Real estate registration service system construction method based on multi-tenant cloud architecture mode

Abstract

The invention relates to the technical field of resource sharing, in particular to a real estate registration service system construction method based on a multi-tenant cloud architecture mode. The method comprises the following steps: based on a unified data structure, ensuring the consistency and compatibility of data of each tenant, and promoting data sharing and exchange among the tenants; province, city and county real estate registration departments are divided into different tenants, the jurisdiction range and service authority of the tenants are defined, and data isolation among the tenants is ensured through a role-based access control mechanism; a data partition strategy is adopted, unique voucher codes are distributed for registration information of different tenants, and partition storage is carried out in a shared data pool according to the voucher codes; the method comprises the following steps: collecting real estate registration approval cases, storing the cases into a case library, establishing a monitoring index system containing approval workflow node processing time and circulation time, setting an abnormal threshold, monitoring data in real time, and triggering an early warning notification when the data exceed the threshold.

Description

Technical Field

[0001] The present invention relates to the technical field of resource sharing, and particularly to a method for constructing a real estate registration business system based on a multi-tenant cloud architecture mode. Background Art

[0002] Compared with the traditional B / S architecture distributed deployment mode of the real estate registration system, the multi-tenant cloud platform architecture mode has the advantages of rapid application deployment, supporting a unified technical architecture for real estate registration, unified business processes, and full administrative region coverage. However, the traditional B / S architecture distributed deployment mode of the real estate registration system has the following disadvantages: The system architecture is huge and the provincial-wide distributed deployment is too scattered, which is not conducive to rapid replication and deployment; The distributed deployment system derives extended database field structures and business data interfaces, which is not conducive to the unified coverage of the technical architecture and business processes for the same type of real estate registration business across the province; The distributed deployment system requires separate docking for horizontal and vertical data sharing and exchange, which is not conducive to business expansion; Real estate registration information belongs to sensitive data, and decentralized management cannot guarantee capital investment and ensure the security of data information, which is not conducive to the information security management of real estate registration. Summary of the Invention

[0003] The present invention provides a method for constructing a real estate registration business system based on a multi-tenant cloud architecture mode for the technical problems existing in the prior art.

[0004] The technical solution of the present invention to solve the above technical problems is as follows: A method for constructing a real estate registration business system based on a multi-tenant cloud architecture mode, including the following steps:

[0005] S101: Based on a unified data structure, ensure the consistency and compatibility of tenant data, facilitate data sharing and data exchange among tenants;

[0006] S102: Divide the real estate registration departments at the provincial, municipal, and county levels as tenants, clarify the jurisdiction and business permissions of each tenant, and based on the role-based access control mechanism, ensure data isolation between tenants, define the roles of provincial administrators, municipal administrators, and county administrators, set the business permissions of each role, and allocate the total role weight according to the business permissions. The specific calculation formula for the total role weight is as follows:

[0007] P county =W view ×n view +W modify ×n modify

[0008] Wherein, P county represents the total role weight, W view represents the data permission weight, and n viewIndicates the number of viewing permissions of the role, W modify Indicates the data permission weight, n modify Indicates the number of modification permissions of the role;

[0009] S103: adopting a data partitioning strategy, assigning a credential code to the registration information of different tenants, and partitioning and storing the data in a shared data pool according to the credential code;

[0010] S104: Collect real estate registration approval cases and store them in the case library, establish a monitoring indicator system, cover the node processing time of the approval workflow and the flow time between nodes, and set an abnormal threshold. When the monitoring data exceeds the threshold, trigger an early warning notification; monitor the node processing time and node flow time in the approval workflow in real time, and compare them with the corresponding abnormal threshold. For county-level tenants, set the abnormal threshold to θ light =T transhold , for city-level tenants, the anomaly threshold is set to θ moderate =2×θ light , for provincial tenants, the abnormal threshold is set to θ severe =3×θ light , Based on the above content, the specific formula for abnormal state judgment is as follows:

[0011]

[0012] When a minor anomaly is triggered, an early warning notification is sent to the current tenant. The notification content includes the abnormal node name, processing time, flow time and abnormal type information. When a moderate anomaly is triggered, a notification is sent to the current tenant and the next-level supervisory unit, including complete approval business information, abnormal data and preliminary risk situation information. When a severe anomaly is triggered, an early warning notification is sent to both the current tenant and the highest-level supervisory unit.

[0013] As a further technical solution of the present invention, in step S101, a shared data pool is established in the cloud platform to integrate the transmission data associated with the tenants in several transmission paths; before data transmission, several transmission paths add random noise to the original data to ensure the privacy and security of the data; for data involving tenant identity information in the shared data, the data containing tenant identity information in the original data is marked as 0, the 0 elements in the data set are deleted, the retained data is generated into a parameter data set, and the finally generated parameter data set is transmitted to the shared data set; an API is configured to cover all aspects of the tenant's real estate registration business, including data query and business operations.

[0014] As a further technical solution of the present invention, in step S102:

[0015] (1) The jurisdiction of provincial-level tenants covers the entire province. Their business authorities include viewing the statistical information of real estate registration data across the province, formulating provincial-level real estate registration policies, and supervising the business execution of lower-level tenants.

[0016] (2) The jurisdiction of municipal-level tenants is within the administrative region of the city. They are responsible for real estate registration business within the administrative region of the city, restricting the access rights of municipal-level tenants to real estate registration data of other cities or municipal administrative divisions. Their business authorities include summarizing and analyzing the real estate registration data of the city, approving the real estate registration business of the city, coordinating the real estate registration business between the city and surrounding districts and cities, and inputting and updating the detailed information of real estate registration in the city.

[0017] (3) The jurisdiction of county-level tenants is within the administrative region of the county. They are responsible for real estate registration business within the administrative region of the county, restricting the access rights of county-level tenants to real estate registration data of other counties or municipal administrative divisions. Their business authorities include summarizing and analyzing the real estate registration data of the county, approving the real estate registration business of the county, coordinating the real estate registration business between the county and surrounding counties and districts, and inputting and updating the detailed information of real estate registration in the county.

[0018] (4) Design an authorization mechanism based on role-based access control, define different roles, including provincial-level administrators, municipal-level administrators, and county-level administrators, define the permission weights of different operations based on different roles, and set the permission weight for viewing data as W view = 1, the permission weight for modifying data as W modify = 2, and the data deletion weight as W delete = 3. For each role, allocate the total role weight according to the business authorities.

[0019] When allocating multiple role permissions to a tenant, it is necessary to detect whether the permissions conflict. When the permission sets of two roles are R1 and R2 respectively, where R1 = {P 11 , P 12 ,..., P 1m}, R2 = {P 21 , P 22 ,..., P 2n}, where P ij represents the jth permission of the ith role. Define the permission conflict function C(R1, R2). When there is a permission conflict between two roles, then C(R1, R2) = 1; when there is no permission conflict between two roles, C(R1, R2) = 0.

[0020] As a further technical solution of the present invention, in step S103, the tenant applies for registration to the shared pool and fills in the license information of the tenant; after completing the license information registration link, an electronic license generation program is triggered to automatically fill in relevant data to generate an electronic license; the server of the shared pool transmits the electronic license of the tenant to the qualification certification center, and the qualification certification center conducts a comparison and review based on the transmitted electronic license of the tenant, passes the compliant tenants, and rejects the registration of non-compliant tenants; after the compliant tenant is successfully authenticated, the qualification certification center assigns an unchangeable registration voucher code Vou to the tenant after successful authentication. er Adopt the tenant's registration voucher code Vou er Data partitioning method, using the registration voucher code Vou er As the partitioning key for data storage, used to determine the partitioning location of the tenant's data storage; the tenant sets the account name and password information in the shared data pool according to the registration voucher code Vou er The server of the shared data pool transmits the electronic license of the tenant to the qualification certification center, and the qualification certification center issues a digital certificate and signature key information to the successfully registered tenant, generates a unique corresponding digital signature public key Pub and private key Pri for the tenant, and generates a digital signature public key Pub adc And signature private key Pri adc ; The private key is used when the tenant and the server of the shared data pool sign the ciphertext data, and the public key is used when the tenant and the server of the shared data pool perform signature verification on the received ciphertext data; when other departments call the shared interface to obtain the electronic license information, they authenticate their identities by providing the digital signature private key Pri, and after passing the verification, they can obtain the electronic license information of the tenant.

[0021] In step S104, collect the real estate registration approval cases in the historical data, including successful cases and failed cases. Each case includes applicant information, real estate information, approval process information, and approval results, and store these cases in the case library. When receiving a new approval business, calculate the similarity between the new business and each case in the case library, calculate the similarity according to the characteristics of the business data, and the feature vector of the new business is X=(x 1 ,x 2 ,...,x 3 ), and the feature vector of the case in the case library is Y=(y 1 ,y 2 ,...,y n ).

[0022] As a further technical solution of the present invention, the similarity calculation formula is as follows:

[0023]

[0024] Among them, S represents the similarity, and x i represents the i-th eigenvalue in the feature vector of the new service, and y i represents the i-th eigenvalue in the feature vector of a certain case in the case library. n represents the number of dimensions used to measure business features; a monitoring index system is established to monitor each approval workflow, including the processing time of each node and the transfer time between nodes.

[0025] As a further technical solution of the present invention, a start time and an end time are set for each approval workflow node, and the node processing duration is calculated as one of the monitoring indexes. The start time of the approval workflow is recorded as the start timestamp t start , and the end time of the approval workflow is recorded as the end timestamp t end . The calculation formula for the node processing time is as follows:

[0026] T process = t start - t end

[0027] Among them, T process represents the node processing time. In the approval workflow, when a node finishes processing and transfers the approval data to the next node, the end timestamp t prew_end of the previous node and the timestamp t next_start when the next node receives the data are recorded. The calculation formula for the transfer time between nodes is as follows:

[0028] T transfer = t next_start - t prew_end

[0029] Among them, T transfer represents the transfer time between nodes. The abnormal threshold of the node processing time is set to 2 times the average processing time, that is, the calculation formula for the abnormal threshold is as follows:

[0030] T transhold = 2 × T process

[0031] Among them, T transhold represents the abnormal threshold. When monitoring the approval workflow, when new monitoring data enters, the node processing time and the node transfer time in the approval workflow are monitored in real time, and compared with the corresponding abnormal threshold. Different abnormal thresholds are set according to the tenant type; when the abnormal threshold is exceeded, a warning notice is triggered. A link is set for each warning message, and after clicking the link, it jumps to the abnormal handling page. In the abnormal handling page, information related to the abnormality is obtained from the data pool.

[0032] The beneficial effects of the present invention are as follows: The advantages of adopting multi-tenant technology in the cloud environment are obvious. First, it gives play to the scale effect and reduces the usage cost of the cloud platform. The cloud platform can be flexibly expanded to achieve the long-tail effect at a relatively low cost. Second, tenants can make more full use of the overall dynamic infrastructure provided by the natural resource cloud, flexibly allocate resources, and meet the needs during the business peak period without separately deploying exclusive virtualized resource pools. Third, it improves the technical application delivery ability of application programs. Through versioned batch deployment, rapid iteration and release can be achieved to quickly respond to the needs of business departments. Fourth, it reduces the average user operation and maintenance cost of the data center. After adopting multi-tenant technology, only one set of application systems and one database instance need to be centrally deployed, greatly reducing the maintenance overhead of operation and maintenance and software technical support personnel. By adopting a data partitioning strategy, sensitive data of different tenants is partitioned and stored in the data pool according to factors such as tenant registration credential codes, realizing data isolation and security guarantee. At the same time, a reasonable partitioning design can improve the storage and query performance of data and avoid data access hotspots and conflicts. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 is a flowchart of the present invention; DETAILED DESCRIPTION OF THE EMBODIMENTS

[0034] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative efforts shall fall within the protection scope of the present application.

[0035] In the description of the present application, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of the described features. In the description of the present application, "a plurality of" means two or more unless otherwise specifically defined.

[0036] In the description of the present application, the term "for example" is used to mean "serving as an example, illustration, or explanation". Any embodiment described in the present application as "for example" is not necessarily to be construed as more preferred or advantageous than other embodiments. The following description is provided to enable any person skilled in the art to implement and use the present invention. In the following description, details are set forth for purposes of explanation. It should be understood that those of ordinary skill in the art can recognize that the present invention can be implemented without the use of these specific details. In other instances, well-known structures and processes are not elaborated in detail to avoid obscuring the description of the present invention with unnecessary details. Therefore, the present invention is not intended to be limited to the embodiments shown, but rather to be in line with the broadest scope consistent with the principles and features disclosed in the present application.

[0037] As Figure 1 , this embodiment provides: a method for constructing a real estate registration business system based on a multi-tenant cloud architecture model, specifically including the following steps:

[0038] S101. Based on a unified data structure, ensure the consistency and compatibility of tenant data, facilitating data sharing and data exchange among tenants;

[0039] Furthermore, establish a shared data pool in the cloud platform, integrate the transmission data associated with tenants in several transmission paths. Before data transmission, several transmission paths add random noise to the original data to ensure the privacy and security of the data; for the data in the shared data that involves tenant identity information, mark the data with tenant identity information in the original data as 0, delete the 0 elements in the dataset, generate a parameter dataset from the remaining data, and transmit the finally generated parameter dataset to the shared dataset. Configure an API that covers all aspects of the real estate registration business of tenants, including data query and business operations.

[0040] S102. Divide the real estate registration departments at the provincial, municipal, and county levels as tenants, clarify the jurisdiction and business authorities of each tenant, and based on the role-based access control mechanism, ensure data isolation between tenants. Define the roles of provincial administrators, municipal administrators, and county administrators, and set the business authorities of each role;

[0041] Furthermore, the jurisdiction scope of provincial tenants is the whole province. Their business authorities include viewing the statistical information of real estate registration data across the province, formulating provincial real estate registration policies, and supervising the business execution of lower-level tenants. The jurisdiction scope of municipal tenants is the administrative area of the city, responsible for real estate registration business within the administrative area of the city. The access to real estate registration data of other cities or municipal administrative divisions is restricted for municipal tenants. Their business authorities include summarizing and analyzing real estate registration data of the city, approving real estate registration business of the city, coordinating real estate registration business between the city and surrounding districts and cities, inputting and updating detailed real estate registration information of the city. The jurisdiction scope of county-level tenants is the administrative area of the county, responsible for real estate registration business within the administrative area of the county. The access to real estate registration data of other counties or municipal administrative divisions is restricted for county-level tenants. Their business authorities include summarizing and analyzing real estate registration data of the county, approving real estate registration business of the county, coordinating real estate registration business between the county and surrounding counties and districts, inputting and updating detailed real estate registration information of the county. Design an authorization mechanism based on role-based access control, define different roles, including provincial administrators, municipal administrators, and county-level administrators, define the permission weights of different operations based on different roles, and set the data viewing permission weight W view = 1, modify the data permission weight W modify = 2, delete the data weight as W delete = 3, for each role, allocate the total role weight according to the business authorities. The specific calculation formula for the total role weight is as follows:

[0042] P county = W view × n view + W modify × n modify

[0043] Among them, P county represents the total role weight, n view represents the number of viewing permissions of the role, n modify represents the number of modification permissions of the role. When multiple role permissions are assigned to a tenant, it is necessary to detect whether the permissions conflict. When the permission sets of two roles are R1 and R2 respectively, where R1 = {P 11 , P 12 ,..., P 1m}, R2 = {P 21 , P 22 ,..., P 2n}, where P ij represents the jth permission of the ith role. Define the permission conflict function C(R1, R2). When there is a permission conflict between two roles, then C(R1, R2) = 1. When there is no permission conflict between two roles, C(R1, R2) = 0.

[0044] S103. Adopt a data partitioning strategy to assign a voucher code to the registration information of different tenants, and partition and store the data in the shared data pool according to this voucher code.

[0045] Further, the tenant applies for registration in the shared pool and fills in the license information of the tenant. When the license information registration link is completed, the electronic license generation program is triggered to automatically fill in relevant data to generate the electronic license. The server of the shared pool transmits the tenant's electronic license to the qualification certification center. The qualification certification center compares according to the transmitted tenant's electronic license, passes the compliant tenants, rejects the registration of non-compliant tenants. After the compliant tenant is successfully authenticated, the qualification certification center assigns an unchangeable registration voucher code Vou er , and adopt the tenant's registration voucher code Vou er data partitioning method, and use the registration voucher code Vou er as the partition key for data storage to determine the partition location of the tenant's data storage. The tenant sets the account name and password information in the shared data pool according to the registration voucher code Vou er . The server of the shared data pool transmits the tenant's electronic license to the qualification certification center. The qualification certification center issues a digital certificate and signature key information to the registered tenant, generates a unique corresponding digital signature public key Pub and private key Pri for the tenant, and generates a digital signature public key Pub adc and signature private key Pri adc for the server of the shared data pool. The private key is used when the tenant and the server of the shared data pool sign the ciphertext data, and the public key is used when the tenant and the server of the shared data pool perform signature verification on the received ciphertext data. When other departments call the shared interface to obtain the electronic license information, they perform identity verification by providing the digital signature private key Pri. After the verification is passed, they can obtain the electronic license information of the tenant.

[0046] S104. Collect real estate registration approval cases and store them in the case library, establish a monitoring index system covering the node processing time and the transfer time between nodes of the approval workflow, and set an exception threshold to trigger a warning notice when the monitored data exceeds the threshold.

[0047] Further, collect real estate registration approval cases in historical data, including successful cases and failed cases. Each case includes applicant information, real estate information, approval process information, and approval results. Store these cases in the case library. When a new approval business is received, calculate the similarity between the new business and each case in the case library, and calculate the similarity according to the characteristics of the business data. The feature vector of the new business is X=(x 1 ,x 2 ,...,x 3), the eigenvector of the case in the case base is Y = (y 1 , y 2 ,..., y n ), then the similarity calculation formula is as follows:

[0048]

[0049] Among them, S represents similarity, x i represents the i-th eigenvalue in the eigenvector of the new service, y i represents the i-th eigenvalue in the eigenvector of a certain case in the case base, n represents the number of dimensions used to measure business characteristics, establish a monitoring index system, track and evaluate the efficiency and quality of the approval workflow in real time, monitor each approval workflow, including the processing time of each node and the transfer time between nodes, set the start time and end time for each approval workflow node, calculate the node processing duration as one of the monitoring indicators, record the start time of the approval workflow as the start timestamp t start , record the end time of the approval workflow as the end timestamp t end , and the calculation formula for the node processing time is as follows:

[0050] T process = t start - t end

[0051] Among them, T process represents the node processing time. In the approval workflow, when a node finishes processing and transfers the approval data to the next node, record the end timestamp t prew_end of the previous node and the timestamp t next_start when the next node receives the data. The calculation formula for the transfer time between nodes is as follows:

[0052] T transfer = t next_start - t prew_end

[0053] Among them, T transfer represents the transfer time between nodes. Set the abnormal threshold of the node processing time to 2 times the average processing time, that is, the calculation formula for the abnormal threshold is as follows:

[0054] T transhold = 2 × T process

[0055] Among them, T transholdDenote the exception threshold. When monitoring the approval workflow, when new monitoring data enters, the node processing time and node transfer time in the approval workflow are monitored in real time and compared with the corresponding exception threshold. Different exception thresholds are set according to the tenant type. For county-level tenants, the exception threshold is set to θ light = T transhold , for city-level tenants, the exception threshold is set to θ moderate = 2×θ light , for provincial-level tenants, the exception threshold is set to θ severe = 3×θ light , based on the above, the specific formula for exception status judgment is as follows:

[0056]

[0057] When a mild exception is triggered, a warning notice is sent to the current tenant. The notice content includes the name of the abnormal node, processing time, transfer time, and abnormal type information. When a moderate exception is triggered, a notice is sent to the current tenant and the superior competent unit, including the complete approval business information, abnormal data, and preliminary risk situation information. When a severe exception is triggered, a warning notice is sent to the current tenant and the highest-level competent department at the same time. A link is set for each warning message, and after clicking the link, it jumps to the exception handling page. In the exception handling page, information related to the exception is obtained from the data pool.

[0058] It should be noted that according to the calculation result of the similarity, the system will find the case most similar to the new business. If the similarity exceeds a certain threshold, such as 0.8, the approval result of this case can be referred to for approval. By combining similar cases, the approval efficiency can be further improved. At the same time, for the approval business processed by referring to similar cases, the system will conduct a correctness review.

[0059] Specifically, for example, standard review conditions are formulated according to classic cases, and selective configuration is carried out according to experience in the case of differences in real estate registration units, so as to optimize the approval process.

[0060] It should be noted that in the above embodiments, the descriptions of each embodiment have their own emphases. For the parts not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0061] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memory, CD-ROM, optical memory, etc.) that contain computer-usable program code.

[0062] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, as well as the combination of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices produce means for implementing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0063] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing devices to work in a specific manner, such that the instructions stored in the computer-readable memory produce a manufactured article including instruction means that implement the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0064] These computer program instructions can also be loaded onto a computer or other programmable data processing devices, such that a series of operation steps are executed on the computer or other programmable devices to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable devices provide steps for implementing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0065] Although the preferred embodiments of the present invention have been described, those skilled in the art can make additional changes and modifications once they learn the basic creative concepts. Therefore, the appended claims are intended to be construed to include the preferred embodiments as well as all changes and modifications falling within the scope of the present invention.

[0066] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention also intends to include these modifications and variations.

Claims

1. A method for constructing a real estate registration business system based on a multi-tenant cloud architecture model, characterized in that: The following steps are involved: S101: Based on a unified data structure, ensure the consistency and compatibility of tenant data, and facilitate data sharing and data exchange among tenants; S102: The real estate registration departments of provinces, cities and counties are divided into tenants, and the jurisdiction and business authority of each tenant are clarified. Based on the role-based access control mechanism, data isolation between tenants is ensured. The roles of provincial administrators, municipal administrators and county administrators are defined, and the business authority of each role is set. The total role weight is allocated according to the business authority. The specific calculation formula for the total role weight is as follows: P county =W view ×n view +W modify ×n modify Among them, P county represents the total weight of roles, W view Indicates the data permission weight, n view Indicates the number of viewing permissions of the role, W modify Indicates the data permission weight, n modify Indicates the number of modification permissions of the role; S103: adopting a data partitioning strategy, assigning a credential code to the registration information of different tenants, and partitioning and storing the data in a shared data pool according to the credential code; S104: Collect real estate registration approval cases and store them in the case library, establish a monitoring indicator system, cover the node processing time of the approval workflow and the flow time between nodes, and set abnormal thresholds. When the monitoring data exceeds the threshold, trigger an early warning notification; Monitor the node processing time and node flow time in the approval workflow in real time, and compare them with the corresponding abnormal threshold. For county-level tenants, the abnormal threshold is set to θ light =T transhold , for city-level tenants, the anomaly threshold is set to θ moderate =2×θ light , for provincial tenants, the abnormal threshold is set to θ severe =3×θ light , Based on the above content, the specific formula for abnormal state judgment is as follows: When a minor anomaly is triggered, an early warning notification is sent to the current tenant. The notification content includes the abnormal node name, processing time, flow time and abnormal type information. When a moderate anomaly is triggered, a notification is sent to the current tenant and the next-level supervisory unit, including complete approval business information, abnormal data and preliminary risk situation information. When a severe anomaly is triggered, an early warning notification is sent to both the current tenant and the highest-level supervisory unit.

2. The method for constructing a real estate registration business system based on a multi-tenant cloud architecture model according to claim 1 is characterized in that: In step S101, a shared data pool is established in the cloud platform to integrate the transmission data associated with the tenants in several transmission paths; before data transmission, several transmission paths add random noise to the original data to ensure the privacy and security of the data; for the data involving the tenant identity information in the shared data, the data with the tenant identity information in the original data is marked as 0, the 0 elements in the data set are deleted, the retained data is used to generate a parameter data set, and the finally generated parameter data set is transmitted to the shared data set; Configure an API that covers all aspects of a tenant's real estate registration business, including data query and business operations.

3. The method for constructing a real estate registration business system based on a multi-tenant cloud architecture model according to claim 1 is characterized in that: In step S102: (1) The jurisdiction of a provincial tenant is the entire province, and the business authority includes viewing the statistical information of real estate registration data in the province, formulating provincial real estate registration policies, and supervising the business execution of subordinate tenants; (2) The jurisdiction of the municipal tenant is the municipal administrative area. The tenant is responsible for the real estate registration business within the municipal administrative area and limits the access rights of the municipal tenant to the real estate registration data of other cities or municipal administrative divisions. The business rights include aggregating and analyzing the real estate registration data of the municipality, approving the real estate registration business of the municipality, coordinating the real estate registration business between the municipality and surrounding districts and cities, and entering and updating the detailed information of the real estate registration of the municipality; (3) The jurisdiction of the county-level tenant is the administrative area of ​​the county. The county-level tenant is responsible for the real estate registration business within the county-level administrative area, and limits the county-level tenant's access to the real estate registration data of other county-level or city-level administrative divisions. The business authority includes summarizing and analyzing the real estate registration data of the county, approving the real estate registration business of the county, coordinating the real estate registration business between the county and surrounding districts and counties, and entering and updating the detailed information of the real estate registration in the county; (4) Design authorization mechanism based on role-based access control, define different roles, including provincial administrators, municipal administrators, and county administrators, define the authority weights of different operations based on different roles, and set the authority weights W for viewing data. view =1, modify data permission weight W modify =2, the weight of deleted data is W delete =3, for each role, the total role weight is allocated according to the business authority.

4. The method for constructing a real estate registration business system based on a multi-tenant cloud architecture model according to claim 3 is characterized in that: When multiple role permissions are assigned to a tenant, it is necessary to detect whether the permissions conflict. When the permission sets of two roles are R1 and R2, R1 = {P 11 , P 12 , ..., P 1m }, R2={P 21 , P 22 , ..., P 2n }, where P ij Represents the jth permission of the ith role, and defines the permission conflict function C(R1, R2). When there is a permission conflict between two roles, C(R1, R2) = 1, and when there is no permission conflict between the two roles, C(R1, R2) = 0.

5. The method for constructing a real estate registration business system based on a multi-tenant cloud architecture model according to claim 1 is characterized in that: In step S103, the tenant applies for registration with the shared pool and fills in the tenant's certificate information; when the certificate information registration link is completed, the electronic certificate generation program is triggered to automatically fill in the relevant data to generate an electronic certificate; the shared pool server transmits the tenant's electronic certificate to the qualification certification center, and the qualification certification center conducts a comparison and review based on the transmitted tenant's electronic certificate, and approves compliant tenants and refuses to register non-compliant tenants; after the compliant tenant is successfully authenticated, the qualification certification center assigns an unchangeable registration voucher code Vou to the successfully authenticated tenant er , using the tenant's registration voucher code Vou er Data partitioning method, register the voucher code Vou er As the partition key of the data storage, it is used to determine the partition location of the tenant's data storage; the tenant registers the data according to the registration credential code Vou er Set the account name and password information in the shared data pool. The server of the shared data pool transmits the tenant's electronic certificate to the Qualification Certification Center. The Qualification Certification Center issues a digital certificate and signature key information to the successfully registered tenant, generates a unique digital signature public key Pub and private key Pri for the tenant, and generates a digital signature public key Pub for the server of the shared data pool. adc And the signature private key Pri adc The private key is used by tenants and servers in the shared data pool to sign ciphertext data, and the public key is used by tenants and servers in the shared data pool to verify the signature of received ciphertext data. When other departments call the shared interface to obtain electronic certificate information, they perform identity authentication by providing the digital signature private key Pri. After the verification is passed, the tenant's electronic certificate information can be obtained.

6. The method for constructing a real estate registration business system based on a multi-tenant cloud architecture model according to claim 1 is characterized in that: In step S104, real estate registration approval cases in historical data are collected, including successful cases and failed cases. Each case contains applicant information, real estate information, approval process information and approval results. These cases are stored in the case library. When a new approval business is received, the similarity between the new business and each case in the case library is calculated. The similarity is calculated based on the characteristics of the business data. The feature vector of the new business is X = (x1, x2, ..., x3), and the feature vector of the case in the case library is Y = (y1, y2, ..., y n ).

7. The method for constructing a real estate registration business system based on a multi-tenant cloud architecture model according to claim 6 is characterized in that: The similarity calculation formula is as follows: Among them, S represents the similarity, x i The i-th eigenvalue in the eigenvector representing the new service, y i represents the i-th eigenvalue in the feature vector of a case in the case library, and n represents the number of dimensions used to measure business characteristics; a monitoring indicator system is established to monitor each approval workflow, including the processing time of each node and the flow time between nodes.

8. The method for constructing a real estate registration business system based on a multi-tenant cloud architecture model according to claim 7 is characterized in that: Set the start time and end time for each approval workflow node, calculate the node processing time as one of the monitoring indicators, and record the start time of the approval workflow as the start timestamp t start , record the end time of the approval workflow as the end timestamp t end , the calculation formula of node processing time is as follows: T process =t start -t end Among them, T process Indicates the node processing time. In the approval workflow, when a node is processed and the approval data is passed to the next node, the end timestamp of the previous node is recorded. prew_end And the timestamp t of the next node receiving the data next_start , the calculation formula of the flow time between nodes is as follows: T transfer =t next_start -t prew_end Among them, T transfer Indicates the flow time between nodes. The abnormal threshold of node processing time is set to twice the average processing time. The calculation formula of the abnormal threshold is as follows: T transhold =2×T process Among them, T transhold Indicates the exception threshold. When monitoring the approval workflow, when new monitoring data enters, the node processing time and node flow time in the approval workflow are monitored in real time, and compared with the corresponding exception threshold. Different exception thresholds are set according to the tenant type. When the exception threshold is exceeded, an early warning notification is triggered. A link is set for each early warning information. Click the link to jump to the exception handling page. On the exception handling page, obtain exception-related information in the data pool.

Images