Standardized implementation method of dynamic automated translation device

Abstract

The application relates to the field of data processing and communication technology, and discloses a standardized implementation method of a dynamic automatic translation device, which comprises the following steps: constructing and analyzing a standard configuration model, generating an attribute dependency matrix, performing loop detection and topological sorting, generating a linear ordered execution sequence, presetting a class code skeleton and a runtime context, extracting a logic code set according to the sequence, applying a code synthesis equation to generate a composite logic source code, calling an instant compiler and an isolated class loader to convert the source code into a dynamic translation instance and perform atomic reference replacement, and feeding device original data into the instance to make the device original data flow in a logical path in a one-way manner in the runtime context to complete translation. Through the conversion of the interpretive execution into the compiled sequential execution, the application eliminates runtime dependency lookup, cooperates with the isolated loading and atomic replacement mechanism, realizes the independent running and smooth hot updating of the device logic, and improves the efficiency and stability of the heterogeneous protocol adaptation.

Description

Technical Field

[0001] This invention relates to the field of data processing and communication technology, specifically to a standardized implementation method for a dynamic automated translation device. Background Technology

[0002] In the smart home and consumer Internet of Things (IoT) ecosystem, the massive number of devices that need to be connected to the platform typically come from different third-party manufacturers, covering a wide range of categories such as lighting, security, and environmental monitoring. These devices often use their own proprietary binary protocols or non-standard object model definitions at the communication layer, which leads to the challenge of adapting to the coexistence of multiple heterogeneous protocols when building a unified device access and control system for IoT platforms or edge gateways.

[0003] Currently, mainstream IoT platforms typically employ interpreted script engines or rule-based dynamic parsing schemes to handle the diversity of device access. These schemes generally use predefined general rule templates, load specific device description files at system runtime, and rely on reflection mechanisms or interpreters to parse data streams in real time. However, as the scale of connected devices expands and the complexity of business logic increases (e.g., complex state calculations involving multiple sensor linkages), this traditional processing model has revealed its technical limitations in practical applications.

[0004] First, the existing interpreted execution model suffers from operational efficiency bottlenecks. Because the parsing logic of device data and the dependency calculations between attributes (e.g., the calculation of filter wear index depends on real-time wind speed and environmental particulate matter concentration) require the interpreter to repeatedly read rule files at runtime and dynamically confirm the reference relationships between variables through recursive lookups or hash retrievals, a significant amount of computational resources are consumed by logical judgments and memory addressing. In high-load scenarios facing massive concurrent status reporting from numerous smart devices, this runtime overhead reduces system throughput, increases data processing latency, and impacts the user's real-time experience in scene-based interactions.

[0005] Secondly, in a platform environment where multiple types of devices coexist, traditional class loading and update mechanisms are insufficient to meet service continuity requirements. When the platform needs to connect to a new type of device or update the parsing logic of an older device, it often relies on the system's default class loader. Without a fine-grained isolation mechanism, frequent logic updates can easily trigger global library conflicts, or require restarting the entire access service for the new logic to take effect. This can lead to intermittent service interruptions, affecting the normal connection and control of other online devices, and failing to meet the stability requirements of smart home platforms for 24 / 7 online connectivity and seamless upgrades.

[0006] Furthermore, due to the lack of standardized configuration models and unified dependency management mechanisms, the integration of new devices often relies on developers hard-coding adaptations for specific protocols or writing complex non-standard scripts. This tightly coupled development approach makes it difficult for platforms to quickly integrate new third-party devices through a unified specification library, causing device integration costs to increase non-linearly with the expansion of the ecosystem and limiting the scalability of the IoT ecosystem. Summary of the Invention

[0007] To address the shortcomings of existing technologies, this invention provides a standardized implementation method for dynamic automated translation devices. This method solves the problems of existing technologies, which mainly adopt an interpreted execution mode, resulting in high runtime dependency lookup overhead and low efficiency. Furthermore, the lack of effective class isolation and hot update mechanisms makes it difficult to achieve efficient adaptation and dynamic expansion of heterogeneous protocols across multiple devices while ensuring service continuity.

[0008] To achieve the above objectives, the present invention provides the following technical solution:

[0009] A standardized implementation method for a dynamic automated translation device includes: Receive external input functional attribute definitions and initialize a device attribute set based on the functional attribute definitions, and construct a standard configuration model containing dependency constraints for the device attribute set; The standard configuration model is parsed and an attribute dependency matrix is ​​constructed. The attribute dependency matrix is ​​then used to quantify the unidirectional dependency relationships between attribute nodes within the device attribute set. Based on the attribute dependency matrix, loop detection and topology sorting calculation are performed to generate a linearly ordered execution sequence; A pre-set class code skeleton and runtime context are used. Business logic fragments are extracted based on the execution sequence to generate a set of logic code. The code synthesis equation is applied to synthesize the class code skeleton, the runtime context and the set of logic code to generate composite logic source code. The interface of the just-in-time compiler and the isolated class loader are invoked to transform the complex logic source code into a dynamic translation instance and perform atomic reference replacement. The original device data is then sent into the runtime context of the dynamic translation instance to perform heterogeneous protocol translation tasks.

[0010] Furthermore, a standard configuration model containing dependency constraints is constructed for the device attribute set, including: for each attribute node in the device attribute set, a detailed configuration data structure is constructed to generate the standard configuration model; the attribute configuration in the standard configuration model includes at least: a unique identifier, a data type, an executor class name, and an explicitly defined dependency set; the dependency set lists the list of dependent attribute identifiers that must be obtained in advance to compute the current attribute node, thus clarifying the logical prerequisite relationships between attributes at the static configuration level.

[0011] Further, parsing the standard configuration model and constructing the attribute dependency matrix includes: initializing an initial adjacency matrix based on the number of attributes defined in the standard configuration model; traversing all attribute configurations in the standard configuration model, and filling the initial adjacency matrix numerically according to the dependency matrix formula to generate the filled attribute dependency matrix; The calculation logic of the dependency matrix formula is as follows: when it is detected that the dependency set of the current attribute node explicitly declares the dependent attribute, the numerical element determined by the corresponding row index and column index in the initial adjacency matrix is ​​set to a logical true value indicating the existence of an explicit dependency relationship; otherwise, it is set to a logical false value indicating that there is no direct dependency relationship.

[0012] Furthermore, based on the attribute dependency matrix, loop detection and topological sorting calculations are performed to generate a linearly ordered execution sequence, including: constructing a corresponding directed graph model based on the attribute dependency matrix, and performing a full path traversal of the directed graph model using a depth-first traversal algorithm; during the traversal, if a reverse edge is detected, it is determined that there is an illegal circular dependency in the standard configuration model and an error is reported; if no reverse edge is detected after the traversal is completed, it is confirmed that the directed graph model is a directed acyclic graph. A topological sorting calculation is performed on the directed graph model that has passed the verification to generate an ordered list of nodes; the execution sequence is generated based on the ordered list of nodes, wherein the prerequisite dependencies of the attribute nodes at any position in the execution sequence are all placed before the corresponding positions in the standard configuration model.

[0013] Furthermore, the code synthesis equation is applied to synthesize the class code skeleton, the runtime context, and the logic code set, including: performing a variable binding operation to map the input and output variables in the logic code set to the runtime context; The system performs a sequential concatenation operation, connecting multiple mapped code segments end-to-end to form a complete logic block according to the index order of the execution sequence; it then performs a code injection operation, embedding the complete logic block into the specified execution entry point of the class code skeleton to generate the composite logic source code; the class code skeleton is pre-defined according to a unified standard interface preset by the system.

[0014] Furthermore, the runtime context is used as a shared memory carrier for data to flow between different logical segments; the runtime context is used to store the original data received from the device, intermediate calculation results, and final business data within the processing lifecycle of a single request.

[0015] Furthermore, the process of calling the just-in-time (JIT) compiler interface and the isolation class loader to transform the composite logic source code into a dynamic translation instance includes: calling the JIT compiler interface to directly compile the composite logic source code into binary bytecode; using the isolation class loader to load the binary bytecode into the method area of ​​the virtual machine, and instantiating it into the dynamic translation instance with full processing capabilities; the isolation class loader is used to prioritize loading bytecode data in the memory buffer and create an independent namespace for each device or each version configuration.

[0016] Further, performing atomic reference replacement includes: registering the dynamic translation instance to the device management center; performing an atomic reference replacement operation to directly update the key-value reference of the corresponding device identifier in the device management center, replacing the pointer pointing to the old instance with a pointer pointing to the newly generated dynamic translation instance, and establishing the currently effective dynamic translation instance.

[0017] Furthermore, sending the device's raw data into the runtime context of the dynamic translation instance includes: when receiving the external device's raw data, obtaining the currently active dynamic translation instance from the device management center based on the device identifier; initializing a new runtime context, and encapsulating the device's raw data into the runtime context; The entry method of the dynamic translation instance is called, and the runtime context is passed in, so that the data flows unidirectionally in the runtime context according to the logical path synthesized by the execution sequence.

[0018] Furthermore, the heterogeneous protocol translation task includes: completing the entire chain of transformation from parsing the original data of the device, calculating intermediate parameters to generating standard translation results in one go, wherein the standard translation results are stored in the runtime context; The converter is invoked to read the standard translation result from the runtime context, map the standard translation result to the specific protocol format required by the target third-party cloud platform, and output the adaptation data packet; the specific protocol format is preset according to the interface specification of the target third-party cloud platform.

[0019] This invention provides a standardized implementation method for a dynamic automated translation device. It has the following beneficial effects: 1. This invention generates a linear execution sequence through topological sorting and combines code synthesis and just-in-time compilation techniques to transform the interpreted execution mode into a compiled sequential execution mode. This method determines the data processing path during the compilation phase, avoiding runtime attribute dependency lookups and recursive calculations, thus improving the execution efficiency of heterogeneous protocol data parsing and computation.

[0020] 2. This invention utilizes a custom-designed isolation class loader and an atomic reference replacement mechanism to achieve isolation and smooth updates of device logic. The isolation class loader avoids class conflicts and memory overflow issues between different devices or configuration versions; the atomic reference replacement mechanism ensures that business processing threads can run continuously during configuration updates, avoiding service interruptions.

[0021] 3. This invention decouples business logic from the execution framework through a standard configuration model and runtime context. The standard configuration model unifies the definition of device attribute dependencies, while the runtime context shields the differences in underlying data structures, enabling the system to handle different protocols in a unified manner and reducing the adaptation cost for new device types. Attached Figure Description

[0022] Figure 1 This is a flowchart of a standardized implementation method for a dynamic automated translation device according to the present invention; Figure 2 This is a flowchart of the code synthesis process for this invention; Figure 3 This is a multi-dimensional timing response monitoring diagram of the spindle state according to the present invention. Detailed Implementation

[0023] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] Please see the appendix Figure 1 This invention provides a standardized implementation method for a dynamic automated translation device. This method runs on a smart home IoT platform or edge gateway and other computing devices containing processors. As a standardized specification library or middleware, it achieves dynamic adaptation and rapid access to heterogeneous protocols of massive third-party IoT devices by constructing a digital configuration and execution system.

[0025] Step S1: Receive externally input function attribute definitions and initialize the device attribute set based on the function attribute definitions. Device attribute set It covers all unprocessed functionalities of the device. If the device includes... Function points, device attribute set Represented as .

[0026] For device attribute set For each attribute node, a detailed configuration data structure is built to generate a standard configuration model. The attribute configuration in the standard configuration model includes a unique identifier, data type, executor class name, and an explicitly defined dependency set. The dependency set lists the pre-obtained dependent attribute identifiers required to compute the current attribute node, establishing the logical prerequisite relationships between attributes at the static configuration level.

[0027] Step S2: Read and parse the standard configuration model, and initialize the initial adjacency matrix based on the number of attributes defined in the standard configuration model. The initial adjacency matrix is ​​used to quantify and describe the set of device attributes. The unidirectional dependency relationships between elements are defined. All attribute configurations in the standard configuration model are traversed, and the initial adjacency matrix is ​​numerically filled according to the dependency matrix formula to generate the filled attribute dependency matrix. The specific dependency matrix formula is as follows: ; In the formula: Attribute dependency matrix The Middle Line number The numerical elements of the column; For the device attribute set with index The current attribute node; For the device attribute set with index The dependent attribute node; 1 is a logical truth value indicating the existence of an explicit dependency; 0 is a logical false value indicating the absence of a direct dependency.

[0028] Step S3: Based on the attribute dependency matrix Construct the corresponding directed graph model and perform a full path traversal of the directed graph model using a depth-first search algorithm. If no reverse edge is detected after the traversal, perform a topological sorting calculation on the directed graph model to generate an ordered list of nodes.

[0029] Based on the ordered list of nodes, a linearly ordered execution sequence is ultimately generated. Execution sequence Ensure that for any attribute node in the sequence, its prerequisite dependencies defined in the standard configuration model are all placed before that node.

[0030] Step S4: Pre-built class code skeleton As the base container, and to define the runtime context It serves as a shared memory carrier for data to flow between different logical segments. (Based on the execution sequence) In the order of iteration, business logic fragments corresponding to each attribute node in the standard configuration model are extracted to generate a set of logic code. .

[0031] Applying code synthesis equations to class code skeletons runtime context and logic code set Code synthesis is performed to generate the final composite logic source code. The specific code composition equation is as follows: ; In the formula: This is the source code for complex logic, that is, the final generated source code string containing the complete business flow; It serves as the class code skeleton, a basic code container containing class definitions and execution entry points; Injecting operators into the code indicates the operation of embedding the logic block generated on the right into the specified position of the skeleton on the left; The sequential concatenation operator represents the operation of joining multiple code snippets together in index order to form a complete logical block. This represents the total number of attributes, i.e., the total number of elements in the execution sequence; This is a loop variable representing the sequential index of the currently processed attribute in the execution sequence; A collection of logical codes; This is a fragment of business logic; This is a logic extraction function used to retrieve business logic fragments corresponding to specified attributes from the standard configuration model; To execute the first in the sequence The attribute nodes corresponding to each position; Binding operators to variables indicates operations that map input and output variables in a business logic segment to a shared context; For runtime context, a shared memory reference object used to store and transfer intermediate data.

[0032] Step S5: Call the Just-In-Time (JIT) Compiler interface to process the complex logic source code. It is directly compiled into binary bytecode. A custom isolated class loader is used to load the binary bytecode into the method area of ​​the virtual machine, and it is instantiated into a dynamic translation instance with full processing capabilities. The dynamic translation instance is registered with the device management center, and the old execution instance is atomically replaced.

[0033] When raw data is received from an external device, it is sent to the currently active dynamic translation instance. Within this instance, the data is synthesized strictly according to the logical path defined by the execution sequence within the runtime context. The process involves unidirectional flow, completing the entire conversion chain from parsing raw device data and calculating intermediate parameters to generating standard translation results in one go. A converter maps the standard translation results to the specific protocol format required by the target third-party cloud platform, outputting adapted data packets.

[0034] Step S1: Building a digital configuration system requires defining a standard configuration model that includes dependency constraints. This is achieved through the following steps: Step S101: Receive externally input functional attribute definitions. These definitions typically originate from standard object model description files (such as JSON / XML format) or proprietary protocol specification documents provided by third-party smart device manufacturers. They contain all data acquisition points, control commands, and status register information corresponding to the physical device at the communication protocol layer. Based on these functional attribute definitions, initialize a device attribute set. This initialization process essentially involves mapping and converting device-side physical addresses (such as private protocol message offsets, Modbus register addresses, etc.) to system-side logical functional nodes. If the device contains... If there are 10 functional points to be processed, then the set of device attributes is represented as follows: ,in An integer greater than or equal to 1, representing the total number of device function points.

[0035] Step S102: For the device attribute set Each attribute node in A detailed configuration data structure is constructed to generate a standard configuration model. This standard configuration model is stored using key-value pairs or a custom structure, aiming to unify the data format under different communication protocols. Each attribute configuration in the standard configuration model contains at least four core fields: unique identifier (ID), data type (Type), executor class name (Executor), and dependency set (Dependency Set).

[0036] A unique identifier is used to uniquely mark the attribute node within the system. It is usually named using an English string (such as "filter_decay" [filter cartridge loss]) and serves as the primary key for subsequent dependent indexes. The data type defines the storage format of the attribute value, such as integer, floating-point, boolean, or string, which can be implemented using basic data types in programming languages ​​by those skilled in the art.

[0037] The executor class name specifies the fully qualified classpath name used to execute the specific parsing logic (e.g., com.example.decoder.VoltageExecutor). To ensure compatibility with subsequent dynamic compilation and invocation, all referenced executor classes must implement the system's pre-defined unified standard interface or inherit from the same abstract base class. This interface defines standardized data processing method signatures, thereby decoupling business logic from the system framework.

[0038] Dependency sets are a key feature of this embodiment, which explicitly define the computation of the current attribute node in the form of a list or array. A list of dependency attribute identifiers that must be obtained in advance.

[0039] For example, the calculation logic of the attribute node "Real-time Filter Cartridge Wear Index" depends on the values ​​of two basic attributes: "Ambient PM2.5 Concentration" and "Fan Speed". Therefore, in the configuration of "Real-time Filter Cartridge Wear Index", its dependency set will be defined as a set containing the identifiers of "Ambient PM2.5 Concentration" and "Fan Speed". For basic attributes directly read from device registers or message headers, since they do not require pre-calculated parameters, their dependency set is defined as an empty set. In this way, the logical pre-requisite relationships between attributes are clearly defined at the static configuration level, providing a data foundation for generating the correct execution sequence.

[0040] Step S2: After parsing the standard configuration model, in order for the computer to automatically process the complex logical relationships between attributes, the semantic-level dependencies described by string identifiers need to be transformed into a mathematical matrix expression that is easy for the computer to process. This is achieved through the following steps: Step S201: Read and parse the standard configuration model output in step S102, and extract the total number of attributes defined therein. Based on the total number of attributes Initialize a dimension in memory. The initial adjacency matrix is ​​generated. Considering that attribute dependencies in IoT devices typically exhibit sparse characteristics (i.e., an attribute depends on only a few other attributes), this initial adjacency matrix can be physically stored using a two-dimensional array (such as int[n][n]) or an adjacency list data structure. During the initialization phase, all elements of this matrix are set to 0 by default, indicating that there are no dependencies between attributes in the default state.

[0041] To address the issue that unique string identifiers in the configuration model cannot be directly used as integer matrix indices, a temporary index mapping table needs to be constructed before filling the matrix. This mapping table is typically implemented using a hash map or a dictionary structure, iterating through the device attribute set once. Each attribute node The unique identifier is used as the key, and its traversal index in the set (0 to 1) is used as the key. The attribute set is stored as a value in the table. For example, if the attribute set is... Their identifiers are "pm25_value", "fan_speed", and "filter_decay", respectively, then a system is established. Key-value pair mapping.

[0042] Step S202: Iterate through all attribute configurations in the standard configuration model again, for each current attribute node (denoted as...). Corresponding row index ), read its dependency set field. If the dependency set is not empty, extract each dependency identifier in the dependency set, and use the aforementioned index mapping table to... The time complexity of querying the column index corresponding to the dependency attribute (denoted as ) Subsequently, the initial adjacency matrix is ​​numerically filled according to the attribute dependency matrix construction formula to generate the filled attribute dependency matrix. This step essentially completes the topological mapping from the "business logic graph" to the "directed graph adjacency matrix". The specific dependency matrix formula is as follows: ; In the formula: Attribute dependency matrix The Middle Line number The column's numeric elements can only take the values ​​0 or 1; For the device attribute set with index The current attribute node; For the device attribute set with index The dependent attribute node; 1 is a logical truth value indicating the existence of an explicit dependency relationship, that is, there exists a path in the directed graph consisting of the node. Pointing to node The directed edges; 0 is a logical false value indicating that there is no direct dependency.

[0043] In practical application scenarios, taking the calculation of "filter element real-time wear index" as an example, let's assume the attribute "filter element real-time wear index" (corresponding to the index in the mapping table) The configuration declares a dependency on the attribute "ambient PM2.5 concentration" (corresponding to the index in the mapping table). When traversing to the "Real-time Filter Cartridge Loss Index" attribute, the dependency was identified, and the first element in the matrix was... Line number Column elements Set to 1. This value of 1 physically represents an attribute. It is an attribute The prerequisites for calculation, i.e., attributes The input parameters of the computation function contain attributes The real-time values ​​are obtained. Through full traversal and filling, the attribute dependency matrix describing the topological relationships of the entire device's functional points is finally obtained. .

[0044] Step S3: Obtain the attribute dependency matrix describing the dependencies of all attributes. Next, the static mesh dependency structure needs to be transformed into a linear runtime instruction flow through algorithmic analysis. The core principle is to reduce the dimensionality of the complex dependency topology in two-dimensional space, mapping it to a one-dimensional instruction sequence that a single-threaded processor can execute sequentially, while ensuring that the causal relationships between data are not destroyed during serialization. This is achieved through the following steps: Step S301: Based on the attribute dependency matrix Construct the corresponding directed graph model. This directed graph model consists of a vertex set and a directed edge set, where the vertex set corresponds to the device attribute set. The set of directed edges is directly generated by mapping the non-zero elements of the matrix. Specifically, if the matrix elements... If the value is 1, then a path is generated in the directed graph model consisting of nodes. Pointing to node A directed edge indicates that the data flow is caused by attributes. Flow direction attribute .

[0045] To ensure the generated execution sequence is logically feasible, loop detection must be performed before sorting. A depth-first search (DFS) algorithm is used to traverse the directed graph model. To handle the possibility of disconnected subgraphs within the attribute set (i.e., some attribute groups are unrelated), an outer loop traverses every node in the graph. If a node has not been visited, a DFS search is initiated from that node. During the traversal, an integer state array (or enumeration array) is maintained to record the visit status of each node, including "unvisited" (usually marked as 0), "being visited" (usually marked as 1), and "visited" (usually marked as 2). For any node in the directed graph, if, during the traversal of its adjacent nodes, the state of an adjacent node is found to be "being visited," it indicates that a path exists in the graph leading back to its predecessor node, i.e., a reverse edge exists. This situation corresponds to circular dependencies in the standard configuration model (e.g., attribute A depends on attribute B, and attribute B depends on attribute A), which is an illegal configuration state. Once a reverse edge is detected, the traversal process is immediately terminated and an exception containing information about the loop path is thrown, preventing the incorrect configuration from going live.

[0046] Step S302: After confirming that the directed graph model is a directed acyclic graph (DAG), a topological sorting calculation is performed on the directed graph model to generate an ordered list of nodes. In this embodiment, Kahn's algorithm based on the in-degree table is used. First, the attribute dependency matrix is ​​traversed. For each row, count the attributes of each node. The in-degree of . According to the definition of a matrix, the first The sum of all the values ​​in a row is the attribute. The in-degree value, which physically represents the computed attribute. The number of required but not yet ready prerequisites. Initialize a processing queue, adding all attribute nodes with an initial in-degree of 0 to this queue. An in-degree of 0 indicates that the attribute does not depend on any other attributes in the device; this typically corresponds to raw message parsing, direct register reads, or constant attributes, which are ready for immediate execution.

[0047] Initiate a loop processing logic. As long as the processing queue is not empty, repeatedly perform the following operation: retrieve a node from the head of the processing queue. This is then appended sequentially to the end of the ordered list of nodes. Subsequently, in the attribute dependency matrix... Find all dependent nodes The successor node.

[0048] The specific operation is to retrieve the first element in the matrix. All elements of a column, if a row Corresponding elements If the value is 1, then the attribute is determined. For nodes The direct successor node. The attribute The corresponding in-degree count is decremented by 1. This operation logically indicates that the node... Execution sequence has been entered, attributes One of the prerequisite dependencies has been met. If the attribute is reduced by 1... The in-degree of the property becomes 0, indicating that all its prerequisites are ready, and then the property is... Add to the processing queue and wait for processing.

[0049] Step S303: When the processing queue is empty, check whether the number of elements in the ordered node list is equal to the total number of attributes. If they are equal, the topological sorting was successful; if they are less than... If this is not the case, it indicates the presence of unresolvable circular dependencies in the graph, which will also result in an error. The final generated ordered list of nodes is the linearly ordered execution sequence. This execution sequence It has a unidirectional dependency in execution order, that is, for any position in the sequence attribute nodes All dependency attributes defined in the standard configuration model are necessarily distributed in the sequence index. arrive Within the specified interval. This strict linear order ensures that the subsequently generated code does not require any dynamic dependency checks or backtracking at runtime; it only needs to be executed sequentially to ensure the correct flow of data.

[0050] See appendix Figure 2 Step S4: Generate a linearly ordered execution sequence Next, the code building phase begins. Code synthesis techniques are used to dynamically assemble a composite logic source code containing a complete business flow in memory. Based on the execution sequence, code synthesis techniques are used to dynamically generate the composite logic source code. Essentially, this process transforms the interpreted execution process, which originally required multiple hash lookups and dynamic distributions at runtime, into a sequentially executed instruction stream determined at compile time. This leverages the pipelining optimization capabilities of modern CPUs. Specifically, this is achieved through the following steps: Step S401: Pre-set a class code skeleton As a basic container. Class code skeleton. It is a source code string template conforming to the syntax specifications of the target programming language (such as Java, C++, or C#). To ensure that dynamically generated code can be loaded and invoked by the system, the skeleton internally defines a class structure that implements the system's default standard interface (e.g., set to IDynamicDeviceProcessor). This standard interface specifies a uniform entry method signature (e.g., void process(Context ctx)). The skeleton contains the class's package name declaration, import statements, class name definition, and the signature definition of the core execution method.

[0051] Within the function body of the core execution method, string anchors or placeholders are reserved for code injection. Simultaneously, a runtime context is defined. Runtime context serves as a shared memory carrier for data to flow between different logical segments. It is typically implemented as a strongly typed context object or a key-value container (such as a Map).<String,Object> This is used to store raw data received from the device, intermediate calculation results, and final business data throughout the processing lifecycle of a single request.

[0052] Step S402, according to the execution sequence The order of iteration is used to extract each attribute node in the standard configuration model. The corresponding business logic fragments generate a set of logic code. .

[0053] Specifically, for each attribute node in the sequence It reads the executor class name (Executor) from its configuration. This executor class must conform to the aforementioned standard interface specification. It then generates the source code snippet that calls the core methods of this executor using reflection or string concatenation. For example, if the attribute... The executor is EnvironmentDecoder, and the generated logic fragments are the instantiation statements or singleton call statements of the class.

[0054] Step S403: Apply the code synthesis equation to create the class code skeleton. runtime context and logic code set Code synthesis is performed to generate the final composite logic source code. .

[0055] During this process, string manipulation and semantic binding are performed at the source code level. For each attribute in the sequence... Generate a fragment of business logic With runtime context The code block for binding.

[0056] This binding operation, at the source code level, manifests as the passing of parameters and the assignment of return values: based on attributes The dependency set is automatically generated from the runtime context. The code that reads dependency data (such as ctx.get("dependence_id")) is passed as an input parameter to the executor's processing method; at the same time, it generates code that writes the executor's return result back to the runtime context. The code (such as ctx.put("current_id", result)).

[0057] According to the execution sequence Following the index order, the binding code blocks generated for each attribute are sequentially concatenated end-to-end to form a continuous, complete function body. This function body then replaces the class code skeleton. The placeholders in the code are used to generate complete, compilable composite logic source code. The specific code synthesis equation is as follows: ; In the formula: This is the source code for complex logic, that is, the final generated source code string containing the complete business flow; It serves as the class code skeleton, a basic code container containing class definitions and execution entry points; Injecting operators into the code indicates the operation of embedding the logic block generated on the right into the specified position of the skeleton on the left; The sequential concatenation operator represents the operation of joining multiple code snippets together in index order to form a complete logical block. This represents the total number of attributes, i.e., the total number of elements in the execution sequence; This is a loop variable representing the sequential index of the currently processed attribute in the execution sequence; A collection of logical codes; This is a fragment of business logic; This is a logic extraction function used to retrieve business logic fragments corresponding to specified attributes from the standard configuration model; To execute the first in the sequence The attribute nodes corresponding to each position; Binding operators to variables indicates operations that map input and output variables in a business logic segment to a shared context; For runtime context, a shared memory reference object used to store and transfer intermediate data.

[0058] Through the above synthesis process, the originally discrete configuration logic is solidified into a compact source code file. This source code logically follows the timing determined by topological sorting, ensuring that variables are defined before they are used, and ensuring that the generated code passes syntax checks during the compilation phase, avoiding logical errors caused by missing dependencies at runtime.

[0059] Step S5: Generate composite logic source code using code synthesis technology. Next, the source code string is transformed into an executable instance that can be directly invoked by the computer at runtime. The generated source code is dynamically compiled, loaded, and executed to perform heterogeneous protocol translation tasks. The core of this process lies in transforming the textual logical description into a machine-executable sequence of instructions and loading it into memory, avoiding disk I / O operations throughout to improve response speed. This is achieved through the following steps: Step S501: Invoke the interface of the Just-In-Time (JIT) Compiler, which is typically provided by the programming language runtime environment (e.g., javax.tools.JavaCompiler in a Java environment or Roslyn compilation service in a .NET environment). The JIT Compiler receives the complex logic source code. As input, a compilation task is built, which compiles the data directly into binary bytecode in memory.

[0060] During this process, the compiler's output manager is configured to point to a memory buffer rather than the physical file system, thereby ensuring that the compiled output resides directly in memory. The specific calling method and compilation parameter configuration of the just-in-time compiler can be set by those skilled in the art according to the specific programming language specifications; these are well-known techniques in the field and will not be elaborated upon here.

[0061] After obtaining the binary bytecode, a custom isolated class loader is used to load it into the method area of ​​the virtual machine. The isolated class loader is a subclass of the system's standard class loader, which implements a specific loading strategy by overriding class search methods (such as `findClass`): it prioritizes loading bytecode data from the memory buffer rather than searching in the classpath. This mechanism creates an independent namespace for each device or configuration. By breaking the parent delegation model or configuring a specific loading path, the isolated class loader ensures that even if different devices use the same class name (e.g., all generating a class named `DeviceProcessorImpl`), their class objects are independent at runtime, preventing class conflicts.

[0062] Meanwhile, when configuration updates require unloading old version logic, simply setting the corresponding isolated class loader to an unreachable state (i.e., removing the reference) allows the virtual machine's garbage collection mechanism to automatically reclaim the loader and all loaded class metadata during class unloading checks, thus preventing Metaspace memory overflow. The loaded class is instantiated using reflection, and the instantiated object is upcast to the system's predefined unified standard interface, generating a dynamically translated instance with full processing capabilities. This dynamically translated instance implements the system's predefined unified standard interface, ensuring that external callers do not need to know its internal implementation logic.

[0063] Step S502: Register the newly generated dynamic translation instance to the device management center. The device management center maintains a thread-safe registry (e.g., ConcurrentHashMap) to store the mapping relationship between device identifiers and currently active execution instances.

[0064] The registration process performs an atomic reference replacement operation, which directly updates the key-value reference of the corresponding device identifier in the registry, replacing the pointer to the old instance with a pointer to the newly generated dynamic translation instance. Since the pointer assignment operation is atomic at the computer instruction level, this process ensures the continuity of business processing at the moment of switching, and there will be no service blockage or inconsistent request status.

[0065] Step S503: When raw device data is received from an external device via a message queue or network socket, retrieve the currently active dynamic translation instance from the device management center based on the device identifier. Initialize a new runtime context. (e.g., create an empty Map object or context entity) and encapsulate the device's raw data into that runtime context. Then, the entry method of the dynamic translation instance is called, and the runtime context is transferred. Incoming.

[0066] Within a dynamic translation instance, program instructions are executed strictly according to the logical order determined during the previous code synthesis phase. Data resides in the runtime context. In unidirectional flow, the output of the preceding logic segment is written into... This data is then read as input parameters for subsequent logic segments. Since the code logic has already completed topological sorting and dependency resolution before compilation, the runtime environment does not need to perform any conditional judgments, loop searches, or recursive calculations. It completes the entire data processing flow in one go, from parsing the original device data and calculating intermediate physical quantities (such as voltage and current calculations) to generating the final standard translation results (such as device health, power, and energy consumption statistics).

[0067] After the conversion is complete, the runtime context It stores normalized standard business data. The Converter is invoked to read the runtime context. The final result is as follows. Based on preset mapping rules or the protocol specifications of third-party platforms (such as Alibaba Cloud's Alink protocol JSON format, Tuya Smart's MQTT Topic specification, or Mi Home extension protocol), the converter serializes standard business data into the adaptation data packets required by the target platform, and sends them to the third-party cloud platform through the network interface to complete the final adaptation of heterogeneous protocols.

[0068] See appendix Figure 3 This embodiment is applied to the ecosystem integration scenario of a smart home IoT platform. This dynamic automated translation device, serving as a centralized and standardized specification library on the platform side, aims to solve the problem of rapid access for a large number of heterogeneous devices from third-party manufacturers. Taking the access of a new smart air purifier from a third-party manufacturer as an example, it needs to interface with the manufacturer's proprietary communication protocol (e.g., proprietary binary packets based on TCP), collect real-time device operating environment data, dynamically calculate the real-time filter wear index on the platform side, and finally translate it into the standard JSON format required by the platform for use by the upper-layer APP, enabling rapid, non-stop access for new types of devices.

[0069] Execute step S1 to receive the functional attribute definition for this new smart air purifier. The definition contains three core attribute nodes: (Environmental PM2.5 concentration) (Air purifier fan speed) (Filter element real-time loss index).

[0070] Among them, attributes The identifier is "pm25_value", the data type is floating point, the executor is configured as EnvironmentDecoder, which is responsible for parsing the raw value from the 10th to 13th bytes of the private message, and the dependency set is empty; property The identifier is "fan_speed", the data type is integer, the executor is configured as MotorStatusDecoder, which is responsible for parsing the value from the 14th to 17th bytes of the private message, and the dependency set is empty; property The identifier is "filter_decay", the data type is floating point, the executor is configured as DecayCalculator, and its business logic formula is " Furthermore, its dependency set is explicitly defined as ["pm25_value", "fan_speed"]. Based on the above definition, initialize the device attribute set. At this point, the total number of attributes .

[0071] Next, proceed to step S2 to construct the attribute dependency matrix. First, establish the index mapping table: , , In the initial dimension of After initializing the adjacency matrix, the configuration is traversed. Due to the attributes... The dependency set of (index 2) contains (index 0) and (Index 1), according to the dependency matrix formula, the matrix elements are... and The value is set to 1, and the rest are 0. This matrix numerically quantifies the topology of the calculation logic: the calculation of the filter wear index must be blocked and wait for the PM2.5 concentration and fan speed data to be ready.

[0072] Subsequently, step S3 is executed to generate the execution sequence. A directed graph model is constructed based on the attribute dependency matrix and topologically sorted. The in-degree is calculated to show that: and In-degree is 0. The in-degree is 2. The sorting algorithm first... and Add to the sequence, then remove its pairing. The dependency constraints will eventually lead to Added. The final generated linearly ordered execution sequence The sequence is ("pm25_value", "fan_speed", "filter_decay"). This sequence ensures unidirectional flow during runtime and avoids calculation errors caused by missing parameters when calculating the loss exponent.

[0073] In the code synthesis and execution phases of steps S4 and S5, composite logic source code is dynamically generated using a specification library and then compiled into an execution instance via JIT. When the smart air purifier is running online and reporting status messages at a frequency of 1 second, the data flow strictly follows the sequence. deal with: First, the parsing logic extracts the ambient PM2.5 concentration of 80 μg / m³ from the message. 3 The runtime context is written to the data. Next, the fan speed of 1200 rpm is extracted and written to the context. Finally, the calculation logic reads these two values ​​from the context and executes the formula. The calculated real-time filter loss index of 96 is written back. Finally, the converter reads the standardized data in the context, encapsulates it into a standard JSON format {"device_id":"AirPurifier_X","ts":1718880000,"data":{"pm25":80,"speed":1200,"decay_index":96}} and pushes it to the business layer, realizing the dynamic translation and calculation from the manufacturer's private protocol to the platform's standard indicators.

[0074] Appendix Figure 3 The horizontal axis represents the time axis of device operation (unit: seconds). The chart contains a dual vertical axis: the left vertical axis corresponds to the input raw physical quantity, where the solid line shows the step change process of the purifier fan speed (accelerating from standby to high-speed purification mode of 12000 rpm), and the dotted line shows the fluctuation trend of the ambient PM2.5 concentration over time (for easier observation, this curve is scaled in the figure to achieve spatial separation from the speed curve); the right vertical axis corresponds to the real-time filter wear index dynamically calculated and output by the method of this invention, and is drawn using a dashed line.

[0075] From the appendix Figure 3 It can be clearly observed that as the fan speed increases and the PM2.5 concentration fluctuates, the loss index curve (dashed line) exhibits a synchronous nonlinear growth trend, and precisely matches the time axis at any point. The pre-defined logic verified the real-time performance and accuracy of this solution as a standardized specification library when dealing with complex dependency calculations of multiple types of equipment.

Claims

1. A standardized implementation method for a dynamic automated translation device, characterized in that, Includes the following steps: Receive and initialize the device attribute set based on the externally input functional attribute definitions, and construct a standard configuration model containing dependency constraints; The standard configuration model is parsed and an attribute dependency matrix is ​​constructed. The attribute dependency matrix is ​​then used to quantify the unidirectional dependency relationships between attribute nodes within the device attribute set. Based on the attribute dependency matrix, loop detection and topology sorting calculation are performed to generate a linearly ordered execution sequence; A pre-set class code skeleton and runtime context are used. A set of logical code is extracted based on the execution sequence. A code synthesis equation is applied to synthesize the class code skeleton, the runtime context and the set of logical code to generate composite logical source code. The interface of the just-in-time compiler and the isolated class loader are invoked to transform the complex logic source code into a dynamic translation instance and perform atomic reference replacement. The original device data is then sent into the runtime context of the dynamic translation instance to perform heterogeneous protocol translation tasks.

2. The standardized implementation method of a dynamic automated translation device according to claim 1, characterized in that, The steps for constructing a standard configuration model containing dependency constraints from the set of device attributes specifically include: For each attribute node in the device attribute set, a detailed configuration data structure is constructed to generate the standard configuration model; The attribute configuration in the standard configuration model includes at least a unique identifier, data type, executor class name, and explicitly defined dependency set; The dependency set lists the list of dependent attribute identifiers that must be obtained in advance to compute the current attribute node.

3. The standardized implementation method of a dynamic automated translation device according to claim 1, characterized in that, The specific steps for parsing the standard configuration model and constructing the attribute dependency matrix include: Initialize the initial adjacency matrix based on the number of attributes defined in the standard configuration model; Traverse all attribute configurations in the standard configuration model, fill the initial adjacency matrix with values ​​according to the dependency matrix formula, and generate the filled attribute dependency matrix. The calculation logic of the dependency matrix formula is as follows: When it is detected that the dependent attribute is explicitly declared in the dependency set of the current attribute node, the numerical element determined by the corresponding row index and column index in the initial adjacency matrix is ​​set to a logical true value indicating the existence of an explicit dependency relationship; otherwise, it is set to a logical false value indicating that there is no direct dependency relationship.

4. The standardized implementation method of a dynamic automated translation device according to claim 1, characterized in that, The steps of performing loop detection and topological sorting calculation based on the attribute dependency matrix to generate a linearly ordered execution sequence specifically include: Based on the attribute dependency matrix, a corresponding directed graph model is constructed, and a depth-first traversal algorithm is used to perform a full path traversal of the directed graph model. If a reverse edge is detected during the traversal, an illegal circular dependency is determined to exist in the standard configuration model and an error is reported. If no reverse edge is detected after traversal, the directed graph model is confirmed to be a directed acyclic graph. Perform topological sorting calculations on the verified directed graph model to generate an ordered list of nodes; The execution sequence is generated based on the ordered list of nodes, and the prerequisite dependencies defined in the standard configuration model for any position of the attribute node in the execution sequence are all placed before the corresponding position.

5. The standardized implementation method of a dynamic automated translation device according to claim 1, characterized in that, The application code synthesis equation specifically includes the following steps for synthesizing the class code skeleton, the runtime context, and the logic code set to generate composite logic source code: Perform variable binding operations to map the input and output variables in the logic code set to the runtime context; Perform a sequential concatenation operation to connect multiple mapped code segments end to end to form a complete logical block according to the index order of the execution sequence; Perform code injection to embed the complete logic block into the specified execution entry point of the class code skeleton, and generate the composite logic source code; The class code skeleton is pre-defined based on a preset unified standard interface.

6. The standardized implementation method of a dynamic automated translation device according to claim 1, characterized in that, The runtime context serves as a shared memory carrier for data flow between different logical segments, storing the original data received from the device, intermediate calculation results, and final business data within the processing lifecycle of a single request.

7. The standardized implementation method of a dynamic automated translation device according to claim 1, characterized in that, The steps of calling the just-in-time compiler interface and the isolation class loader to transform the complex logic source code into a dynamic translation instance specifically include: The interface of the just-in-time compiler is invoked to directly compile the complex logic source code into binary bytecode; The binary bytecode is loaded into the method area of ​​the virtual machine using the isolation class loader and instantiated into the dynamic translation instance with full processing capabilities; The isolation class loader is used to prioritize loading bytecode data in the memory buffer and create an independent namespace for each device or each version configuration.

8. The standardized implementation method of a dynamic automated translation device according to claim 1, characterized in that, The steps for performing atomic substitution specifically include: Register the dynamic translation instance to the device management center; Perform an atomic reference replacement operation to directly update the key-value reference of the corresponding device identifier in the device management center, replace the pointer pointing to the old instance with a pointer pointing to the newly generated dynamic translation instance, and establish the currently effective dynamic translation instance.

9. A standardized implementation method for a dynamic automated translation device according to claim 1, characterized in that, The step of sending the raw device data into the runtime context of the dynamic translation instance specifically includes: When the original data from the external device is received, the currently active dynamic translation instance is retrieved from the device management center based on the device identifier; A new runtime context is initialized, and the original device data is encapsulated into the runtime context; The entry method of the dynamic translation instance is called, and the runtime context is passed in, so that the data flows unidirectionally in the runtime context according to the logical path synthesized by the execution sequence.

10. A standardized implementation method for a dynamic automated translation device according to claim 1, characterized in that, The specific steps for performing heterogeneous protocol translation tasks include: The entire process, from parsing the device's raw data and calculating intermediate parameters to generating standard translation results, is completed in one go, and the standard translation results are stored in the runtime context. The converter is invoked to read the standard translation result from the runtime context, map the standard translation result to the specific protocol format required by the target third-party cloud platform, and output the adapted data packet.

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