terminal, and obtaining the idle computing power value of each associated management terminal; According to the computing power idle value, calculate the sum of the computing power idle values ​​of all associated management terminals, and determine whether the sum of the computing power idle values ​​meets the operation requirement of the sum of the load computing power value; If yes, then calculating the number of resource call routing hops between each associated management terminal and the current management terminal, and adjusting the computing power calling order of the idle computing power resources according to the number of resource call routing hops; The idle computing resources of each associated management terminal are called in turn according to the computing power calling order to perform computing power resource compensation processing on the current management terminal.

2. The office data management method based on edge computing according to claim 1, characterized in that: The calculating the sum of idle computing power values ​​of each associated management terminal and judging whether the sum of idle computing power values ​​meets the operation requirement of the sum of load computing power values ​​also includes: If not, then obtaining the current running business progress of each of the associated management terminals, and analyzing the expiration release computing power and computing power release time nodes of the associated management terminals according to the current running business progress; Optimizing the computing power calling sequence of the associated management terminal according to the computing power release time node, and calling the corresponding expired released computing power according to the optimized computing power calling sequence to perform computing power resource compensation processing on the current management terminal; The data reuse model calls the computing resources of the current management terminal through formula (2), which is as follows: （2）； in, Indicates the current idle computing resource value of the management cloud. Represents the total load computing power value in the data reuse model. Indicates the load computing power value of the current management terminal. It means managing the remaining computing resources in the cloud. Indicates the idle computing power value of the associated management terminal. Indicates the number of associated management terminals corresponding to the sum of the idle computing power values ​​of the associated management terminals required to meet the computing power resource compensation. The number of associated management terminals corresponding to the expired released computing power required to meet the computing power resource compensation, Indicates the expired released computing power value corresponding to each computing power release time node.

3. The office data management method based on edge computing according to claim 1, characterized in that: The obtaining of office data of each management terminal of the enterprise and performing data format conversion to convert the office data of each management terminal into enterprise office data in a unified data format specifically includes: Obtaining the management function of each management terminal of the enterprise, and classifying the business of the management terminal according to the management function; Plan the business scope of each business node in the current management terminal according to the business classification results, and mark the business management authority of each business node according to the planned business scope; The business classification and the business management authority are used as data format prefixes, and the data format of the office data of the management terminal is converted to generate enterprise office data in which the business classification, business management authority and office data are sequentially associated.

4. An office data management system based on edge computing, characterized in that: include: The data conversion module is used to obtain the office data of each management terminal of the enterprise and convert the data format, convert the office data of each management terminal into enterprise office data in a unified data format, and store it in the management cloud; A model building module, used to associate the terminal business association relationship between the enterprise office data related to each terminal business, and build a data reuse model between the management cloud and a plurality of management terminals according to the terminal business association relationship; A resource matching module, used to calculate the load computing power value of each management terminal, input the load computing power value into the data reuse model, and perform computing power resource matching processing on each management terminal; The business processing module is used to call the computing resources of the management cloud to coordinate allocation to all management terminals according to the computing resource matching results, and process the terminal business of each management terminal according to the resource allocation results; The calculation of the load computing power value of each management terminal specifically includes: The load computing power value of each management terminal is calculated by formula (1), which is as follows: （1）； in, Indicates the load computing power value of the management terminal, n indicates the number of connected loads of the current management terminal, Indicates the load factor of the current management terminal. Indicates the node load value of each business node of the management terminal. Indicates the terminal load value of the management terminal. Indicates the resource idle value of the management terminal. Indicates the sum of the computing power required for each business of the current management terminal. The number of routing hops between the business node and the management cloud; The step of inputting the load computing power value into the data reuse model and performing computing power resource matching processing on each management terminal specifically includes: A data calculation submodule, used to calculate the sum of the load computing power values ​​input into the data reuse model at the same time and the remaining computing power resources of the management cloud; An operation analysis submodule, used to determine whether the remaining computing power resources meet the operation requirements of the total load computing power value according to the data reuse model; a proportion calculation submodule, for calculating the proportion of the load computing power value of the newly connected load connected to the management cloud at the same time according to the load computing power value; A resource matching submodule is used to distribute the remaining computing power resources in proportion to several management terminals connected at the same time to perform computing power resource matching processing according to the proportion of the load computing power value; Wherein, judging whether the remaining computing power resources meet the operation requirement of the total load computing power value according to the data reuse model further includes: an idle data search submodule, for searching, if not, in the data reuse model for an associated management terminal that matches the terminal service type according to the terminal service type of the current management terminal, and obtaining a computing power idle value of each associated management terminal; An idle matching judgment submodule, used to calculate the sum of the idle computing power values ​​of all associated management terminals according to the idle computing power value, and judge whether the sum of the idle computing power values ​​meets the operation requirement of the sum of the load computing power value; A call adjustment submodule, configured to calculate the number of resource call routing hops between each associated management terminal and the current management terminal, and adjust the computing power call order of the idle computing power resources according to the number of resource call routing hops; The computing power compensation submodule is used to call the idle computing power resources of each associated management terminal in turn according to the computing power call order to perform computing power resource compensation processing on the current management terminal.

5. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the office data management method based on edge computing as described in any one of claims 1 to 3 are implemented.

6. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the office data management method based on edge computing as described in any one of claims 1 to 3 are implemented.

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