Payment service processing method and device based on process engine, equipment and medium

Abstract

The invention relates to the technical field of data processing, can be applied to business system platforms of medical health, financial science and technology and the like, and discloses a payment business processing method based on a process engine, which comprises the following steps: standardizing an input / output interface, packaging business logic into business nodes, and storing the business nodes in a node library. And selecting nodes, configuration information and a connection relationship according to service requirements, and generating a process model. And starting the process engine, and converting the process model to obtain a process instance. And extracting node information and a connection relationship, scheduling node execution, obtaining real-time data, and generating a dynamic adjustment decision. And according to the decision and the real-time data, adjusting a process instance execution path and node parameters, scheduling node execution, completing payment service processing, and storing process instance information in a historical record library. By standardizing the interface, packaging the service nodes, generating the process model and dynamically adjusting the execution path and parameters, the payment service processing is efficiently completed, the flexibility and efficiency are improved, and the process information is convenient to store and trace.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a payment business processing method, device, equipment and storage medium based on a process engine. Background Art

[0002] While business process management and workflow engine technologies are widely used in payment systems, existing technologies have numerous shortcomings. Mainstream workflow engines such as Apache Activiti and Camunda, while supporting graphical configuration, are designed for general business processes and are not optimized for the high real-time, high security, and complex node combinations required by payment systems. Some payment platforms, such as Alipay and WeChat Pay, utilize proprietary or third-party process management tools, but these tools are highly coupled, with fixed node combinations that make dynamic adjustments difficult. Some payment systems modularize business logic but lack standardized interfaces, resulting in strong coupling between nodes and inflexible configuration.

[0003] In existing technologies, business logic node combinations are fixed, requiring new nodes to be completely redesigned and integrated, resulting in long development cycles and high costs. Adjusting business processes requires redeployment or a system restart, preventing dynamic adjustments during runtime and making it difficult to meet requirements such as real-time risk assessment. Node interfaces are not standardized, with poor encapsulation and reusability, further exacerbating coupling. Some process engines experience performance bottlenecks when handling complex business processes, making it difficult to meet the high concurrency requirements of payment systems. Furthermore, process configuration tools are unfriendly and lack an intuitive visual interface. Users must define processes through code or complex configuration files, reducing the system's ease of use.

[0004] In the healthcare sector, existing workflow engines and process management tools have numerous shortcomings and are unable to meet the complex needs of healthcare services. Healthcare operations, such as patient treatment processes and drug procurement processes, require dynamic adjustments based on factors such as patient conditions and drug availability. However, the fixed node combinations of existing workflow engines make it difficult to achieve fully flexible dynamic adjustments, which can impact patient treatment outcomes and the efficiency of healthcare services. Healthcare services require dynamic adjustments to business processes based on real-time patient examination results or changes in conditions, but existing systems are often unable to perform these adjustments during runtime, requiring re-deployment or system restarts. This can lead to delays in patient treatment and impact the timeliness and continuity of healthcare services. During peak hours, healthcare systems (such as hospital registration systems and examination scheduling systems) may face high concurrent access. Some existing process engines may experience performance bottlenecks when dynamically loading and executing complex business processes, resulting in slow system responses or even crashes, disrupting the normal operation of healthcare services. Healthcare staff may lack technical familiarity, and some process configuration tools lack intuitive visual interfaces, requiring process definition through code or complex configuration files. This increases operational difficulty, reduces the system's usability and maintainability, and may impact the normal operation and management efficiency of healthcare services. Healthcare services involve collaboration across multiple departments and systems, such as hospital information systems (HIS), laboratory information systems (LIS), and photographic imaging systems (PACS). Existing workflow engines and process management tools lack unified, standardized interfaces for business logic nodes, resulting in strong node coupling and difficulty in achieving free combination and flexible, dynamic configuration. This can lead to difficulties in system integration and poor information sharing, impacting the overall collaborative efficiency of healthcare services.

[0005] In the FinTech sector, existing workflow engines and process management tools suffer from numerous deficiencies, making them unable to meet the complex demands of financial services. These requirements are complex and constantly changing. For example, when adding new business nodes (such as risk assessment nodes), existing tools are difficult to quickly adapt. These tools often require redesign and integration, resulting in long development cycles and high costs, severely impacting financial institutions' responsiveness to market changes. During financial transactions, real-time risk assessment results may require dynamic adjustments to the execution order of nodes. However, most existing systems lack runtime dynamic adjustments, often requiring system redeployment or restarts. This not only leads to transaction interruptions or delays, but also severely impacts user experience and business continuity. Financial payment systems require extremely high real-time performance and high performance to handle high-concurrency transactions. However, some existing process engines may encounter performance bottlenecks when dynamically loading and executing complex business processes, failing to meet the high concurrency demands of financial services. This can lead to transaction delays or even failures, further impacting the reputation and customer trust of financial institutions. Furthermore, some process configuration tools lack intuitive visual interfaces, forcing financial institution personnel to define processes using code or complex configuration files. This not only increases operational complexity and the risk of error, but also reduces system usability and maintainability. Financial services involve a large amount of sensitive information and financial transactions, placing extremely high security requirements. Existing workflow engines and process management tools may not be specifically optimized for the high security demands of financial services, and may contain security vulnerabilities or risks that could lead to information leaks, transaction fraud, and other issues, resulting in significant losses for financial institutions and their customers. Summary of the Invention

[0006] The main purpose of the present invention is to provide a payment business processing method, device, equipment and storage medium based on a process engine, aiming to solve the problems of insufficient flexibility, limited dynamic adjustment capabilities, lack of standardized interfaces, insufficient real-time and performance, and lack of visual configuration tools in the business process management of existing payment systems.

[0007] To achieve the above objectives, the present invention provides a payment service processing method based on a process engine, comprising:

[0008] Standardize each input and output interface to obtain a standardized interface, encapsulate each business logic into a business node, and store the standardized interface and business logic in the node library;

[0009] Selecting corresponding business nodes from the node library according to business requirements, setting configuration information and node connection relationships of the business nodes, and generating a process model based on the configuration information and node connection relationships;

[0010] Start the process engine according to the execution instruction, convert the process model through the process engine to obtain a process instance;

[0011] Extracting node information and connection relationships of the process model, scheduling the execution order of the nodes according to the process instance, node information and connection relationships, obtaining real-time data of node execution in real time, and generating dynamic adjustment decisions based on the real-time data;

[0012] Dynamically adjusting the execution path and node parameters of the process instance according to the dynamic adjustment decision and real-time data;

[0013] Schedule node execution according to the adjusted execution path and node parameters to complete payment business processing, and store process instance information in the history library.

[0014] Furthermore, to achieve the above-mentioned purpose, the present invention provides a payment service processing device based on a process engine, comprising:

[0015] The interface and node processing module is used to standardize each input and output interface to obtain a standardized interface, encapsulate each business logic into a business node, and store the standardized interface and business logic in the node library;

[0016] A process design module is used to select corresponding business nodes from the node library according to business requirements, set configuration information and node connection relationships of the business nodes, and generate a process model based on the configuration information and node connection relationships;

[0017] The process engine module is used to start the process engine according to the execution instruction, and convert the process model through the process engine to obtain a process instance;

[0018] A business process execution module is used to extract the node information and connection relationships of the process model, schedule the execution order of the nodes according to the process instance, node information and connection relationships, obtain real-time data of node execution in real time, and generate dynamic adjustment decisions based on the real-time data;

[0019] A dynamic adjustment module, configured to dynamically adjust the execution path and node parameters of the process instance according to the dynamic adjustment decision and real-time data;

[0020] The process end module is used to schedule node execution according to the adjusted execution path and node parameters, complete payment business processing, and store process instance information in the history record library.

[0021] Furthermore, to achieve the above-mentioned purpose, the present invention also provides a computer device, which includes a memory, a processor, and a payment business processing program based on a process engine stored in the memory and runnable on the processor. When the payment business processing program based on the process engine is executed by the processor, the steps of the payment business processing method based on the process engine as described above are implemented.

[0022] Furthermore, to achieve the above-mentioned purpose, the present invention also provides a computer-readable storage medium, on which a payment business processing program based on a process engine is stored. When the payment business processing program based on the process engine is executed by a processor, the steps of the payment business processing method based on the process engine as described above are implemented.

[0023] Beneficial effect: The present invention relates to the field of data processing technology and can be applied to business system platforms such as medical health and financial technology. A payment business processing method based on a process engine is disclosed, comprising: standardizing each input and output interface to obtain a standardized interface, encapsulating each business logic into a business node, and storing the standardized interface and business logic in a node library; selecting a corresponding business node in the node library according to business needs, setting the configuration information and node connection relationship of the business node, and generating a process model based on the configuration information and node connection relationship; starting the process engine according to an execution instruction, converting the process model through the process engine to obtain a process instance; extracting the node information and connection relationship of the process model, scheduling the execution order of the node according to the process instance, node information and connection relationship, and obtaining real-time data of node execution in real time, generating a dynamic adjustment decision based on the real-time data; dynamically adjusting the execution path and node parameters of the process instance according to the dynamic adjustment decision and real-time data; scheduling the node execution according to the adjusted execution path and node parameters, completing the payment business processing, and storing the process instance information in a historical record library. The present invention encapsulates business logic into independent nodes through standardized interfaces and stores them in a node library. During design, users select nodes from a node library, configure and connect them to generate a process model. At runtime, the process engine loads the model, creates instances, schedules node execution, and dynamically adjusts the process based on real-time data monitoring. This approach improves the flexibility, performance, and usability of the payment system, reduces development and maintenance costs, enhances risk control capabilities, supports high-concurrency scenarios, and improves business responsiveness and system stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The present invention will be further described below with reference to the accompanying drawings and embodiments, in which:

[0025] Figure 1 A schematic diagram of an application environment of a payment service processing method based on a process engine in one embodiment of the present invention;

[0026] Figure 2 This is a flow chart of an embodiment of a payment service processing method based on a process engine according to the present invention;

[0027] Figure 3 This is a functional module diagram of a preferred embodiment of a payment service processing device based on a process engine of the present invention;

[0028] Figure 4 A schematic diagram of the structure of a computer device according to an embodiment of the present invention;

[0029] Figure 5 FIG. 2 is another structural diagram of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0030] 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.

[0031] The payment service processing method based on the process engine provided by the embodiment of the present invention can be applied in Figure 1 In an application environment, the user end communicates with the server end through a network. The server end can standardize each input and output interface through the user end to obtain a standardized interface, encapsulate each business logic into a business node, and store the standardized interface and business logic in a node library; select the corresponding business node in the node library according to business needs, set the configuration information and node connection relationship of the business node, and generate a process model based on the configuration information and node connection relationship; start the process engine according to the execution instruction, and convert the process model through the process engine to obtain a process instance; extract the node information and connection relationship of the process model, schedule the execution order of the node according to the process instance, node information and connection relationship, and obtain real-time data of node execution in real time, and generate dynamic adjustment decisions based on the real-time data; dynamically adjust the execution path and node parameters of the process instance according to the dynamic adjustment decision and real-time data; schedule node execution according to the adjusted execution path and node parameters to complete payment business processing, and store the process instance information in a historical record library. The present invention encapsulates business logic into independent nodes through standardized interfaces and stores them in a node library. During design, the user selects nodes from the node library, configures and connects to generate a process model. During runtime, the process engine loads the model, creates an instance, schedules node execution, and dynamically adjusts the process using real-time data monitoring. This method improves the flexibility, performance, and usability of the payment system, reduces development and maintenance costs, enhances risk control capabilities, supports high-concurrency scenarios, and improves business response speed and system stability. The user end can include, but is not limited to, various personal computers, laptops, smartphones, tablets, and portable wearable devices. The server end can be implemented as a standalone server or a server cluster consisting of multiple servers. The present invention is described in detail below using specific embodiments.

[0032] See also Figure 2 , Figure 2This is a flow chart of an embodiment of a payment service processing method based on a process engine provided by the present invention. It should be noted that although a logical order is shown in the flow chart, in some cases, the steps shown or described may be performed in a different order than that shown here.

[0033] like Figure 2 As shown, the payment service processing method based on the process engine proposed in the present invention includes the following steps:

[0034] S100 , standardize each input and output interface to obtain a standardized interface, encapsulate each business logic into a business node, and store the standardized interface and business logic in a node library.

[0035] In this embodiment, the payment system achieves free combination and loose coupling of business logic nodes by defining universal input and output interface specifications. The system uses the JSON format as the data exchange standard. Each node's input interface explicitly specifies the names, types, and constraints of required parameters, while the output interface defines the structure and status code of the returned result. For example, the input interface of an order processing node might include fields such as order number, order amount, and user information, while the output interface returns a status code indicating the success or failure of the order processing, along with related descriptive information.

[0036] Various business logic components within the payment system, such as order processing, payment authorization, risk assessment, and clearing, are encapsulated as independent service modules. Each node module internally implements specific business logic processing functions and exposes these functions externally through standardized interfaces. For example, an order processing node internally implements operations such as order reception, verification, and storage, while externally receiving order data and returning processing results through standardized interfaces.

[0037] S200, selecting a corresponding business node from the node library according to business requirements, setting configuration information and node connection relationships of the business node, and generating a process model based on the configuration information and node connection relationships;

[0038] S300: Start a process engine according to an execution instruction, and convert the process model through the process engine to obtain a process instance.

[0039] In this embodiment, the system has designed a visual process designer based on a graphical interface. Users can drag node components onto the canvas and define the execution order between nodes by connecting them. The designer provides a rich node component library, including common business logic nodes predefined by the system (such as order processing, payment authorization, etc.) as well as user-defined node templates. Each node component is displayed as an icon on the canvas, labeled with the node name and a brief functional description. The designer also provides node property configuration functions, allowing users to directly set node parameter values ​​through the interface. For example, on the risk assessment node, users can configure risk assessment thresholds, assessment models, and other parameters. After the user completes the process definition in the visual process designer, the system converts the process definition information into an executable process model and stores it in the process definition repository. The process model is stored in a standardized format (such as BPMN 2.0 or a custom XML format) and contains information about each node in the process (such as node type, node parameters, and connection relationships between nodes). The process definition repository can be a database or file system, which is used to store all defined business process models in the system to facilitate subsequent process execution and management.

[0040] S400, extracting the node information and connection relationship of the process model, scheduling the execution order of the nodes according to the process instance, node information and connection relationship, and obtaining real-time data of node execution in real time, and generating dynamic adjustment decisions based on the real-time data.

[0041] In this embodiment, a real-time data monitoring module is deployed in the payment system to collect and analyze key transaction data (such as user behavior, transaction amount, and risk score) in real time. The real-time data monitoring module uses technologies such as message queues (such as Kafka) to quickly transmit the collected data to the data analysis engine. The data analysis engine processes and analyzes the data in real time based on preset rules and models, generating decision-making basis for dynamically adjusting the process. For example, if a transaction amount exceeds a set threshold, the data analysis engine will determine that the transaction is high-risk and generate corresponding risk warning information. While executing the business process, the process engine receives decision-making information such as risk warnings from the data analysis engine in real time. Based on this information, the process engine dynamically adjusts the execution order or parameters of nodes. For example, during the payment authorization process, if a risk warning is received, the process engine can dynamically skip the clearing node and directly proceed to the exception handling node; or adjust the parameters of the risk assessment node to increase the rigor of the risk assessment. This dynamic adjustment process is achieved by modifying the runtime state and parameters of the process instance, without the need for redeployment or system restart, ensuring business process continuity and real-time responsiveness.

[0042] S500 , dynamically adjusting the execution path and node parameters of the process instance according to the dynamic adjustment decision and real-time data.

[0043] In this embodiment, a process engine is designed using a distributed architecture, distributing the execution tasks of process instances to multiple nodes for parallel processing, fully utilizing cluster resources and improving the system's processing capabilities. Within the distributed architecture, load balancing technologies (such as Nginx or a load balancer) are used to rationally distribute the execution tasks of process instances based on the current load of each node, preventing overloading of any particular node. Message queues (such as RabbitMQ) are introduced as a communication mechanism between process instances to ensure efficient and reliable message transmission between them. Process engine nodes exchange process instance status information, task assignment information, and other information through message queues. The node execution logic within the process engine is optimized to reduce unnecessary computation and resource consumption. For example, during node execution, a caching mechanism (such as Redis) is used to cache frequently queried data, reducing the number of database accesses. For complex business logic nodes, asynchronous processing is employed, placing time-consuming operations in a background thread pool to avoid blocking the main thread and improving system responsiveness. Data transmission between nodes is optimized to reduce the number of data serialization and deserialization times, thereby improving data transmission efficiency. For example, for identical data transmitted between multiple nodes, a pass-by-reference approach can be used to avoid duplicate data copies.

[0044] The process engine features comprehensive resource management capabilities, monitoring system resource usage (such as CPU, memory, and disk I / O) in real time. It dynamically adjusts the system's resource allocation strategy based on resource usage. For example, if a node's CPU usage is too high, some process instances will be automatically migrated to other nodes with more abundant resources. A resource monitoring interface is provided, allowing administrators to view system resource usage in real time and promptly identify and resolve resource bottlenecks.

[0045] The business logic within the payment system is divided into multiple independent node modules based on business functions. Each module focuses on implementing a specific business function. For example, the order processing function is encapsulated in the order processing node module, and the payment authorization function is encapsulated in the payment authorization node module. Each module implements the complete business logic processing flow internally and interacts with other modules through standardized interfaces. During the development process, object-oriented programming was adopted, with clear classes and interfaces defined for each node module. The class encapsulates the internal implementation details of the node module, while the interface defines the functional interface provided by the node module to the outside world. Communication between node modules is achieved through standardized interfaces. Node modules do not directly call each other's internal implementation code, but instead exchange data through interfaces. For example, after completing order processing, the order processing node module sends the order processing results to the payment authorization node module through a standardized interface. After receiving the order processing results, the payment authorization node module performs payment authorization based on the results. Interface communication can be achieved through remote call technologies (such as RESTful APIs and RPC). Each node module provides corresponding interface services, and other node modules call these interface services to achieve data exchange and business collaboration.

[0046] S600 , scheduling node execution according to the adjusted execution path and node parameters, completing payment business processing, and storing process instance information in a history record library.

[0047] In this embodiment, after a process instance completes execution, the processing results are output and the process instance information is archived. When all nodes in the process instance complete execution without exception, the process engine checks the completion status of the process instance and outputs the processing results to the payment system frontend or related business systems. The processing results can be transmitted via an API or message queue. Completed process instance information is stored in a history repository, and a database is used to store process instance information to support subsequent auditing and analysis.

[0048] As an example, within a healthcare business system platform, each input and output interface is first standardized to create a standardized interface. For example, a patient information input interface is defined, including fields such as the patient's name, age, and medical record number; and an examination result output interface is defined, returning the examination result status code and detailed description. Various medical business logic, such as patient registration, examination appointment scheduling, and diagnostic report generation, is encapsulated into independent business nodes, and these standardized interfaces and business logic are stored in a node library.

[0049] Based on specific medical business needs, such as full-process patient diagnosis and treatment services, select corresponding business nodes from the node library, such as registration nodes, examination appointment nodes, and diagnostic report generation nodes. Configure these business nodes, such as the registration department and examination item type, and set the connections between nodes, such as connecting to the examination appointment node after registration is completed. Generate a medical business process model based on this configuration information and node connections.

[0050] When it is necessary to initiate a patient diagnosis and treatment process, the process engine is started according to the execution instructions. The process engine converts the generated medical business process model to obtain an executable process instance. The process engine extracts the node information and connection relationships in the process model and schedules node execution based on the process instance, node information, and connection relationships. During the node execution process, real-time data on node execution is obtained in real time, such as the waiting time for examination appointments and the generation time of diagnostic reports. Dynamic adjustment decisions are generated based on this real-time data. For example, if the waiting time for an examination appointment is too long, the execution path of the process instance is dynamically adjusted to skip non-essential examination items and prioritize critical examinations.

[0051] Based on dynamic adjustment decisions and real-time data, the execution path and node parameters of the process instance are dynamically adjusted, such as adjusting the time window for examination appointments or increasing the priority of diagnostic report generation. Node execution is rescheduled according to the adjusted execution path and node parameters to complete the patient's diagnosis and treatment service. The entire process instance information is stored in the historical record library for subsequent medical service quality analysis and patient record management.

[0052] In the FinTech business system platform, each input and output interface is similarly standardized to create standardized interfaces. For example, an input interface for order information is defined, including fields such as order number, transaction amount, and user information; an output interface for payment results is defined, returning a status code and description indicating payment success or failure. FinTech business logic, such as order processing, payment authorization, risk assessment, and clearing, is encapsulated into independent business nodes, and these standardized interfaces and business logic are stored in a node library.

[0053] Based on specific FinTech business needs, such as online payment processing, select the appropriate business nodes from the node library, such as order processing, payment authorization, and risk assessment. Configure these business nodes, including order processing rules, payment gateway type, and risk assessment thresholds, as well as the connections between them, such as connecting to the payment authorization node after order processing. Generate a FinTech business process model based on this configuration information and node connections.

[0054] When a user initiates an online payment request, the process engine is activated according to the execution instructions. The process engine converts the generated FinTech business process model to obtain an executable process instance. The process engine extracts node information and connections from the process model and schedules node execution based on the process instance, node information, and connections. During node execution, real-time data is collected, such as transaction amounts, user behavior data, and risk scores. Dynamic adjustment decisions are made based on this real-time data. For example, if the risk score exceeds a preset threshold, the execution path of the process instance is dynamically adjusted, skipping the clearing node and directly proceeding to the exception handling node.

[0055] Based on dynamic adjustment decisions and real-time data, the execution path and node parameters of the process instance are dynamically adjusted, such as adjusting the threshold of the risk assessment node or the timeout of the payment authorization node. Node execution is rescheduled according to the adjusted execution path and node parameters to complete the online payment transaction. The entire process instance information is stored in the history library for subsequent transaction audits and risk analysis.

[0056] In the field of e-commerce, payment is a core component. The technology of this invention can significantly optimize the payment process of e-commerce platforms. For example, during promotional events, transaction volume on e-commerce platforms can surge dramatically, and traditional payment systems, due to their fixed business processes and node combinations, may struggle to cope. By adopting a process engine-based method that allows for the free combination of business logic nodes in the payment system, the payment process can be dynamically adjusted based on the characteristics of the promotion (such as different product types, different user levels, etc.). For example, for payments of high-value goods, additional risk assessment nodes can be dynamically added to the process to ensure transaction security; while for ordinary goods, the process can be simplified to improve payment efficiency. E-commerce transactions are subject to various risks, such as fraud and credit risk. The real-time data-driven process optimization and dynamic adjustment capabilities of this invention can effectively enhance risk control. During the payment process, transaction data (such as transaction amount, transaction frequency, transaction location, etc.) is monitored in real time. If anomalies are detected, such as transaction amounts far exceeding the user's normal spending level, the process can be dynamically adjusted to increase the frequency or intensity of risk assessment node execution. For example, additional identity verification nodes can be invoked to require users to provide more information for verification, thereby reducing risks.

[0057] The payment system of an e-commerce platform needs to be constantly updated to adapt to new business needs and security requirements. The modular design and low coupling adopted by this invention make the maintenance and upgrade of the payment system more convenient. When it is necessary to introduce new payment methods (such as new mobile payment channels) or update risk control algorithms, it is only necessary to add or update the corresponding business logic node module in the process engine, without the need for large-scale reconstruction of the entire payment system. This greatly reduces the time and cost of system maintenance and improves the operational efficiency of the e-commerce platform.

[0058] In the Internet of Things scenario, with the popularization of smart devices, the demand for payments between devices is gradually increasing. For example, in a smart home environment, smart appliances (such as smart washing machines and smart air conditioners) may need to automatically purchase consumables (such as laundry detergent and filters) or services (such as repairs and maintenance). The present invention can be used to construct a free combination system of business logic nodes for device payments. Different types of smart devices can dynamically combine payment processes based on their payment needs and security requirements. For example, for maintenance service payments for high-value equipment, complex verification and authorization nodes can be set up to ensure the security and accuracy of payments; and for some small-amount consumable purchases, a simplified process can be adopted to improve payment efficiency.

[0059] IoT devices generate a large amount of data, which can be used to optimize the interaction processes between devices, including payment processes. The real-time data-driven process optimization feature of the present invention can give full play to this advantage. For example, when purchasing parts or paying for maintenance services, equipment in a smart factory (such as robots, detection equipment on automated production lines) can dynamically adjust the payment process based on the equipment's operating status data (such as the equipment's failure frequency, the degree of wear of parts, etc.). If equipment failures are frequent, it may be necessary to increase the priority of the payment process for emergency repair services and adjust the payment nodes for parts procurement to ensure the normal operation of the equipment.

[0060] There are many types of devices in the Internet of Things environment, and payment security and coordination between different devices is an important issue. The standardized node interface and high-performance process engine of the present invention can ensure the compatibility and efficient execution of payment processes of different devices. By defining a unified payment business logic node interface, IoT devices of different brands and types can be seamlessly connected to the payment system. For example, in an intelligent transportation system, vehicles (such as self-driving cars) need to pay road usage fees, parking fees, etc. Through the technology of the present invention, vehicle equipment can conduct safe and efficient payment interactions with road management equipment, parking equipment, etc., to achieve cross-device collaborative payment.

[0061] In one embodiment, the step S100 includes:

[0062] S101, defining the input data format and parameters of each input interface to obtain a standardized input interface;

[0063] S102. Define the result format and status code of each output interface to obtain a standardized output interface;

[0064] S103, dividing each business logic into corresponding independent functional modules and encapsulating them to generate multiple business nodes;

[0065] S104: Register the standardized input interface, standardized output interface, and service node into the system and store them into the node library.

[0066] In this embodiment, the payment system achieves free combination and loose coupling through standardized interfaces within business logic nodes. Specifically, the system defines the input data format and parameters required for each input interface. These parameters cover aspects such as order information, user information, transaction amount, and risk score. The system also specifies the result format and status code returned by each output interface upon completion. To ensure efficient and convenient data exchange, the system uses the JSON format as the standard. JSON is lightweight, easy to read, write, and parse, making it ideal for data transmission between different systems.

[0067] Node encapsulation is a key step in packaging complex business logic into independent service modules. First, the business logic within the payment system is divided into multiple independent functional modules. For example, the order processing node is primarily responsible for receiving order information, performing order verification, and storing order data; the payment authorization node focuses on interacting with the payment gateway to complete payment authorization; the risk assessment node is responsible for evaluating the risk level of the transaction and determining whether further verification is required based on the risk score; and the clearing node is responsible for handling post-transaction fund settlement and accounting processing. Each node module exposes its functionality through standardized interfaces and adheres to the single responsibility principle, focusing on implementing a specific business function. The module's internal implementation details are hidden from the outside world, with functionality exposed only through standardized interfaces. Communication between modules also occurs through interfaces, reducing direct dependencies.

[0068] At system startup, all developed node modules are loaded and registered with the system. Registration information includes key information such as the node name, node function description, input interface specifications, and output interface specifications. These registered node modules are then stored in a node library, which can be a database table or file system directory. The primary purpose of the node library is to facilitate the search and call of node modules during subsequent process configuration.

[0069] Through the above steps, the business logic nodes in the payment system are encapsulated as independent service modules, exposing their functionality through standardized interfaces. These node modules are registered with the system and stored in a node library, providing a solid foundation for subsequent process configuration and dynamic combination. This design not only improves the system's flexibility and scalability, but also reduces coupling between modules, making system maintenance and upgrades easier.

[0070] In one embodiment, step S200 includes:

[0071] S201: Select business nodes from the node library according to business requirements, define the execution order of the business nodes, and obtain the node connection relationship;

[0072] S202: Set parameter values ​​for each node and store the parameter values ​​in the node configuration information;

[0073] S203, parsing node configuration information and node connection relationships to generate process definition information;

[0074] S204: Convert the process definition information into a standardized process model, and store the process model in a process definition repository.

[0075] In this embodiment, users design business processes using a visual process designer interface. After logging into the system, users enter the main interface of the visual process designer. This interface primarily consists of a toolbar, a canvas area, and a node library area. The toolbar provides users with buttons for process design, including functions such as saving, loading, undoing, redoing, and running processes. The canvas area is the "main battlefield" for process design, where users can define business processes by dragging and connecting nodes. The node library area clearly lists all available node modules, allowing users to easily select as needed. When a user clicks the "New Process" button, the system initializes a new, blank process design canvas and loads the node library, displaying all available node modules for the user to select. Users find the desired node module from the node library, such as "Order Processing Node" or "Payment Authorization Node," and then drag and drop the node from the node library onto the canvas. The node icon and name appear on the canvas. Next, the user clicks the output port (usually a small dot) of a node and drags the mouse to the input port of another node to connect the nodes. The system automatically creates a connection line with an arrow that indicates the direction of data flow. For example, you can connect the output port of the "Order Processing Node" to the input port of the "Payment Authorization Node" to indicate that after the order is processed, the data will be passed to the Payment Authorization Node.

[0076] Users can also configure parameter values ​​for each node through the interface. These parameters may include risk assessment thresholds, order processing rules, and more. Simply double-click the node icon on the canvas to open the node's detailed configuration interface. This configuration interface typically appears as a pop-up window, clearly displaying all configurable parameters for the node and their default values. Users manually enter or select parameter values ​​based on specific business needs. For example, in the "Risk Assessment Node," users can set the risk assessment threshold to 80, meaning that transactions exceeding 80 are considered high risk. In the "Order Processing Node," users can configure order processing rules, such as whether to verify user identity or send notifications. Parameter values ​​can be static values, such as numbers or strings, or dynamic expressions, such as variables retrieved from the context. After completing parameter settings, click "Save," and the system will save the parameter values ​​to the node's configuration information. These saved parameter values ​​will be used by the node module during process execution.

[0077] After the user completes a series of operations such as dragging and dropping nodes, connecting them, and configuring parameters, click the "Save Process" button. At this point, the system will parse the node information and connection relationships on the canvas and convert the process definition into a standardized process model. The process model usually uses the BPMN 2.0 format or a custom XML / JSON format. The generated process model is then stored in a process definition repository, which can be a database, file system, or cloud storage service. Each process model in the repository has a unique identifier, such as a process ID, which facilitates subsequent loading and execution. Through this visual process designer, users can easily design and configure business processes. This visual design method greatly improves the efficiency of process design while lowering the technical threshold, allowing non-technical personnel to easily complete complex business process configuration.

[0078] In one embodiment, step S300 includes:

[0079] S301, start the process engine according to the execution instruction, and load the configuration information and system environment into the process engine;

[0080] S302: Connect the process definition repository to the process engine, and load the process model in the process definition repository into the process engine;

[0081] S303, parsing each process model through a process engine and converting the process model into a process instance;

[0082] S304: Obtain the system resource allocation policy in the configuration information, and perform initialization configuration according to the system resource allocation policy and the process instance;

[0083] S305: During the initial configuration process, monitor the usage of system resources, output the monitoring results, and dynamically adjust the allocation of system resources based on the monitoring results.

[0084] In this embodiment, the startup and initialization phase of the process engine lays a solid foundation for the efficient execution of business processes. The process engine is started through a startup script or command. During the startup process, it first loads the configuration file and initializes the system environment. The configuration file contains key settings such as database connection information, node library path, process definition repository path, etc. in detail. Subsequently, the process engine connects to the process definition repository, which can be a database or file system, and then loads all defined process models. For each process model, the process engine parses it and converts it into an internal executable process instance. For example, if the process model uses the BPMN 2.0 format, the process engine will parse the XML file and accurately extract the node information, connection relationship and parameter configuration; if the process model exists in the form of a JSON file, the process engine will also parse the JSON file to build an internal process instance structure.

[0085] At the same time, the process engine performs initial configuration based on system resources, such as CPU and memory, and simultaneously initiates resource monitoring. It reads resource allocation policies, including key parameters such as the maximum number of threads and memory limits, from the configuration file. Based on these configurations, the process engine initializes a thread pool dedicated to handling concurrent process instances. Regarding memory management, the process engine sets memory usage limits to effectively prevent memory leaks, for example, by setting the heap memory size through JVM parameters. Furthermore, the process engine launches a monitoring thread that regularly checks system resource usage, covering key metrics such as CPU utilization and memory usage. It collects these resource usage metrics using system tools (such as `Runtime.getRuntime()`) or third-party libraries (such as `Micrometer`) and dynamically adjusts resource allocation based on the monitoring results. For example, if high CPU utilization is detected, the process engine can dynamically adjust the number of threads in the thread pool to optimize resource utilization.

[0086] Regarding the communication mechanism, the process engine initializes a message queue, such as Kafka or RabbitMQ, for communication between process instances. Based on system requirements, it selects an appropriate message queue system and reads the message queue connection information, including the host address, port number, username, and password, from a configuration file. Subsequently, the message queue client is initialized based on the configuration file. During process execution, the process engine uses the message queue to send messages between nodes. For example, after completing an order processing node, it sends the result to the message queue. The next node, such as the payment authorization node, then receives the message from the message queue and continues processing.

[0087] During the process engine's initialization and loading phase, it provides comprehensive foundational support for business process execution. By loading configuration files, initializing the system environment, and loading all defined process models, the process engine ensures the smooth startup of business processes. Simultaneously, it initializes the thread pool and memory management based on system resources, activates resource monitoring mechanisms, and dynamically adjusts resource allocation, ensuring stable system operation and efficient performance. Furthermore, it selects and initializes a message queue system for communication between process instances, further enhancing the process engine's collaborative capabilities. Through this series of initialization and loading operations, the process engine efficiently manages and executes business processes, ensuring overall system stability and performance.

[0088] In one embodiment, step S400 includes:

[0089] S401. Load the corresponding process model in the process definition repository according to the business type;

[0090] S402, parsing the process model to extract node information and connection relationships;

[0091] S403, scheduling node execution according to the process instance, node information and connection relationship;

[0092] S404: Monitor the real-time data of the node during execution in real time, and generate a dynamic adjustment decision based on the real-time data.

[0093] In this embodiment, when a payment service is triggered, the process engine will load the corresponding process model according to the business type and create a process instance. The payment service can be triggered in a variety of ways, such as a user submitting a payment request, a scheduled task triggering payment reconciliation, etc. When triggered, the system will receive a business event containing the business type (such as order payment, refund processing, etc.) and related data (such as order information, user information, etc.). The process engine loads the corresponding process model from the process definition repository based on the business type. For example, when the business type is "order payment", the process engine will load a process model named "PaymentProcess". Subsequently, the process engine creates a new process instance based on the loaded process model. The process instance contains the runtime state of the process, such as the current node, process variables, execution path, etc.

[0094] The process engine schedules nodes for execution sequentially according to the order defined in the process model. It parses the process model, extracting node information and connections. For example, the process model defines an "order processing node" and a "payment authorization node" and specifies their execution order. During scheduling, the process engine checks node dependencies to ensure that data transfer and processing conform to the process model definition. The current node receives the output data of the previous node through a standardized interface. Each node receives data through a standardized interface to ensure data format consistency. For example, the output data of the order processing node may be a JSON object containing the order processing results. The output data of the previous node is passed to the current node through a standardized interface, such as the payment authorization node receiving the output data of the order processing node. The node processes the data according to its internal logic and generates output results. Each node encapsulates specific business logic. For example, the order processing node is responsible for verifying and storing order information, while the payment authorization node is responsible for interacting with the payment gateway. After completing processing, the node generates output results and returns them through a standardized interface. The output results can be JSON objects, status codes, etc., for the next node to use. The node sends the processing results to the next node through a standardized interface and stores the output data in variables in the process instance for the next node to receive. If nodes communicate with each other through message queues, the node sends the output data to the message queue, and the next node receives the data from the queue.

[0095] During node execution, the real-time data monitoring module collects data related to the business process, such as transaction amounts, user behavior, and risk scores. This module collects data related to the business process by monitoring system resources, user behavior, and transaction data. This collected data is stored in a real-time database or memory for use by the data analysis engine. The data analysis engine uses this real-time data to generate dynamic adjustment decisions, such as skipping certain nodes or adjusting node parameters. Based on this collected real-time data, the data analysis engine analyzes the status and risk level of the business process. For example, the risk score determines whether a transaction requires additional risk assessment. Based on this analysis, the data analysis engine generates dynamic adjustment decisions and notifies the process engine.

[0096] During the business process execution phase, the process engine ensures efficient and flexible payment operations through the following steps: loading the process model and creating a process instance based on the business type; scheduling nodes for execution in the order defined in the process model; receiving the output data of the previous node through a standardized interface; processing the data according to internal logic and generating output results; and sending the results to the next node through a standardized interface; collecting real-time data related to the business process; and generating dynamic adjustment decisions based on this real-time data to optimize the process execution path. These steps ensure that the payment system can dynamically adjust business processes based on real-time data, thereby improving the system's flexibility and responsiveness.

[0097] In one embodiment, step S500 includes:

[0098] S501. Modify the execution path and / or node parameters of the process instance in real time according to the dynamic adjustment decision;

[0099] S502: Evaluate the transaction risk level based on the real-time data and obtain a risk assessment result;

[0100] S503: Modify the execution path and / or node parameters of the process instance in real time according to the risk assessment result;

[0101] S504: Transmit the adjusted execution path and / or node parameters to the next node through the process instance.

[0102] In this embodiment, the process engine modifies the execution path or node parameters of a process instance in real time based on dynamic adjustment decisions. These decisions are generated by the data analysis engine based on real-time data. For example, based on risk assessment results, user behavior, transaction amounts, and other data, the data analysis engine determines whether process adjustments are necessary. If the risk assessment results indicate a high risk transaction, the decision may be to skip non-essential nodes or adjust node parameters.

[0103] The process engine will modify the execution path of the process instance in real time based on dynamic adjustment decisions, such as skipping certain non-essential nodes and proceeding directly to the next critical node. At the same time, the process engine will also modify the operating parameters of the node in real time based on dynamic adjustment decisions, such as adjusting the threshold parameters of the risk assessment node. The risk assessment node will assess the risk level of the transaction based on real-time data such as transaction amount, user behavior, and historical records, and may return a risk score. If the risk score exceeds the preset threshold, the process engine will decide to skip certain non-essential nodes, such as the clearing node, and proceed directly to the exception handling node. In addition, the process engine will dynamically modify the operating parameters of the node based on real-time data or dynamic adjustment decisions, such as adjusting the threshold parameters of the risk assessment node based on the transaction amount.

[0104] Adjusted parameters are passed to the next node via process instance variables, and the dynamically adjusted results are fed back to subsequent nodes to ensure process continuity and real-time performance. For example, the adjusted risk threshold at the risk assessment node is passed to the payment authorization node, and subsequent nodes continue execution based on the feedback data, ensuring process continuity and real-time performance. For example, the payment authorization node decides whether to authorize the payment based on the adjusted risk threshold.

[0105] The process engine also dynamically adjusts resource allocation and optimizes node execution logic based on resource monitoring to ensure stability and real-time performance in high-concurrency scenarios. The process engine uses a resource monitoring mechanism to monitor system resource usage, such as CPU, memory, and thread pools, in real time. Based on resource monitoring results, the process engine dynamically adjusts resource allocation, such as adjusting the number of threads in the thread pool, and optimizes node execution logic, such as reducing the execution time of certain nodes or adjusting the execution order.

[0106] During the dynamic adjustment and optimization phase, the process engine ensures that business processes can flexibly adjust based on real-time data and system status through the following steps: It modifies the execution path or node parameters of process instances in real time based on dynamic adjustment decisions; skips non-essential nodes based on risk assessment results; dynamically modifies node operating parameters; and feeds back the results of dynamic adjustments to subsequent nodes to ensure process continuity and real-time performance. Furthermore, it dynamically adjusts resource allocation based on resource monitoring and optimizes node execution logic to ensure stability and real-time performance in high-concurrency scenarios. These measures ensure that the payment system can dynamically adjust business processes based on real-time data, thereby improving the system's flexibility and responsiveness.

[0107] In one embodiment, the payment service processing method based on the process engine further includes:

[0108] Real-time detection of whether a node fails to execute;

[0109] When a node execution exception is detected, the exception handling mechanism is triggered, the current node is switched to the backup node to continue execution, the process path is adjusted, the fault point is skipped, the exception information is recorded, and an alarm notification is sent.

[0110] In this embodiment, the process engine has powerful exception handling and fault tolerance capabilities. During the node execution process, it monitors the node status in real time, including key information such as execution time and return status code. For example, by setting a timeout threshold, once the node execution time exceeds the set value, the node execution is determined to have failed. When an abnormal situation is detected (such as timeout, error return, etc.), the process engine will immediately trigger the exception handling mechanism. The backup node is pre-defined in the process model. When the main node fails to execute, it automatically switches to the backup node to continue executing the process. In addition, the process engine will flexibly adjust the process path according to the abnormal situation, skip the faulty node, and ensure that the entire process can continue to execute smoothly. At the same time, the abnormal information is recorded in detail, including key elements such as node ID, error information, and occurrence time, and an alarm notification is sent to the administrator. The notification method is diverse, which can be email, SMS or system message, so that the administrator can know in time and take corresponding measures.

[0111] The process engine also has comprehensive process monitoring and management capabilities. It monitors the execution status of business processes in real time, covering aspects such as node execution time and resource usage. Through the monitoring thread, detailed information such as node execution time and resource usage is collected in real time to provide data support for subsequent analysis and management. Before and after the execution of each node, the process engine records detailed logs covering key information such as input and output data and execution time. The execution time and resource usage of process instances are regularly analyzed to generate performance reports to provide a basis for process optimization. In addition, the process engine provides a web interface through which administrators can view the execution status, log information, performance reports, etc. of process instances in real time. With the help of a unified monitoring and management interface, administrators can efficiently locate and adjust problems, thereby improving management efficiency and accuracy.

[0112] Regarding process termination and result output, the process engine checks that all nodes have completed execution without exception. When this condition is met, the process instance terminates. It stores the final processing results in variables within the process instance and outputs them to the payment system frontend or related business systems, completing the payment transaction. Completed process instance information is also archived in a historical record repository to facilitate subsequent auditing and analysis.

[0113] To continuously optimize and expand system functionality, the process engine regularly adjusts the process model based on real-time data and historical execution results. Based on performance reports and historical data, the order of nodes or parameters in the process model are adjusted to improve process execution efficiency and quality. New node modules are developed and registered with the system based on business needs, continuously expanding system functionality to meet ever-changing business requirements. Furthermore, the process engine and related components are continuously upgraded and regularly updated to fix vulnerabilities, improve overall system performance and stability, and ensure that the payment system can flexibly and efficiently handle business processes while maintaining high concurrency and security requirements.

[0114] Through the coordinated operation of the above-mentioned exception handling and fault-tolerance mechanisms, process monitoring and management, process termination and result output, as well as continuous optimization and expansion, the payment system has been significantly improved in terms of stability, ease of use, and scalability, maintenance costs have been reduced, and risk control capabilities have been enhanced, thereby effectively ensuring the smooth and efficient development of payment business.

[0115] In one embodiment, a payment service processing device based on a process engine is provided, and the payment service processing device based on a process engine corresponds one-to-one to the payment service processing method based on a process engine in the above embodiment. Figure 3 , Figure 3 This is a functional module diagram of a preferred embodiment of a payment service processing device based on a process engine according to the present invention. It includes an interface and node processing module 10, a process design module 20, a process engine module 30, a business process execution module 40, a dynamic adjustment module 50, and a process termination module 60. Each functional module is described in detail below:

[0116] The interface and node processing module 10 is used to standardize each input and output interface to obtain a standardized interface, encapsulate each business logic into a business node, and store the standardized interface and business logic in a node library;

[0117] A process design module 20 is used to select corresponding business nodes from the node library according to business requirements, set configuration information and node connection relationships of the business nodes, and generate a process model based on the configuration information and node connection relationships;

[0118] The process engine module 30 is used to start the process engine according to the execution instruction, and convert the process model through the process engine to obtain a process instance;

[0119] The business process execution module 40 is used to extract the node information and connection relationships of the process model, schedule the execution order of the nodes according to the process instance, node information and connection relationships, obtain real-time data of node execution in real time, and generate dynamic adjustment decisions based on the real-time data;

[0120] A dynamic adjustment module 50, configured to dynamically adjust the execution path and node parameters of the process instance according to the dynamic adjustment decision and real-time data;

[0121] The process ending module 60 is used to schedule node execution according to the adjusted execution path and node parameters, complete the payment business processing, and store the process instance information in the history record library.

[0122] In one embodiment, the interface and node processing module 10 includes:

[0123] An input interface definition unit, used to define the input data format and parameters of each input interface to obtain a standardized input interface;

[0124] The output interface definition unit is used to define the result format and status code of each output interface to obtain a standardized output interface;

[0125] The business logic encapsulation unit is used to divide each business logic into corresponding independent functional modules and encapsulate them to generate multiple business nodes;

[0126] The storage unit is used to register the standardized input interface, standardized output interface and business node into the system and store them in the node library.

[0127] In one embodiment, the process design module 20 includes:

[0128] Define the node execution unit, which is used to select business nodes from the node library according to business requirements, define the execution order of business nodes, and obtain the node connection relationship;

[0129] A parameter value setting unit, used to set the parameter value of each node and store the parameter value in the configuration information of the node;

[0130] The process definition information unit is used to parse the node configuration information and node connection relationship to generate process definition information;

[0131] The process model unit is used to convert the process definition information into a standardized process model and store the process model in a process definition repository.

[0132] In one embodiment, the process engine module 30 includes:

[0133] The process engine unit is used to start the process engine according to the execution instruction and load the configuration information and system environment into the process engine;

[0134] The process model loading unit is used to connect the process definition repository with the process engine and load the process model in the process definition repository into the process engine;

[0135] A process instance unit, configured to parse each process model through a process engine and convert the process model into a process instance;

[0136] A system resource allocation strategy unit, configured to obtain the system resource allocation strategy in the configuration information and perform initialization configuration according to the system resource allocation strategy and the process instance;

[0137] The resource monitoring unit is used to monitor the usage of system resources during the initial configuration process, output the monitoring results, and dynamically adjust the system resource allocation based on the monitoring results.

[0138] In one embodiment, the business process execution module 40 includes:

[0139] The process model unit is used to load the corresponding process model in the process definition repository according to the business type;

[0140] An information extraction unit, configured to parse the process model and extract node information and connection relationships;

[0141] A scheduling node execution unit, configured to schedule node execution according to the process instance, node information, and connection relationship;

[0142] The real-time data unit is used to monitor the real-time data of the node during execution in real time and generate dynamic adjustment decisions based on the real-time data.

[0143] In one embodiment, the dynamic adjustment module 50 includes:

[0144] A first data modification unit, configured to modify the execution path and / or node parameters of the process instance in real time according to the dynamic adjustment decision;

[0145] a risk assessment unit, configured to assess a transaction risk level based on the real-time data and obtain a risk assessment result;

[0146] A second data modification unit, configured to modify the execution path and / or node parameters of the process instance in real time according to the risk assessment result;

[0147] The data transmission unit is used to transmit the adjusted execution path and / or node parameters to the next node through the process instance.

[0148] In one embodiment, the exception handling module includes:

[0149] Node checking unit, used to detect in real time whether a node has failed to execute;

[0150] The exception handling unit is used to trigger the exception handling mechanism when a node execution exception is detected, switch the current node to the backup node for continued execution, adjust the process path, skip the fault point, record the exception information, and send an alarm notification.

[0151] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 4 As shown. The computer device includes a processor, memory, network interface, and database connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes non-volatile and / or volatile storage media and internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external user terminal via a network connection. When the computer program is executed by the processor, it implements the functions or steps on the service side of a payment business processing method based on a process engine.

[0152] In one embodiment, a computer device is provided. The computer device may be a user terminal, and its internal structure diagram may be as follows: Figure 5 As shown. The computer device includes a processor, memory, a network interface, a display screen, and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external server via a network connection. When executed by the processor, the computer program implements the functions or steps on the user side of a payment service processing method based on a process engine.

[0153] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the following steps are performed:

[0154] Standardize each input and output interface to obtain a standardized interface, encapsulate each business logic into a business node, and store the standardized interface and business logic in the node library;

[0155] Selecting corresponding business nodes from the node library according to business requirements, setting configuration information and node connection relationships of the business nodes, and generating a process model based on the configuration information and node connection relationships;

[0156] Start the process engine according to the execution instruction, convert the process model through the process engine to obtain a process instance;

[0157] Extracting node information and connection relationships of the process model, scheduling the execution order of the nodes according to the process instance, node information and connection relationships, obtaining real-time data of node execution in real time, and generating dynamic adjustment decisions based on the real-time data;

[0158] Dynamically adjusting the execution path and node parameters of the process instance according to the dynamic adjustment decision and real-time data;

[0159] Schedule node execution according to the adjusted execution path and node parameters to complete payment business processing, and store process instance information in the history library.

[0160] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0161] Standardize each input and output interface to obtain a standardized interface, encapsulate each business logic into a business node, and store the standardized interface and business logic in the node library;

[0162] Selecting corresponding business nodes from the node library according to business requirements, setting configuration information and node connection relationships of the business nodes, and generating a process model based on the configuration information and node connection relationships;

[0163] Start the process engine according to the execution instruction, convert the process model through the process engine to obtain a process instance;

[0164] Extracting node information and connection relationships of the process model, scheduling the execution order of the nodes according to the process instance, node information and connection relationships, obtaining real-time data of node execution in real time, and generating dynamic adjustment decisions based on the real-time data;

[0165] Dynamically adjusting the execution path and node parameters of the process instance according to the dynamic adjustment decision and real-time data;

[0166] Schedule node execution according to the adjusted execution path and node parameters to complete payment business processing, and store process instance information in the history library.

[0167] It should be noted that the above functions or steps that can be implemented by the computer-readable storage medium or computer device can be found in the relevant descriptions of the server side and the user side in the aforementioned method embodiment. To avoid repetition, they will not be described one by one here.

[0168] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0169] Those skilled in the art will clearly understand that for the sake of convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0170] It should be noted that if any software tools or components other than those of the Company appear in the embodiments of this application, they are merely for illustration and do not represent actual use. The above embodiments are intended only to illustrate the technical solutions of the present invention, not to limit them. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some of the technical features therein with equivalents. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the scope of protection of the present invention.

Claims

1. A payment service processing method based on a process engine, characterized in that: The following steps are involved: Standardize each input and output interface to obtain a standardized interface, encapsulate each business logic into a business node, and store the standardized interface and business logic in the node library; Selecting corresponding business nodes from the node library according to business requirements, setting configuration information and node connection relationships of the business nodes, and generating a process model based on the configuration information and node connection relationships; Start the process engine according to the execution instruction, convert the process model through the process engine to obtain a process instance; Extracting node information and connection relationships of the process model, scheduling the execution order of the nodes according to the process instance, node information and connection relationships, obtaining real-time data of node execution in real time, and generating dynamic adjustment decisions based on the real-time data; Dynamically adjusting the execution path and node parameters of the process instance according to the dynamic adjustment decision and real-time data; Schedule node execution according to the adjusted execution path and node parameters to complete payment business processing, and store process instance information in the history library.

2. The payment service processing method based on the process engine according to claim 1, characterized in that: The process of standardizing each input and output interface to obtain a standardized interface, encapsulating each business logic into a business node, and storing the standardized interface and business logic in a node library includes: Define the input data format and parameters of each input interface to obtain a standardized input interface; Define the result format and status code of each output interface to obtain a standardized output interface; Divide each business logic into corresponding independent functional modules and encapsulate them to generate multiple business nodes; Register the standardized input interface, standardized output interface and business nodes into the system and store them in the node library.

3. The payment service processing method based on the process engine according to claim 1, characterized in that: The selecting corresponding business nodes from the node library according to business requirements, setting configuration information and node connection relationships of the business nodes, and generating a process model according to the configuration information and node connection relationships includes: Select business nodes from the node library according to business requirements, define the execution order of business nodes, and obtain node connection relationships; Setting parameter values ​​for each node and storing the parameter values ​​in the node's configuration information; Parse the node configuration information and node connection relationship to generate process definition information; The process definition information is converted into a standardized process model, and the process model is stored in a process definition repository.

4. The payment service processing method based on the process engine according to claim 1, characterized in that: The process engine is started according to the execution instruction, and the process engine is used to parse the process model to obtain the process embodiment, including: Start the process engine according to the execution instructions and load the configuration information and system environment into the process engine; Connect the process definition repository with the process engine and load the process model in the process definition repository into the process engine; Parsing each process model through a process engine and converting the process model into a process instance; Obtain the system resource allocation strategy in the configuration information, and perform initialization configuration according to the system resource allocation strategy and process instance; During the initial configuration process, the system resource usage is monitored, the monitoring results are output, and the system resource allocation is dynamically adjusted based on the monitoring results.

5. The payment service processing method based on the process engine according to claim 1, characterized in that: The extracting of node information and connection relationships of the process model, scheduling the execution order of the nodes according to the process instance, node information and connection relationships, acquiring real-time data of node execution in real time, and generating dynamic adjustment decisions based on the real-time data include: Load the corresponding process model in the process definition repository according to the business type; Parsing the process model to extract node information and connection relationships; Scheduling node execution according to the process instance, node information, and connection relationships; Real-time monitoring of real-time data during node execution, and generating dynamic adjustment decisions based on the real-time data.

6. The payment service processing method based on the process engine according to claim 1, characterized in that: The dynamically adjusting the execution path and node parameters of the process instance according to the dynamic adjustment decision and real-time data includes: Modify the execution path and / or node parameters of the process instance in real time based on dynamic adjustment decisions; Assess the transaction risk level based on the real-time data and obtain a risk assessment result; Modify the execution path and / or node parameters of the process instance in real time according to the risk assessment results; The adjusted execution path and / or node parameters are transmitted to the next node through the process instance.

7. The payment service processing method based on the process engine according to claim 1, characterized in that: Also includes: Real-time detection of whether a node fails to execute; When a node execution exception is detected, the exception handling mechanism is triggered, the current node is switched to the backup node to continue execution, the process path is adjusted, the fault point is skipped, the exception information is recorded, and an alarm notification is sent.

8. A payment service processing device based on a process engine, characterized in that: The payment service processing device based on the process engine includes: The interface and node processing module is used to standardize each input and output interface to obtain a standardized interface, encapsulate each business logic into a business node, and store the standardized interface and business logic in the node library; A process design module is used to select corresponding business nodes from the node library according to business requirements, set configuration information and node connection relationships of the business nodes, and generate a process model based on the configuration information and node connection relationships; The process engine module is used to start the process engine according to the execution instruction, and convert the process model through the process engine to obtain a process instance; A business process execution module is used to extract the node information and connection relationships of the process model, schedule the execution order of the nodes according to the process instance, node information and connection relationships, obtain real-time data of node execution in real time, and generate dynamic adjustment decisions based on the real-time data; A dynamic adjustment module, configured to dynamically adjust the execution path and node parameters of the process instance according to the dynamic adjustment decision and real-time data; The process end module is used to schedule node execution according to the adjusted execution path and node parameters, complete payment business processing, and store process instance information in the history record library.

9. A computer device, characterized in that: The computer device includes a memory, a processor, and a payment business processing program based on a process engine stored in the memory and capable of running on the processor. When the payment business processing program based on the process engine is executed by the processor, the steps of the payment business processing method based on the process engine as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that The storage medium stores a payment service processing program based on a process engine. When the payment service processing program based on the process engine is executed by a processor, the steps of the payment service processing method based on the process engine as described in any one of claims 1 to 7 are implemented.

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