High-reliability full-life-cycle project intelligent management method and system

Abstract

The invention relates to the technical field of database main and standby node switching, and discloses a high-reliability full-life-cycle project intelligent management method and system, and the method comprises the steps: distributing a distributed database list for a full-life-cycle supply chain user, generating a distributed database switching strategy of a target project management time period, and achieving the intelligent management of a full-life-cycle project. Driving each full-life-cycle supply chain user to execute a first main and standby node switching action, before each unit management time period starts, judging whether a data processing load meets a total service operation load demand, executing a second main and standby node switching action of each unit management time period, and switching the second main and standby nodes in the unit management time period; and finally, enabling each full-life-cycle supply chain user to execute a service data processing action based on the switched main node in each unit management time period. Therefore, intelligent switching management of the main and standby nodes of the distributed database in a supply chain scene is realized, and the matching adaptability between a supply chain user and the database and the reliability and compatibility of the database during actual service operation can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of database master-slave node switching, and in particular to a high-reliability full-lifecycle project intelligent management method and system. Background Art

[0002] The full life cycle project management system based on the supply chain regards the entire process of the supply chain from initial planning to final completion as a project, and uses systematic project management methods to integrate and optimize all aspects of the supply chain (including demand forecasting, supplier selection, procurement, production, warehousing, logistics and transportation, sales delivery, after-sales service and recycling disposal, etc.) to achieve a management system that maximizes supply chain efficiency, minimizes costs and controllable risks.

[0003] Given the large number and wide distribution of different supply chain users within different supply chains, distributed databases are typically used to collect, process, and store business data between supply chain users throughout the supply chain lifecycle. Furthermore, to improve the efficiency and stability of supply chain business data processing, the system typically assigns each supply chain user several candidate database nodes for primary and backup node switching, preventing service interruptions caused by potential overload failures in a single database.

[0004] However, the existing distributed database master-slave node switching method for supply chain users has the following limitations: (1) The candidate database selection for each supply chain user adopts a single factor consideration (such as the distance between the database and the deployment area of ​​the supply chain user), without considering the matching adaptability between the business characteristics of the supply chain user (such as data read and write latency performance, data indexing and processing speed requirements, etc.) and the attribute characteristics of the database (such as deployment location, hardware performance, network bandwidth, etc.), nor considering the differences in the business data processing requirements and parallel impact of several supply chain users in different supply chains, resulting in poor reliability and compatibility of the candidate database assigned to each supply chain user during actual business operation; (2) Users at adjacent positions in the supply chain are usually closely related related supply chain users, and their business data have the characteristics of high-frequency interaction. When executing the master-slave node switching for each supply chain user from the candidate database, not only the data processing load of each database and the business operation load changes of each supply chain user must be considered, but also the convenience of business data interaction between related supply chain users must be considered. This undoubtedly increases the difficulty of managing the master-slave node switching of the distributed database and also affects the operation efficiency of the full life cycle project management system.

[0005] Therefore, how to realize the intelligent switching management of distributed database master and standby nodes in the supply chain scenario, improve the matching adaptability between supply chain users and databases, and the reliability and compatibility of databases during actual business operations, and improve the operating efficiency of the full life cycle project management system, is a technical problem that needs to be solved urgently. Summary of the Invention

[0006] The present invention provides a highly reliable full-life cycle project intelligent management method and system, aiming to solve at least one of the above technical problems.

[0007] To achieve the above objectives, the present invention provides a highly reliable full-lifecycle project intelligent management method, comprising: When project entry information is received, the business attributes of several full-lifecycle supply chain users are extracted and a distributed database list is allocated to the full-lifecycle supply chain users; wherein the distributed database list includes a switchable master node and several backup nodes; Generate a distributed database switching strategy for a target project management period based on the distributed database list and the initial business operation load sequence of each full life cycle supply chain user; Convert the distributed database switching strategy into a master / slave node switching plan for each full lifecycle supply chain user in each unit management period of the target project management period, and execute the first master / slave node switching action in the distributed database list for each full lifecycle supply chain user; Before the start of each unit management period of the target project management period, according to the updated business operation load sequence of each distributed database and each assigned full life cycle supply chain user, the second active / standby node switching action of each full life cycle supply chain user in the distributed database list is executed; In each unit management period of the target project management period, a business data processing action for each unit management period is executed using a master node in the distributed database list.

[0008] Optionally, upon receiving the project entry information, extracting the business attributes of several full life cycle supply chain users and allocating a distributed database list step for the full life cycle supply chain users specifically includes: Upon receiving project entry information, extracting first business attributes of a plurality of full life cycle supply chain users from the project entry information; wherein the first business attribute is configured as a business type; According to the business type, several database requirement characteristics of each full life cycle supply chain user are matched in the business type and database requirement characteristic comparison table, and based on the several database requirement characteristics, a distributed database list is allocated to each full life cycle supply chain user.

[0009] Optionally, based on the plurality of database requirement characteristics, a distributed database list step is allocated to each full life cycle supply chain user, specifically including: Query the database feature set of each distributed database and calculate the matching degree between several database requirement features of each full life cycle supply chain user and the database feature set of each distributed database; Based on the deployment communication distance between each distributed database and each full life cycle supply chain user, the communication delay between each distributed database and each full life cycle supply chain user is estimated, and several candidate distributed databases that meet the communication delay conditions of each full life cycle supply chain user are selected from several distributed databases; According to the matching degree between each distributed database and each full life cycle supply chain user, several candidate distributed databases are ranked, and the top candidate distributed database is used as the main node, and the remaining candidate distributed databases are used as backup nodes; Based on the candidate distributed databases as the master node and several backup nodes, a distributed database list for each full life cycle supply chain user is generated.

[0010] Optionally, based on the distributed database list and the initial business operation load sequence of each full life cycle supply chain user, generating a distributed database switching strategy step for the target project management period specifically includes: Determine the business operation load sequence of the full life cycle supply chain user by utilizing the business data processing requirements of the target project management period uploaded by each full life cycle supply chain user; Based on the business operation load sequence of each full life cycle supply chain user and the data processing load information of the distributed database in the target project management period, considering the business attribute association relationship of each full life cycle supply chain user and the database deployment information of each master node and backup node in the distributed database list, the distributed database switching strategy for the target project management period is generated.

[0011] Optionally, the business data processing requirements of the target project management period uploaded by each full life cycle supply chain user are used to determine the business operation load sequence steps of the full life cycle supply chain user, including: Obtaining the business data processing requirements for the target project management period uploaded by each full lifecycle supply chain user at the initial stage of the project; wherein the business data processing requirements include the business data volume, business data processing operation type, and business data processing operation period during the target project management period; According to the business data processing operation period, the business data volume and business data processing operation type are allocated to each unit management period of the target project management period; Based on the business data volume and business data processing operation type in each unit management period, the business operation load of the full life cycle supply chain users in each unit management period is predicted, and the business operation load sequence of the full life cycle supply chain users is generated.

[0012] Optionally, based on the business operation load sequence of each full life cycle supply chain user and the data processing load information of the distributed database in the target project management period, taking into account the business attribute association relationship of each full life cycle supply chain user and the database deployment information of each primary node and backup node in the distributed database list, the distributed database switching strategy steps for the target project management period are generated, specifically including: Extracting a second business attribute of a plurality of full life cycle supply chain users from the project entry information; wherein the second business attribute is configured as a project supply chain position; According to the project supply chain position of each full life cycle supply chain user, the associated full life cycle supply chain users with business attribute association relationships at the previous and next positions in the project supply chain are extracted from all full life cycle supply chain users; Based on the business operation load sequence of each full life cycle supply chain user and the data processing load information of the distributed database in the target project management period, the business processing database assigned to each unit management period of the target project management period is selected from the distributed database list of each full life cycle supply chain user to solve the distributed database switching strategy, so that when each distributed database is used as the business processing database of the full life cycle supply chain user assigned in each unit management period of the target project management period, the data processing load of each distributed database in each unit management period of the target project management period meets the total business operation load demand of the assigned full life cycle supply chain user as a constraint condition and each full life cycle supply chain user meets the optimization goal of minimizing the sum of deployment distances with the business processing database assigned to the associated full life cycle supply chain user in each unit management period of the target project management period, and the optimization algorithm is used to solve the business processing database assigned to each full life cycle supply chain user in each unit management period of the target project management period; The business processing database assigned to each unit management period of each full life cycle supply chain user in the target project management period is used as the main node, and the remaining distributed databases in the distributed database list are used as standby nodes to generate the distributed database switching strategy for the target project management period.

[0013] Optionally, the distributed database switching strategy is converted into a master / slave node switching plan for each full lifecycle supply chain user in each unit management period during the target project management period, and the first master / slave node switching action steps in the distributed database list of each full lifecycle supply chain user are executed, specifically including: Extracting the distributed database assigned as the master node to each unit management period of the target project management period for each full life cycle supply chain user recorded in the distributed database switching strategy, and generating a master-slave node switching plan including the master node of each unit management period; In each unit management period of the target project management period, each full life cycle supply chain user is controlled to select the distributed database as the master node of the current unit management period in the distributed database list to perform the master-slave node switching action.

[0014] Optionally, before the start of each unit management period in the target project management period, according to the updated business operation load sequence of each distributed database and each assigned full life cycle supply chain user, the second active / standby node switching action steps for each full life cycle supply chain user in the distributed database list are executed, specifically including: Before the start of each unit management period of the target project management period, obtain the business data processing and update requirements of the target project management period uploaded by each full life cycle supply chain user, and determine the business operation load sequence updated by each full life cycle supply chain user based on the business data processing and update requirements; Based on the updated business operation load sequence of each full life cycle supply chain user and the data processing load information of each distributed database, determine whether the data processing load of the current unit management period meets the total business operation load requirements of the assigned full life cycle supply chain user when each distributed database processes business data according to the master node of the current distributed database switching strategy; According to the judgment result, the first master-standby node switching action of the current distributed database switching strategy is selected as the second master-standby node switching action or an updated distributed database switching strategy is used to perform the second master-standby node switching action.

[0015] Optionally, based on the judgment result, selecting the first master-slave node switching action of the current distributed database switching strategy as the second master-slave node switching action or adopting an updated distributed database switching strategy to perform the second master-slave node switching action step specifically includes: If so, the same first master-slave node switching action in the current distributed database switching strategy is used as the second master-slave node switching action, and the master-slave node switching action is executed; If not, based on the business operation load sequence updated by each full life cycle supply chain user, the distributed database switching strategy of the target project management period is regenerated to update the current distributed database switching strategy, and each full life cycle supply chain user in the updated distributed database switching strategy is allocated to the distributed database as the master node in the current unit management period, and the second master-slave node switching action of the current unit management period is determined and the master-slave node switching action is executed.

[0016] In addition, in order to achieve the above objectives, the present invention also provides a highly reliable full-life cycle project intelligent management system, including: A list allocation module is used to extract the business attributes of several full-lifecycle supply chain users upon receiving project input information, and allocate a distributed database list to the full-lifecycle supply chain users; wherein the distributed database list includes a switchable master node and several backup nodes; A strategy generation module, configured to generate a distributed database switching strategy for a target project management period based on the distributed database list and the initial business operation load sequence of each full life cycle supply chain user; A first master-slave node switching module is configured to convert the distributed database switching strategy into a master-slave node switching plan for each full life cycle supply chain user in each unit management period of the target project management period, and execute a first master-slave node switching action for each full life cycle supply chain user in the distributed database list; The second master-slave node switching module is used to execute the second master-slave node switching action for each full life cycle supply chain user in the distributed database list according to the updated business operation load sequence of each distributed database and each assigned full life cycle supply chain user before the start of each unit management period of the target project management period; The business data processing module is used to execute business data processing actions for each unit management period in each unit management period of the target project management period by using the master node in the distributed database list.

[0017] The beneficial effects of the present invention are: a highly reliable full-life cycle project intelligent management method and system is proposed, by allocating a distributed database list to full-life cycle supply chain users, generating a distributed database switching strategy for the target project management period, driving each full-life cycle supply chain user to execute the first master-slave node switching action, and before the start of each unit management period, judging whether the data processing load meets the total business operation load demand, executing the second master-slave node switching action for each unit management period, and finally enabling each full-life cycle supply chain user to execute business data processing actions based on the switched master node in each unit management period. Thus, the present invention realizes the intelligent switching management of distributed database master-slave nodes in the supply chain scenario, which can improve the matching adaptability between supply chain users and databases, as well as the reliability and compatibility of the database during actual business operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 Schematic diagram of a process of a highly reliable full-life cycle project intelligent management method according to an embodiment of the present invention; Figure 2 The figure is a structural diagram of a highly reliable full-life cycle project intelligent management system in an embodiment of the present invention.

[0019] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0020] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0021] The embodiment of the present invention provides a highly reliable full life cycle project intelligent management method, referring to Figure 1 , Figure 1 The figure is a flow chart of a highly reliable full-life cycle project intelligent management method according to an embodiment of the present invention.

[0022] In this embodiment, a highly reliable full-lifecycle project intelligent management method includes: S1: When project entry information is received, business attributes of several full-lifecycle supply chain users are extracted, and a distributed database list is allocated to the full-lifecycle supply chain users; wherein the distributed database list includes a switchable master node and several backup nodes; S2: Generate a distributed database switching strategy for the target project management period based on the distributed database list and the initial business operation load sequence of each full life cycle supply chain user; S3: converting the distributed database switching strategy into a master / slave node switching plan for each full lifecycle supply chain user in each unit management period of the target project management period, and executing a first master / slave node switching action in the distributed database list for each full lifecycle supply chain user; S4: Before the start of each unit management period in the target project management period, according to the updated business operation load sequence of each distributed database and each assigned full life cycle supply chain user, execute the second active / standby node switching action for each full life cycle supply chain user in the distributed database list; S5: In each unit management period of the target project management period, the master node in the distributed database list is used to execute a business data processing action for each unit management period.

[0023] It should be noted that the existing distributed database master-slave node switching method for supply chain users has the following limitations: (1) The candidate database selection for each supply chain user adopts a single factor consideration (such as the distance between the database and the deployment area of ​​the supply chain user), without considering the matching adaptability between the business characteristics of the supply chain user (such as data read and write latency performance, data indexing and processing speed requirements, etc.) and the attribute characteristics of the database (such as deployment location, hardware performance, network bandwidth, etc.), nor considering the differences in business data processing requirements and parallel impacts of several supply chain users in different supply chains, resulting in poor reliability and compatibility of the candidate database assigned to each supply chain user during actual business operation; (2) Users at adjacent positions in the supply chain are usually closely related related supply chain users, and their business data have the characteristics of high-frequency interaction. When executing the master-slave node switching for each supply chain user from the candidate database, not only the data processing load of each database and the business operation load changes of each supply chain user must be considered, but also the convenience of business data interaction between related supply chain users must be considered. This undoubtedly increases the difficulty of managing the master-slave node switching of the distributed database and also affects the operation efficiency of the full life cycle project management system.

[0024] In order to solve the above problems, this embodiment allocates a distributed database list to full life cycle supply chain users, generates a distributed database switching strategy for the target project management period, drives each full life cycle supply chain user to execute the first master-slave node switching action, and before the start of each unit management period, determines whether the data processing load meets the total business operation load demand, executes the second master-slave node switching action for each unit management period, and finally enables each full life cycle supply chain user to execute business data processing actions based on the switched master node in each unit management period. Thus, the present invention realizes the intelligent switching management of distributed database master-slave nodes in the supply chain scenario, which can improve the matching adaptability between supply chain users and databases, as well as the reliability and compatibility of the database during actual business operation.

[0025] In a preferred embodiment, upon receiving project entry information, the steps of extracting business attributes of several full life cycle supply chain users and allocating a distributed database list to the full life cycle supply chain users specifically include: S11: upon receiving project entry information, extracting first business attributes of a plurality of full life cycle supply chain users from the project entry information; wherein the first business attribute is configured as a business type; S12: According to the business type, match several database requirement characteristics of each full life cycle supply chain user in the business type and database requirement characteristic comparison table, and allocate a distributed database list to each full life cycle supply chain user based on the several database requirement characteristics.

[0026] Furthermore, based on the aforementioned database requirement characteristics, a distributed database list step is allocated to each full life cycle supply chain user, specifically including: S121: querying the database feature set of each distributed database, and calculating the matching degree between a number of database demand features of each full life cycle supply chain user and the database feature set of each distributed database; S122: estimating the communication delay between each distributed database and each full life cycle supply chain user based on the deployed communication distance between each distributed database and each full life cycle supply chain user, and selecting several candidate distributed databases from the several distributed databases that meet the communication delay conditions of each full life cycle supply chain user; S123: Rank several candidate distributed databases based on the matching degree between each distributed database and each full life cycle supply chain user, select the top candidate distributed database as the primary node, and the remaining candidate distributed databases as candidate nodes; S124: Based on the candidate distributed databases serving as the master node and several backup nodes, a distributed database list for each full life cycle supply chain user is generated.

[0027] In this embodiment, by considering the database feature set of each distributed database and the database demand characteristics of each full life cycle supply chain user, the matching degree between the two can be measured according to the cosine similarity between the feature words, and then screened based on the communication delay condition and sorted in order from large to small according to the matching degree, so as to determine the main node and alternative node of each full life cycle supply chain user, thereby improving the matching adaptability between the supply chain user and the database and the reliability and compatibility of the database during actual business operation.

[0028] In a preferred embodiment, based on the distributed database list and the initial business operation load sequence of each full life cycle supply chain user, the distributed database switching strategy steps for the target project management period are generated, specifically including: S21: Determine the business operation load sequence of the full life cycle supply chain user by utilizing the business data processing requirements of the target project management period uploaded by each full life cycle supply chain user; S22: Based on the business operation load sequence of each full life cycle supply chain user and the data processing load information of the distributed database in the target project management period, considering the business attribute association relationship of each full life cycle supply chain user and the database deployment information of each master node and backup node in the distributed database list, generate the distributed database switching strategy for the target project management period.

[0029] Furthermore, the business data processing requirements of the target project management period uploaded by each full life cycle supply chain user are used to determine the business operation load sequence steps of the full life cycle supply chain user, including: S211: Obtaining the business data processing requirements for the target project management period uploaded by each full lifecycle supply chain user at the initial stage of the project; wherein the business data processing requirements include the business data volume, business data processing operation type, and business data processing operation period during the target project management period; S212: Allocate the business data volume and the business data processing operation type to each unit management period of the target project management period according to the business data processing operation period; S213: Based on the business data volume and business data processing operation type of each unit management period, predict the business operation load of the full life cycle supply chain user in each unit management period, and generate a business operation load sequence of the full life cycle supply chain user.

[0030] Furthermore, based on the business operation load sequence of each full-lifecycle supply chain user and the data processing load information of the distributed database during the target project management period, the distributed database switching strategy steps for the target project management period are generated by considering the business attribute association relationship of each full-lifecycle supply chain user and the database deployment information of each primary node and backup node in the distributed database list. Specifically, the steps include: S221: extracting a second business attribute of a plurality of full life cycle supply chain users from the project entry information; wherein the second business attribute is configured as a project supply chain position; S222: extracting associated full life cycle supply chain users with business attribute association relationships at the previous and next positions in the project supply chain from all full life cycle supply chain users based on the project supply chain position of each full life cycle supply chain user; S223: Based on the business operation load sequence of each full life cycle supply chain user and the data processing load information of the distributed database in the target project management period, the business processing database assigned to each unit management period of the target project management period is selected from the distributed database list of each full life cycle supply chain user to solve the distributed database switching strategy, so that when each distributed database serves as the business processing database assigned to the full life cycle supply chain user in each unit management period of the target project management period, the data processing load of each distributed database in each unit management period of the target project management period satisfies the total business operation load demand of the assigned full life cycle supply chain user as a constraint condition, and each full life cycle supply chain user satisfies the optimization goal of minimizing the sum of deployment distances to the business processing databases assigned to the associated full life cycle supply chain users in each unit management period of the target project management period, and an optimization algorithm is used to solve the business processing database assigned to each full life cycle supply chain user in each unit management period of the target project management period; S224: The business processing database assigned to each unit management period of each full life cycle supply chain user in the target project management period is used as the primary node, and the remaining distributed databases in the distributed database list are used as backup nodes to generate a distributed database switching strategy for the target project management period.

[0031] In this embodiment, by extracting the business attributes of several full-life cycle supply chain users, a distributed database list is allocated to the full-life cycle supply chain users, and then based on the initial business operation load sequence of each full-life cycle supply chain user, a distributed database switching strategy for the target project management period is generated, driving each full-life cycle supply chain user to execute the first master-slave node switching action for each unit management period. Therefore, by analyzing the business characteristics of the supply chain users and the attribute characteristics of the database, considering the differences in business data processing requirements and parallel impacts of several supply chain users in different supply chains, a distributed database switching strategy is generated that takes into account the business data interaction between related supply chain users, thereby realizing intelligent switching management of distributed database master-slave nodes in the supply chain scenario.

[0032] In a preferred embodiment, the distributed database switching strategy is converted into a master-slave node switching plan for each full life cycle supply chain user in each unit management period of the target project management period, and the first master-slave node switching action steps in the distributed database list of each full life cycle supply chain user are executed, specifically including: S31: extracting the distributed database assigned as the master node to each unit management period of each full life cycle supply chain user in the target project management period, as recorded in the distributed database switching strategy, and generating a master-slave node switching plan including the master node of each unit management period; S32: In each unit management period of the target project management period, control each full life cycle supply chain user to select a distributed database as the master node of the current unit management period in the distributed database list to perform a master-slave node switching action.

[0033] In this embodiment, after obtaining the distributed database switching strategy, each full life cycle supply chain user can be driven to perform the first master-slave node switching action in each unit management period of the target project management period, so that each full life cycle supply chain user can perform business data processing based on the most suitable distributed database allocated to it.

[0034] In a preferred embodiment, before the start of each unit management period of the target project management period, the second active / standby node switching action steps for each full life cycle supply chain user in the distributed database list are executed according to the updated business operation load sequence of each distributed database and each assigned full life cycle supply chain user, specifically including: S41: Before the start of each unit management period of the target project management period, obtain the business data processing and update requirements of the target project management period uploaded by each full life cycle supply chain user, and determine the business operation load sequence updated by each full life cycle supply chain user based on the business data processing and update requirements; S42: Based on the updated business operation load sequence of each full life cycle supply chain user and the data processing load information of each distributed database, determine whether the data processing load of the current unit management period meets the total business operation load demand of the assigned full life cycle supply chain user when each distributed database processes business data according to the master node of the current distributed database switching strategy; S43: According to the judgment result, the first master-slave node switching action of the current distributed database switching strategy is selected as the second master-slave node switching action or an updated distributed database switching strategy is adopted to perform the second master-slave node switching action.

[0035] Furthermore, according to the judgment result, the first master-slave node switching action of the current distributed database switching strategy is selected as the second master-slave node switching action or an updated distributed database switching strategy is adopted to perform the second master-slave node switching action step, specifically including: S431: If yes, use the same first master-slave node switching action in the current distributed database switching strategy as the second master-slave node switching action, and execute the master-slave node switching action; S432: If not, based on the business operation load sequence updated by each full life cycle supply chain user, regenerate the distributed database switching strategy for the target project management period to update the current distributed database switching strategy, and use the distributed database assigned to each full life cycle supply chain user as the master node in the current unit management period in the updated distributed database switching strategy to determine the second master-slave node switching action for the current unit management period and execute the master-slave node switching action.

[0036] In this embodiment, before the start of each unit management period, based on the updated business operation load sequence of each distributed database and each assigned full life cycle supply chain user, it is judged whether the data processing load of the distributed database meets the total business operation load demand of the assigned full life cycle supply chain user, and the second master-slave node switching action of each unit management period is executed according to the judgment result, so that each full life cycle supply chain user can finally perform business data processing actions based on the switched master node in each unit management period. Therefore, the present invention analyzes the business characteristics of the supply chain user and the attribute characteristics of the database, considers the differences in the business data processing requirements and parallel effects of several supply chain users in different supply chains, generates a distributed database switching strategy that takes into account the business data interaction between related supply chain users, drives each full life cycle supply chain user to execute the first master-slave node switching action and the second master-slave node switching action in each unit management period, realizes the intelligent switching management of the distributed database master-slave node in the supply chain scenario, improves the matching adaptability between the supply chain user and the database, and the reliability and compatibility of the database during actual business operation, and improves the operating efficiency of the full life cycle project management system.

[0037] Reference Figure 2 , Figure 2 This is a structural diagram of a high-reliability, full-lifecycle project intelligent management system according to an embodiment of the present invention.

[0038] like Figure 2 As shown, the highly reliable full-lifecycle project intelligent management system proposed in the embodiment of the present invention includes: The list allocation module 10 is used to extract the business attributes of several full life cycle supply chain users upon receiving project input information, and allocate a distributed database list to the full life cycle supply chain users; wherein the distributed database list includes a switchable master node and several backup nodes; A strategy generation module 20 is configured to generate a distributed database switching strategy for a target project management period based on the distributed database list and the initial business operation load sequence of each full life cycle supply chain user; The first master-slave node switching module 30 is configured to convert the distributed database switching strategy into a master-slave node switching plan for each full lifecycle supply chain user in each unit management period of the target project management period, and execute the first master-slave node switching action in the distributed database list for each full lifecycle supply chain user; The second master-slave node switching module 40 is configured to execute a second master-slave node switching action for each full life cycle supply chain user in the distributed database list based on the updated business operation load sequence of each distributed database and each assigned full life cycle supply chain user before the start of each unit management period of the target project management period; The business data processing module 50 is configured to execute business data processing actions for each unit management period in each unit management period of the target project management period by using the master node in the distributed database list.

[0039] Other embodiments or specific implementation methods of the high-reliability full-life cycle project intelligent management system of the present invention can refer to the above-mentioned method embodiments and will not be repeated here.

[0040] It should be understood that, in the description of this specification, reference to terms such as "one embodiment," "another embodiment," "other embodiments," or "first to Nth embodiments" means that the specific features, structures, materials, or characteristics described in conjunction with that embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any appropriate manner in any one or more embodiments or examples.

[0041] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or system comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or system. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or system comprising the element.

[0042] The above are only preferred embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention description and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A highly reliable full life cycle project intelligent management method, characterized by: include: When project entry information is received, the business attributes of several full-lifecycle supply chain users are extracted and a distributed database list is allocated to the full-lifecycle supply chain users; wherein the distributed database list includes a switchable master node and several backup nodes; Generate a distributed database switching strategy for a target project management period based on the distributed database list and the initial business operation load sequence of each full life cycle supply chain user; Convert the distributed database switching strategy into a master / slave node switching plan for each full lifecycle supply chain user in each unit management period of the target project management period, and execute the first master / slave node switching action in the distributed database list for each full lifecycle supply chain user; Before the start of each unit management period of the target project management period, according to the updated business operation load sequence of each distributed database and each assigned full life cycle supply chain user, the second active / standby node switching action of each full life cycle supply chain user in the distributed database list is executed; In each unit management period of the target project management period, a business data processing action for each unit management period is executed using a master node in the distributed database list.

2. The high-reliability full-lifecycle project intelligent management method according to claim 1, characterized in that: When receiving project input information, extract the business attributes of several full life cycle supply chain users and assign distributed database list steps to the full life cycle supply chain users, including: Upon receiving project entry information, extracting first business attributes of a plurality of full life cycle supply chain users from the project entry information; wherein the first business attribute is configured as a business type; According to the business type, several database requirement characteristics of each full life cycle supply chain user are matched in the business type and database requirement characteristic comparison table, and based on the several database requirement characteristics, a distributed database list is allocated to each full life cycle supply chain user.

3. The high-reliability full-lifecycle project intelligent management method according to claim 2, characterized in that: Based on the aforementioned database requirement characteristics, the steps of allocating a distributed database list to each full life cycle supply chain user include: Query the database feature set of each distributed database and calculate the matching degree between several database requirement features of each full life cycle supply chain user and the database feature set of each distributed database; Based on the deployment communication distance between each distributed database and each full life cycle supply chain user, the communication delay between each distributed database and each full life cycle supply chain user is estimated, and several candidate distributed databases that meet the communication delay conditions of each full life cycle supply chain user are selected from several distributed databases; According to the matching degree between each distributed database and each full life cycle supply chain user, several candidate distributed databases are ranked, and the top candidate distributed database is used as the main node, and the remaining candidate distributed databases are used as backup nodes; Based on the candidate distributed databases as the master node and several backup nodes, a distributed database list for each full life cycle supply chain user is generated.

4. The high-reliability full-lifecycle project intelligent management method according to claim 1, characterized in that: Based on the distributed database list and the initial business operation load sequence of each full life cycle supply chain user, the distributed database switching strategy steps for the target project management period are generated, specifically including: Determine the business operation load sequence of the full life cycle supply chain user by utilizing the business data processing requirements of the target project management period uploaded by each full life cycle supply chain user; Based on the business operation load sequence of each full life cycle supply chain user and the data processing load information of the distributed database in the target project management period, considering the business attribute association relationship of each full life cycle supply chain user and the database deployment information of each master node and backup node in the distributed database list, the distributed database switching strategy for the target project management period is generated.

5. The high-reliability full-lifecycle project intelligent management method according to claim 4, characterized in that: Using the business data processing requirements of the target project management period uploaded by each full life cycle supply chain user, the business operation load sequence steps of the full life cycle supply chain user are determined, including: Obtaining the business data processing requirements for the target project management period uploaded by each full lifecycle supply chain user at the initial stage of the project; wherein the business data processing requirements include the business data volume, business data processing operation type, and business data processing operation period during the target project management period; According to the business data processing operation period, the business data volume and business data processing operation type are allocated to each unit management period of the target project management period; Based on the business data volume and business data processing operation type in each unit management period, the business operation load of the full life cycle supply chain users in each unit management period is predicted, and the business operation load sequence of the full life cycle supply chain users is generated.

6. The high-reliability full-lifecycle project intelligent management method according to claim 4, characterized in that: Based on the business operation load sequence of each full-lifecycle supply chain user and the data processing load information of the distributed database during the target project management period, taking into account the business attribute association relationship of each full-lifecycle supply chain user and the database deployment information of each primary node and backup node in the distributed database list, the distributed database switching strategy steps for the target project management period are generated, including: Extracting a second business attribute of a plurality of full life cycle supply chain users from the project entry information; wherein the second business attribute is configured as a project supply chain position; According to the project supply chain position of each full life cycle supply chain user, the associated full life cycle supply chain users with business attribute association relationships at the previous and next positions in the project supply chain are extracted from all full life cycle supply chain users; Based on the business operation load sequence of each full life cycle supply chain user and the data processing load information of the distributed database in the target project management period, the business processing database assigned to each unit management period of the target project management period is selected from the distributed database list of each full life cycle supply chain user to solve the distributed database switching strategy, so that when each distributed database is used as the business processing database of the full life cycle supply chain user assigned in each unit management period of the target project management period, the data processing load of each distributed database in each unit management period of the target project management period meets the total business operation load demand of the assigned full life cycle supply chain user as a constraint condition and each full life cycle supply chain user meets the optimization goal of minimizing the sum of deployment distances with the business processing database assigned to the associated full life cycle supply chain user in each unit management period of the target project management period, and the optimization algorithm is used to solve the business processing database assigned to each full life cycle supply chain user in each unit management period of the target project management period; The business processing database assigned to each unit management period of each full life cycle supply chain user in the target project management period is used as the main node, and the remaining distributed databases in the distributed database list are used as standby nodes to generate the distributed database switching strategy for the target project management period.

7. The high-reliability full-lifecycle project intelligent management method according to claim 1, characterized in that: The distributed database switching strategy is converted into a master / slave node switching plan for each full lifecycle supply chain user in each unit management period of the target project management period, and the first master / slave node switching action steps in the distributed database list of each full lifecycle supply chain user are executed, specifically including: Extracting the distributed database assigned as the master node to each unit management period of the target project management period for each full life cycle supply chain user recorded in the distributed database switching strategy, and generating a master-slave node switching plan including the master node of each unit management period; In each unit management period of the target project management period, each full life cycle supply chain user is controlled to select the distributed database as the master node of the current unit management period in the distributed database list to perform the master-slave node switching action.

8. The high-reliability full-lifecycle project intelligent management method according to claim 1, characterized in that: Before the start of each unit management period in the target project management period, according to the updated business operation load sequence of each distributed database and each assigned full life cycle supply chain user, the second active / standby node switching action steps for each full life cycle supply chain user in the distributed database list are executed, specifically including: Before the start of each unit management period of the target project management period, obtain the business data processing and update requirements of the target project management period uploaded by each full life cycle supply chain user, and determine the business operation load sequence updated by each full life cycle supply chain user based on the business data processing and update requirements; Based on the updated business operation load sequence of each full life cycle supply chain user and the data processing load information of each distributed database, determine whether the data processing load of the current unit management period meets the total business operation load requirements of the assigned full life cycle supply chain user when each distributed database processes business data according to the master node of the current distributed database switching strategy; According to the judgment result, the first master-standby node switching action of the current distributed database switching strategy is selected as the second master-standby node switching action or an updated distributed database switching strategy is used to perform the second master-standby node switching action.

9. The high-reliability full-lifecycle project intelligent management method according to claim 8, characterized in that: According to the judgment result, the first master-slave node switching action of the current distributed database switching strategy is selected as the second master-slave node switching action or an updated distributed database switching strategy is adopted to perform the second master-slave node switching action step, specifically including: If so, the same first master-slave node switching action in the current distributed database switching strategy is used as the second master-slave node switching action, and the master-slave node switching action is executed; If not, based on the business operation load sequence updated by each full life cycle supply chain user, the distributed database switching strategy of the target project management period is regenerated to update the current distributed database switching strategy, and each full life cycle supply chain user in the updated distributed database switching strategy is allocated to the distributed database as the master node in the current unit management period, and the second master-slave node switching action of the current unit management period is determined and the master-slave node switching action is executed.

10. A highly reliable full life cycle project intelligent management system, characterized by: include: A list allocation module is used to extract the business attributes of several full-lifecycle supply chain users upon receiving project input information, and allocate a distributed database list to the full-lifecycle supply chain users; wherein the distributed database list includes a switchable master node and several backup nodes; A strategy generation module, configured to generate a distributed database switching strategy for a target project management period based on the distributed database list and the initial business operation load sequence of each full life cycle supply chain user; A first master-slave node switching module is configured to convert the distributed database switching strategy into a master-slave node switching plan for each full life cycle supply chain user in each unit management period of the target project management period, and execute a first master-slave node switching action for each full life cycle supply chain user in the distributed database list; The second master-slave node switching module is used to execute the second master-slave node switching action for each full life cycle supply chain user in the distributed database list according to the updated business operation load sequence of each distributed database and each assigned full life cycle supply chain user before the start of each unit management period of the target project management period; The business data processing module is used to execute business data processing actions for each unit management period in each unit management period of the target project management period by using the master node in the distributed database list.

Images