Communication interface adaptation method and system based on communication unit interface language

Abstract

The invention belongs to the technical field of data communication, and provides a communication interface adaptation method and system based on a communication unit interface language, and the method comprises the steps: carrying out the parameterized description according to the physical characteristics of various communication channels, and constructing a communication interface language; carrying out abstract description on protocol components and protocol units of the measurement sensing equipment and the communication unit to obtain respective corresponding abstract data; generating a unit object with coding and decoding capabilities by utilizing a communication unit interface language protocol stack according to the abstract data; performing communication protocol coding and decoding between the measurement sensing equipment and the communication unit through the unit object; and after the communication protocol is coded and decoded, acquiring communication pressure data between the measurement sensing equipment and the communication unit, determining a final communication link through the communication pressure data, and performing data communication between the measurement sensing equipment and the communication unit. According to the invention, efficient and stable data interaction between the measurement sensing equipment and the communication unit can be ensured.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of data communication, and particularly relates to a communication interface adaptation method and system based on a communication unit interface language. BACKGROUND

[0002] With the rapid development of measurement sensing technology, data acquisition technology and information communication technology, more and more field measurement sensing devices and communication technology products are widely used in industrial production, environmental protection, urban management and other fields. The development of these technologies greatly improves the efficiency and quality of data collection, and also promotes the improvement of the informatization level of various industries. However, in this process, some problems that need to be solved have been exposed, and the most prominent one is the cross-integration problem between different types of field measurement sensing devices and various communication technology products.

[0003] Currently, there is a lack of unified interface specification between the devices that generate measurement sensing data and analyze and process the data, and various communication technology products of different manufacturers. This means that even in the same application scenario, different brands or models of sensors and communication devices may not be able to work effectively due to interface incompatibility. This incompatibility not only increases the cost and complexity of system integration, but also limits the effective transmission and application range of data, affecting the overall performance and efficiency of the system. The compatibility problem between measurement sensing devices and various communication technology products results in their inability to work effectively together. CN113190366A, entitled External Interface Adaptation Method, Device, Equipment and Storage Medium, although it also mentions the adaptation of communication interfaces, it extracts and processes the method through a pre-set interface configuration table, and then implements interface adaptation according to the processing method. This method has limited accuracy in improving interface adaptation, and lacks sufficient flexibility. At the same time, the current link selection scheme between measurement sensing devices and communication technology products lacks analysis of data communication pressure and data communication constraints, resulting in the selected communication link being unable to well carry the data interaction between them, causing the data communication to fail to achieve the expected effect. SUMMARY

[0004] The purpose of the present application is to provide a communication interface adaptation method and system based on a communication unit interface language to solve the problems of interface adaptation and compatibility.

[0005] To achieve the above-mentioned purpose, the present application adopts the following technical solutions: In a first aspect, the present application provides a communication interface adaptation method based on a communication unit interface language, comprising: Based on the physical characteristics of various communication channels, a communication interface language is constructed by parameterizing its description; at the same time, the protocol components and protocol units of the measurement sensing device and communication unit are abstracted and described to obtain their respective abstract data. Based on the abstract data, a unit object with encoding and decoding capabilities is generated using the communication unit interface language protocol stack; The communication protocol encoding and decoding between the measurement sensing device and the communication unit is performed through the unit object; After the communication protocol is encoded and decoded, the communication pressure data between the measurement sensing device and the communication unit is obtained. The final communication link is determined through the communication pressure data, and data communication between the measurement sensing device and the communication unit is carried out.

[0006] Furthermore, the construction of a communication interface language based on parameterized descriptions of the physical characteristics of various communication channels includes: Based on the interface, channel, and functional characteristics of various communication technologies, corresponding generality data, scalability data, and interoperability data are obtained. Generality refers to the degree to which an interface can be shared and used by multiple different units; scalability refers to the compatibility of the interface; and interoperability refers to the ability of the interface to enable communication between different components or systems. Interface adapters are determined based on the generality data, scalability data, and interoperability data. Specifically, parameterized description objects are generated through the generality data, scalability data, and interoperability data. A communication interface language is constructed based on the parameterized description objects to determine the interface adapter. The interface adapter is equipped with a self-adaptive interface interaction model, which is constructed by the boundaries of the transmission mechanism, signaling data, and service data, as well as preset synchronization sequences and feature byte conversion rules.

[0007] Furthermore, the abstract description of the protocol components and protocol units of the measurement sensing device and communication unit to obtain their respective abstract data includes: The protocol components of measurement sensing devices and communication units include syntax, semantics, frame structure, transmission mode, interface type, network protocol, security policy, application protocol, transmission rate, timing, and user configuration. Protocol units include control information and user data. The process involves acquiring the components and units of each communication protocol, generating a tree-structured model using these components and units in conjunction with a metadata table, constructing a parsing abstract model, and analyzing the dependency relationships of rule statements within the protocol components using this parsing abstract model. Dependencies are obtained by comparing the parameter relationships between rule inputs, rule conditions, rule processing, and rule outputs. A priority extraction module is set for the protocol components and units, defining the granular interface of the inter-process communication mechanism. This priority extraction module determines the common characteristics of the protocol components and units, identifies protocol characteristic description information, and obtains common data and characteristic data based on these common characteristics and the protocol characteristic description information. Abstract data is then generated from the dependency data, common data, and characteristic data.

[0008] Furthermore, the step of generating a unit object with encoding and decoding capabilities based on the abstract data using the communication unit interface language protocol stack includes: Based on the Communication Unit Interface Language (CUMIL) protocol stack, several unit objects with self-encoding and self-decoding capabilities are generated using abstract data. The CUMIL protocol stack includes an interface layer, a protocol frame structure processing layer, a protocol information field processing layer, and a data field processing layer. The CUMIL protocol frame structure includes a frame start identifier field, a length field, a length check field, a control field, an information field, a frame check field, and a frame end identifier field. This protocol stack abstracts all protocol components and protocol units and transforms them into codeable and codecable unit objects.

[0009] Furthermore, the step of encoding and decoding the communication protocol between the measurement sensing device and the communication unit through the unit object includes: Encoding of the communication protocol between the measurement sensing device and the communication unit through the unit object: The SetData interface in the unit object is called. The unit object contains an encoding unit subclass, which has a SetData interface. The SetData interface is used to access the communication unit interface language protocol data structure, including the interface layer, protocol frame structure processing layer, protocol information field processing layer, and data field processing layer. The communication unit interface language protocol data structure is set as the data format and structure of the measurement sensor and the communication unit. The Encode interface in the unit object is called, and the CEncodeBuffer buffer class is accessed according to the Encode interface. The CEncodeBuffer buffer class is used for encoding. The first data member is encoded into the corresponding communication unit interface language protocol frame data segment. The frame header, frame control field, and frame information field of the communication unit interface language data frame are encoded. The encoding interface of the protocol information field processing layer is called to encode the frame length field, frame length check field, frame check field, and frame trailer. Decoding the communication protocol between the measurement sensing device and the communication unit is performed through the communication unit. The Communication Unit Interface Language (CUMIL) protocol stack acts as a protocol converter. During the interface design of the measurement sensor and communication unit, control components with the CUMIL protocol stack are deployed in the corresponding modules of the measurement sensor and communication unit. The stack calls the Decode interface in the unit object, which in turn accesses the CDecodeBuffer class for decoding. The CDecodeBuffer class then uses the CUMIL protocol data structure to decode the communication protocol encoding results of the measurement sensor and communication unit, verifying the validity of the input CUMIL protocol frame data segments.

[0010] Furthermore, after the communication protocol is encoded and decoded, the communication pressure data between the measurement sensing device and the communication unit is obtained, including: Based on preset service data transmission requirements, historical service flows are segmented. These historical service flows include successfully transmitted service data packets from each time slot in the past. The preset service data transmission requirements include preset time slot lengths. The historical service flows are then segmented according to the time slot lengths to obtain time slot service flows. Discrete wavelet transform is performed on the time slot service flows to generate a decomposition coefficient sequence. The relationship between the average transmission delay and the rated transmission delay of service data packets is determined from the time slot service flows, and this is combined with the decomposition coefficient sequence to obtain a communication pressure characteristic sequence. Based on the communication link information set of the historical service flows, communication strength is analyzed. A node communication graph is generated using the analyzed communication strength information. A deep learning algorithm is used to establish a communication pressure analysis model using the node communication graph and the communication pressure characteristic sequence. The communication pressure is then analyzed using this model, ultimately yielding communication pressure data.

[0011] Furthermore, the step of determining the final communication link through communication pressure data and performing data communication between the measurement sensing device and the communication unit includes: The communication link information set is divided into multiple cluster center datasets using a clustering algorithm. A directed acyclic graph (DAG) is then used to correct these datasets, filtering out outliers. Data communication selection constraints are determined based on communication pressure data, and another constraint is established based on data transmission data obtained from historical service flow analysis, prioritizing links with high data transmission rates. These two constraints are combined to arrive at the final selection constraints. Based on these final communication selection constraints, a particle swarm optimization algorithm is used to optimize the clustered data link set to obtain the target communication link. After encoding and decoding the communication protocol between the measurement sensing device and the communication unit, interface self-adaptation is performed based on the corresponding protocol content and a self-adaptive interface interaction model, enabling seamless integration between measurement sensing devices and communication units from different manufacturers.

[0012] Secondly, the present invention provides a communication interface adaptation system based on a communication unit interface language, comprising: The data acquisition module is used to construct a communication interface language by parametrically describing the physical characteristics of various communication channels; at the same time, it abstracts and describes the protocol components and protocol units of the measurement sensing device and the communication unit to obtain their respective abstract data. The data processing module is used to generate unit objects with encoding and decoding capabilities based on abstract data using the communication unit interface language protocol stack. The encoding / decoding module is used to encode and decode the communication protocol between the measurement sensing device and the communication unit through the unit object; The output module is used to obtain communication pressure data between the measurement sensing device and the communication unit after the communication protocol is encoded and decoded. The final communication link is determined through the communication pressure data, and data communication between the measurement sensing device and the communication unit is carried out.

[0013] Thirdly, the present invention provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the communication interface adaptation method based on the communication unit interface language.

[0014] Fourthly, the present invention provides a computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the steps of the communication interface adaptation method based on the communication unit interface language.

[0015] Compared with the prior art, the present invention has the following technical effects: This invention, based on the physical characteristics of various communication channels, employs a parameterization method to abstract interfaces, channels, and functional features to determine a self-adaptive interface interaction model. This model describes the interaction between measurement sensing devices and communication units. By abstracting the protocol components and units of measurement sensing devices and communication units, errors in communication protocol encoding and decoding can be reduced. By using the unit objects generated from the communication unit interface language protocol stack through abstract data to encode and decode the communication protocols of measurement sensing devices and communication units, the problem of interface incompatibility between measurement sensing devices and communication units can be solved. Combined with the determined self-adaptive interface interaction model, the reliability of interface adaptation and connectivity adaptation can be improved, enabling the standardization of communication between different modules and achieving more reliable connectivity adaptation between measurement sensing devices and communication units. Data communication pressure analysis enables the adaptation to large data volume transmissions. By selecting communication links, it is possible to better support data interaction between measurement sensing devices and communication units. The selected communication links can be adapted to the communication efficiency required for the current data communication task, ensuring that the determined communication links can better support data interaction between measurement sensing devices and communication units. Finally, data communication between measurement sensing devices and communication units is carried out according to the communication protocol encoding and decoding results and the target communication link, achieving seamless docking and interface unification between measurement sensing devices and communication units, ensuring effective data flow, and ensuring efficient and stable data interaction between measurement sensing devices and communication units. Attached Figure Description

[0016] Figure 1 This is a flowchart of the present invention.

[0017] Figure 2 This is a schematic diagram of the frame structure of the present invention. Detailed Implementation

[0018] The present invention will be further described below with reference to the accompanying drawings: Example 1, please refer to Figure 1 This invention provides a communication interface adaptation method based on a communication unit interface language, comprising: Based on the physical characteristics of various communication channels, a communication interface language is constructed by parameterizing its description; at the same time, the protocol components and protocol units of the measurement sensing device and communication unit are abstracted and described to obtain their respective abstract data. Based on the abstract data, a unit object with encoding and decoding capabilities is generated using the communication unit interface language protocol stack; The communication protocol encoding and decoding between the measurement sensing device and the communication unit is performed through the unit object; After the communication protocol is encoded and decoded, the communication pressure data between the measurement sensing device and the communication unit is obtained. The final communication link is determined through the communication pressure data, and data communication between the measurement sensing device and the communication unit is carried out.

[0019] This invention, based on the physical characteristics of various communication channels, employs a parameterized method to abstract interface, channel, and functional features, proposing a service-decoupled communication interface model. Based on this, a communication unit interface language is constructed to resolve the interface compatibility issue between measurement sensing devices and communication units. Interface connectivity adaptation is achieved through bidirectional negotiation of the interface language, and the communication efficiency adaptation required for current data communication tasks is addressed through communication pressure analysis and communication link selection. This solution not only resolves the interface compatibility issues between existing measurement sensing devices and various communication technology products but also addresses the problems arising from future upgrades and iterations of various communication technologies. By implementing a communication unit interface language protocol stack, the system obtains unit objects with encoding and decoding capabilities. Using these unit objects for communication protocol encoding and decoding between measurement sensing devices and communication units reduces errors in communication protocol encoding and decoding, achieving reliable and efficient interface adaptation and seamless integration between the two.

[0020] Example 2: This invention provides a communication interface adaptation method based on a communication unit interface language, specifically including: 1. Based on the physical characteristics of various communication channels, a parameterization method is used to abstract the interface, channel, and functional characteristics, and a communication unit interface language is constructed. The interfaces, channels, and functional characteristics of various communication technologies are analyzed to obtain corresponding generality data, scalability data, and interoperability data. Generality refers to the degree to which an interface can be shared by multiple different units; scalability refers to the interface's compatibility; and interoperability refers to the interface's ability to enable communication between different components or systems. Interface adapters are determined based on these data. Specifically, parameterized description objects are generated from the generality, scalability, and interoperability data. A communication interface language is constructed based on these parameterized description objects to determine the interface adapter. The interface adapter includes a self-adaptive interface interaction model, which is constructed from the boundaries of transmission mechanisms, signaling data, and service data, as well as preset synchronization sequences and feature byte conversion rules. This further ensures the accuracy and flexibility of interface adaptation, thereby guaranteeing the effectiveness of data flow. Based on the self-adaptive interface interaction model in the interface adapter and the encoding / decoding results of the communication protocol, interface compatibility between the measurement sensing device and the communication unit is achieved, resulting in more reliable connectivity adaptation between them.

[0021] 2. Abstract the protocol components and protocol units of the measurement sensing device and communication unit to obtain their corresponding abstract data. Protocol components include syntax, semantics, frame structure, transmission method, interface type, network protocol, security policy, application protocol, transmission rate and timing, and user configuration. Protocol units include control information and user data. The process involves acquiring the components and units of each communication protocol (identical to those mentioned above), and using these components and units, combined with a metadata table, to generate a tree-structured model. This model is then used to construct a parsing abstract model. The parsing abstract model is used to analyze the dependency relationships of rule statements within the protocol components. Dependencies are obtained by comparing the parameter relationships between rule inputs, rule conditions, rule processing, and rule outputs. A priority extraction module is set for the protocol components and units, defining the granularity interface for inter-process communication mechanisms. This priority extraction module determines the common characteristics of the protocol components and units. Based on the common characteristics and protocol characteristic descriptions, common data and characteristic data are obtained. Abstract data is then generated from the dependency data, common data, and characteristic data.

[0022] 3. Based on the abstract data, use the communication unit interface language protocol stack to generate unit objects with encoding and decoding capabilities. The Communication Unit Interface Language (CUML) protocol stack utilizes abstract data to generate several unit objects with self-encoding and self-decoding capabilities. The core concept of the CUML protocol stack is to provide a universal encoding / decoding element, which includes an interface layer, a protocol frame structure processing layer, a protocol information field processing layer, and a data field processing layer. The CUML protocol frame structure includes a frame start identifier field, a length field, a length check field, a control field, an information field, a frame check field, and a frame end identifier field. This protocol stack abstracts all protocol components and units into a series of encodeable / decodeable unit objects. All unit objects inherit the basic functions of the encoding / decoding element. These unit objects inherit the basic functions of the basic encoding / decoding components, thus achieving efficient data encoding and decoding while maintaining high flexibility. All unit objects inheriting from the basic encoding / decoding components possess self-encoding and self-decoding capabilities, meaning that each unit object can independently handle its own data encoding and decoding tasks.

[0023] 4. Encode and decode the communication protocol between the measurement sensing device and the communication unit through the unit object. 4.1 Encoding the communication protocol between the measurement sensing device and the communication unit through unit objects. The SetData interface in the unit object is invoked. The unit object contains a coding unit subclass, which also has a SetData interface. This SetData interface is used to access the communication unit interface language protocol data structure, including the interface layer, protocol frame structure processing layer, protocol information field processing layer, and data field processing layer. The communication unit interface language protocol data structure is then configured as the data format and structure for both the measurement sensing device and the communication unit.

[0024] The Encode interface in the unit object is called, and the CEncodeBuffer buffer class is accessed according to the Encode interface. The CEncodeBuffer buffer class is used for encoding and provides variable memory space to support sufficient encoding memory. The first data member is encoded into the corresponding communication unit interface language protocol frame data segment. The frame header, frame control field and frame information field of the communication unit interface language data frame are encoded. The protocol information field processing layer encoding interface is called, and then the frame length field, frame length check field, frame check field and frame tail are encoded to realize the communication protocol encoding of the measurement sensing device and the communication unit, that is, to obtain the communication protocol encoding result.

[0025] The frame structure consists of seven parts: Start of Frame (SOF), Length (LEN), Length Check (LENC), Control (CTRL), Information (INFO), Frame Check (FCS), and End of Frame (EOF). During frame transmission, the lowest address byte of each field is transmitted first. The frame structure is as follows: Figure 2 As shown.

[0026] 4.2 Decoding the communication protocol between the measurement sensing device and the communication unit via the communication unit. The Communication Unit Interface Language (CUMIL) protocol stack acts as a protocol converter, implementing protocol encoding and decoding. In the interface design of measurement sensing devices and communication units, to achieve encoding and decoding, control components with the CUMIL protocol stack are deployed in the corresponding modules of the measurement sensing devices and communication units. The Decode interface in the unit object is called, and the CDecodeBuffer class is accessed through the Decode interface. The CDecodeBuffer class is used for decoding and has a self-checking mechanism to check if there is enough data for decoding.

[0027] The CDecodeBuffer class utilizes the Communication Unit Interface Language (CUMIL) protocol data structure to decode the communication protocol encoding results of the measurement sensing device and the communication unit. It verifies the validity of the input CUMIL protocol frame data segments, such as frame headers, frame trailers, and minimum frame lengths. It decodes the frame length field and length check field to obtain frame length information. Based on the frame length information, it performs non-parametric checks on the frame check field, decodes the frame control field to obtain the frame type, including request frames and general response frames, decodes the information field, and calls the information field processing layer decoding interface to obtain the corresponding protocol content—that is, the communication protocol decoding result. Through the encoding / decoding buffer class, components with encoding / decoding capabilities and their sub-unit objects can encode and decode their corresponding data segments from the buffer. The CUMIL protocol stack acts as a bridge connecting the measurement sensing device and the communication unit, enabling seamless integration between the two.

[0028] 5. Analyze and measure the communication pressure data between the sensing device and the communication unit. Based on preset service data transmission requirements, historical service flows are segmented. These historical service flows include successfully transmitted service data packets from each time slot in the past. The preset service data transmission requirements include preset time slot lengths. The historical service flows are then segmented according to the time slot lengths to obtain time slot service flows. Discrete wavelet transform is performed on the time slot service flows to generate a decomposition coefficient sequence. The relationship between the average transmission delay and the rated transmission delay of service data packets is determined from the time slot service flows. This relationship, combined with the decomposition coefficient sequence, yields a communication pressure characteristic sequence. Based on the communication link information set of the historical service flows, communication strength is analyzed. Communication strength may include message loss rate, transmission frequency, and duration. A node communication graph is generated using the analyzed communication strength information. Using the node communication graph and the communication pressure characteristic sequence, a deep learning algorithm is used to establish a communication pressure analysis model. This model is then used to analyze communication pressure, ultimately yielding communication pressure data. Given the ever-increasing volume of electricity information transmission, communication pressure analysis ensures the stability of data interaction between measurement sensing devices and communication units.

[0029] 6. Determine the final communication link using communication pressure data. The communication link information set is divided into multiple cluster center datasets using a clustering algorithm. A directed acyclic graph (DAG) is then used to refine these datasets, filtering out outliers. Data communication selection constraints are determined based on communication pressure data, prioritizing links with low packet loss rates. Another selection constraint is determined based on data transmission data obtained from historical traffic flow analysis, prioritizing links with high data transmission rates. Combining these two constraints yields the final selection constraints. Based on these final selection constraints, a particle swarm optimization algorithm is used to optimize the clustered data link set, identifying the target communication links. The analyzed communication pressure data determines the required target communication links, ensuring they are adapted to the communication efficiency needed for the current data communication task and better support data interaction between the measurement sensing device and the communication unit.

[0030] 7. Perform data communication between the measurement sensing device and the communication unit. After encoding and decoding the communication protocol between the measurement sensing device and the communication unit, interface self-adaptation is performed based on the corresponding protocol content and a self-adaptive interface interaction model. This enables seamless connection between measurement sensing devices and communication units from different manufacturers, solving the problems of interface unification and data exchange, and allowing the measurement sensing device and communication unit to work collaboratively. After interface self-adaptation, the information data collected by the measurement sensing device is parsed into data bytes and mapped using the Abstract Syntax Notation (ASN.1). The mapped data bytes are then encapsulated using an encapsulation protocol, and the encapsulated information data is transmitted to the communication unit through the communication link.

[0031] In another embodiment of the present invention, a communication interface adaptation system based on a communication unit interface language is provided, which can be used to implement the above-mentioned communication interface adaptation method based on a communication unit interface language. Specifically, the system includes: The data acquisition module is used to construct a communication interface language by parametrically describing the physical characteristics of various communication channels; at the same time, it abstracts and describes the protocol components and protocol units of the measurement sensing device and the communication unit to obtain their respective abstract data. The data processing module is used to generate unit objects with encoding and decoding capabilities based on abstract data using the communication unit interface language protocol stack. The encoding / decoding module is used to encode and decode the communication protocol between the measurement sensing device and the communication unit through the unit object; The output module is used to obtain communication pressure data between the measurement sensing device and the communication unit after the communication protocol is encoded and decoded. The final communication link is determined through the communication pressure data, and data communication between the measurement sensing device and the communication unit is carried out.

[0032] The module division in this embodiment of the invention is illustrative and represents only one logical functional division. In actual implementation, other division methods may be used. Furthermore, the functional modules in the various embodiments of the invention can be integrated into a single processor, exist as separate physical entities, or be integrated into a single module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0033] In another embodiment of the present invention, a computer device is provided, comprising a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions from the computer storage medium to achieve a corresponding method flow or corresponding function. The processor described in this embodiment of the present invention can be used for operation of a communication interface adaptation method based on a communication unit interface language.

[0034] In another embodiment of the present invention, a storage medium is provided, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the computer device and extended storage media supported by the computer device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, the storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the corresponding steps of the communication interface adaptation method based on the communication unit interface language in the above embodiments.

[0035] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0036] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0037] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxesFigure 1 The function specified in one or more boxes.

[0038] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0039] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A communication interface adaptation method based on a communication unit interface language, characterized in that, include: A communication unit interface language is constructed based on parameterized descriptions of various communication channels; Simultaneously, the protocol components and protocol units of the measurement sensing device and communication unit are abstracted and described to obtain their respective abstract data; Based on the abstract data, a unit object with encoding and decoding capabilities is generated using the protocol stack of the communication unit interface language; The communication protocol encoding and decoding between the measurement sensing device and the communication unit is performed through the unit object; After the communication protocol is encoded and decoded, the communication pressure data between the measurement sensing device and the communication unit is obtained. The final communication link is determined through the communication pressure data, and data communication between the measurement sensing device and the communication unit is carried out.

2. The communication interface adaptation method based on communication unit interface language according to claim 1, characterized in that, The construction of the communication unit interface language based on parameterized descriptions of various communication channels includes: Based on the interface, channel, and functional characteristics of various communication technologies, corresponding generality data, scalability data, and interoperability data are obtained. Generality refers to the degree to which an interface can be shared and used by multiple different units; scalability refers to the compatibility of the interface; and interoperability refers to the ability of the interface to enable communication between different components or systems. Interface adapters are determined based on the generality data, scalability data, and interoperability data. Specifically, parameterized description objects are generated through the generality data, scalability data, and interoperability data. A communication interface language is constructed based on the parameterized description objects to determine the interface adapter. The interface adapter is equipped with a self-adaptive interface interaction model, which is constructed by the boundaries of the transmission mechanism, signaling data, and service data, as well as preset synchronization sequences and feature byte conversion rules.

3. The communication interface adaptation method based on communication unit interface language according to claim 1, characterized in that, The abstract description of the protocol components and protocol units of the measurement sensing device and communication unit to obtain their corresponding abstract data includes: The protocol components of measurement sensing devices and communication units include syntax, semantics, frame structure, transmission mode, interface type, network protocol, security policy, application protocol, transmission rate, timing, and user configuration. Protocol units include control information and user data. The process involves acquiring the components and units of each communication protocol, generating a tree-structured model using these components and units in conjunction with a metadata table, constructing a parsing abstract model, and analyzing the dependency relationships of rule statements within the protocol components using this parsing abstract model. Dependencies are obtained by comparing the parameter relationships between rule inputs, rule conditions, rule processing, and rule outputs. A priority extraction module is set for the protocol components and units, defining the granular interface of the inter-process communication mechanism. This priority extraction module determines the common characteristics of the protocol components and units, identifies protocol characteristic description information, and obtains common data and characteristic data based on these common characteristics and the protocol characteristic description information. Abstract data is then generated from the dependency data, common data, and characteristic data.

4. The communication interface adaptation method based on communication unit interface language according to claim 1, characterized in that, The step of generating a unit object with encoding and decoding capabilities based on the abstract data using the protocol stack of the communication unit interface language includes: Based on the Communication Unit Interface Language (CUMIL) protocol stack, several unit objects with self-encoding and self-decoding capabilities are generated using abstract data. The CUMIL protocol stack includes an interface layer, a protocol frame structure processing layer, a protocol information field processing layer, and a data field processing layer. The CUMIL protocol frame structure includes a frame start identifier field, a length field, a length check field, a control field, an information field, a frame check field, and a frame end identifier field. This protocol stack abstracts all protocol components and protocol units and transforms them into codeable and codecable unit objects.

5. The communication interface adaptation method based on the communication unit interface language according to claim 1, characterized in that, The method of encoding and decoding the communication protocol between the measurement sensing device and the communication unit through the unit object includes: Encoding of the communication protocol between the measurement sensing device and the communication unit through the unit object: The SetData interface in the unit object is called. The unit object contains an encoding unit subclass, which has a SetData interface. The SetData interface is used to access the communication unit interface language protocol data structure, including the interface layer, protocol frame structure processing layer, protocol information field processing layer, and data field processing layer. The communication unit interface language protocol data structure is set as the data format and structure of the measurement sensor and the communication unit. The Encode interface in the unit object is called, and the CEncodeBuffer buffer class is accessed according to the Encode interface. The CEncodeBuffer buffer class is used for encoding. The first data member is encoded into the corresponding communication unit interface language protocol frame data segment. The frame header, frame control field, and frame information field of the communication unit interface language data frame are encoded. The encoding interface of the protocol information field processing layer is called to encode the frame length field, frame length check field, frame check field, and frame trailer. Decoding the communication protocol between the measurement sensing device and the communication unit is performed through the communication unit. The Communication Unit Interface Language (CUMIL) protocol stack acts as a protocol converter. During the interface design of the measurement sensor and communication unit, control components with the CUMIL protocol stack are deployed in the corresponding modules of the measurement sensor and communication unit. The stack calls the Decode interface in the unit object, which in turn accesses the CDecodeBuffer class for decoding. The CDecodeBuffer class then uses the CUMIL protocol data structure to decode the communication protocol encoding results of the measurement sensor and communication unit, verifying the validity of the input CUMIL protocol frame data segments.

6. The communication interface adaptation method based on the communication unit interface language according to claim 1, characterized in that, After the communication protocol is encoded and decoded, communication pressure data between the measurement sensing device and the communication unit is obtained, including: Based on preset service data transmission requirements, historical service flows are segmented. These historical service flows include successfully transmitted service data packets from each time slot in the past. The preset service data transmission requirements include preset time slot lengths. The historical service flows are then segmented according to the time slot lengths to obtain time slot service flows. Discrete wavelet transform is performed on the time slot service flows to generate a decomposition coefficient sequence. The relationship between the average transmission delay and the rated transmission delay of service data packets is determined from the time slot service flows, and this is combined with the decomposition coefficient sequence to obtain a communication pressure characteristic sequence. Based on the communication link information set of the historical service flows, communication strength is analyzed. A node communication graph is generated using the analyzed communication strength information. A deep learning algorithm is used to establish a communication pressure analysis model using the node communication graph and the communication pressure characteristic sequence. The communication pressure is then analyzed using this model, ultimately yielding communication pressure data.

7. The communication interface adaptation method based on the communication unit interface language according to claim 1, characterized in that, The process of determining the final communication link through communication pressure data and performing data communication between the measurement sensing device and the communication unit includes: The communication link information set is divided into multiple cluster center datasets using a clustering algorithm. A directed acyclic graph (DAG) is then used to correct these datasets, filtering out outliers. Data communication selection constraints are determined based on communication pressure data, and another constraint is established based on data transmission data obtained from historical service flow analysis, prioritizing links with high data transmission rates. These two constraints are combined to arrive at the final selection constraints. Based on these final communication selection constraints, a particle swarm optimization algorithm is used to optimize the clustered data link set to obtain the target communication link. After encoding and decoding the communication protocol between the measurement sensing device and the communication unit, interface self-adaptation is performed based on the corresponding protocol content and a self-adaptive interface interaction model, enabling seamless integration between measurement sensing devices and communication units from different manufacturers.

8. A communication interface adaptation system based on a communication unit interface language, characterized in that, include: The data acquisition module is used to construct a communication interface language by parametrically describing the physical characteristics of various communication channels. Simultaneously, the protocol components and protocol units of the measurement sensing device and communication unit are abstracted and described to obtain their respective abstract data; The data processing module is used to generate unit objects with encoding and decoding capabilities based on abstract data using the communication unit interface language protocol stack. The encoding / decoding module is used to encode and decode the communication protocol between the measurement sensing device and the communication unit through the unit object; The output module is used to obtain communication pressure data between the measurement sensing device and the communication unit after the communication protocol is encoded and decoded. The final communication link is determined through the communication pressure data, and data communication between the measurement sensing device and the communication unit is carried out.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the communication interface adaptation method based on the communication unit interface language as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the communication interface adaptation method based on the communication unit interface language as described in any one of claims 1 to 7.

Images