Multi-scene resource processing method and device

Abstract

The invention discloses a multi-scene resource processing method and device. The method comprises the following steps: carrying out signature processing on a resource capability descriptor and a device communication descriptor; encrypting the signed resource capability descriptor and the signed equipment communication descriptor, and sending the signed resource capability descriptor and the signed equipment communication descriptor to an edge container adapter; analyzing the encrypted resource capability descriptor and the device communication descriptor by utilizing an edge container adapter, and writing the analyzed resource capability descriptor and the device communication descriptor into a hot loading state machine; and when the edge container adapter receives a control instruction based on the unified data model, mapping the control instruction into an instruction which can be understood by the equipment according to the register address or the object mapping in the equipment communication descriptor. According to the invention, the technical problem that the field debugging period is long due to the fact that the brand, the communication protocol and the data model of the distributed energy resources are greatly different in the prior art is solved.

Description

Technical Field

[0001] This invention relates to the field of distributed energy and smart grid technology, and more specifically, to a multi-scenario resource processing method and apparatus. Background Technology

[0002] In recent years, with the widespread application of renewable energy and the development of the energy internet, significant progress has been made in the field of "distributed energy and smart grid" technology. Zero-carbon parks, as an emerging energy management model, integrate various resources such as solar energy, energy storage, electric vehicle charging infrastructure, and building automation systems, aiming to achieve energy self-sufficiency and efficient management within the region. However, current technologies still face many challenges in energy management within zero-carbon parks, mainly in the following aspects:

[0003] 1) The Compatibility Challenge of Heterogeneous Equipment: The energy equipment in the zero-carbon park comes from different manufacturers, covering various types such as photovoltaic inverters, energy storage battery management systems, charging piles, and building HVAC systems. These devices use different communication protocols, such as Modbus-TCP / RTU, IEC 61850, OCPP, BACnet, and MQTT, and their data models and structures differ significantly. This leads to complexity and inconsistency in connecting the equipment to the energy management system.

[0004] 2) Low integration efficiency: Traditional equipment integration methods often follow a "case-by-case" approach, meaning that each new device requires customized development and on-site debugging, typically taking between two weeks and one month. This inefficient integration process not only increases implementation costs but also limits the ability of zero-carbon parks to quickly respond to changes in the energy market.

[0005] 3) Frequent changes to system code: Whenever a new device type or communication protocol needs to be integrated, the existing master station control system often needs to modify its core code, perform regression testing, and deploy online, leading to system version fragmentation. This problem increases the difficulty of system maintenance and affects the system's stability and scalability.

[0006] 4) Tight Coupling of Protocol Parsing and Business Logic: Currently, most gateway devices tightly integrate protocol parsing and business logic processing. This means that every change to the protocol parsing logic may affect the correctness of the business logic. Furthermore, the lack of a unified security authentication mechanism, such as device-level authentication and data integrity verification, creates security vulnerabilities in the transmission of remote control commands, potentially leading to incorrect execution or malicious tampering of the commands.

[0007] 5) Inconsistent semantics for multiple energy flows: When dealing with various energy flows such as electricity, water, heat, and cooling, existing systems often lack a unified semantic framework, making it difficult to effectively schedule and manage different types of energy on the same platform. For example, the representation and processing methods of physical quantities such as electrical power, hot water flow rate, and cooling tons vary significantly across different devices and systems, which limits the realization of cross-medium energy optimization scheduling.

[0008] There is currently no effective solution to the above problems. Summary of the Invention

[0009] This invention provides a multi-scenario resource processing method and apparatus to at least solve the technical problem in related technologies where the existing "one case, one solution" driven development method results in a long on-site debugging cycle due to the large differences in the brands, communication protocols and data models of distributed energy resources.

[0010] According to one aspect of the present invention, a multi-scenario resource processing method is provided, comprising: generating a resource capability descriptor and a device communication descriptor through a graphical interface in a cloud configuration center, wherein the resource capability descriptor is used to define adjustable capabilities and constraint information of the device, and the device communication descriptor is used to describe communication information; performing signature processing on the resource capability descriptor and the device communication descriptor through the cloud configuration center to obtain signed resource capability descriptors and device communication descriptors; encrypting the signed resource capability descriptors and device communication descriptors to obtain encrypted resource capability descriptors and device communication descriptors; and connecting the encrypted resource capability descriptors and device communication descriptors... The device communication descriptor is sent to the edge container adapter; the edge container adapter parses the encrypted resource capability descriptor and the device communication descriptor to obtain the parsed resource capability descriptor and the device communication descriptor, and writes the parsed resource capability descriptor and the device communication descriptor into the hot-load state machine; the edge container adapter uses the parsed device communication descriptor to perform real-time data mapping to convert the original communication data into a unified data model; when the edge container adapter receives a control instruction based on the unified data model, it maps the control instruction into a device-understandable instruction according to the register address or object mapping in the device communication descriptor.

[0011] Optionally, the resource capability descriptor and the device communication descriptor are signed through the cloud configuration center to obtain the signed resource capability descriptor and the device communication descriptor. This includes: performing SHA-256 digital signature and CRC32 verification on the resource capability descriptor and the device communication descriptor in the cloud configuration center to obtain the signed resource capability descriptor and the device communication descriptor.

[0012] Optionally, the signed resource capability descriptor and the device communication descriptor are encrypted to obtain encrypted resource capability descriptors and device communication descriptors, including: encrypting the signed resource capability descriptor and the device communication descriptor using TLS 1.3 and national cryptographic standards to obtain encrypted resource capability descriptors and device communication descriptors.

[0013] Optionally, sending the encrypted resource capability descriptor and the device communication descriptor to the edge container adapter includes: transmitting the encrypted resource capability descriptor and the device communication descriptor to the edge container adapter via OTA service.

[0014] Optionally, after writing the parsed resource capability descriptor and device communication descriptor into the hot-load state machine, the multi-scenario resource processing method further includes: monitoring changes in the configuration file through the file change notification mechanism of the edge container adapter to obtain monitoring results; and starting the hot-load state machine when the monitoring results indicate that new resource capability descriptors and device communication descriptors have arrived to speed up the loading speed of protocol plugins.

[0015] Optionally, real-time data mapping is performed using the parsed device communication descriptor through the edge container adapter to convert the original communication data into a unified data model, including: using the parsed device communication descriptor through the edge container adapter to linearly convert the original data values ​​in the device communication protocol in the original communication data into physical values ​​under the unified data model.

[0016] Optionally, the multi-scenario resource processing method further includes: caching the unified data model data to a local storage medium through the edge container adapter when the device is offline; and automatically retransmitting the unified data model data to the cloud when the device recovers its network.

[0017] According to another aspect of the present invention, a multi-scenario resource processing apparatus is also provided, comprising: a generation unit, configured to generate resource capability descriptors and device communication descriptors through a graphical interface in a cloud configuration center, wherein the resource capability descriptors are used to define adjustable capabilities and constraint information of the device, and the device communication descriptors are used to describe communication information; a signing unit, configured to perform signature processing on the resource capability descriptors and the device communication descriptors through the cloud configuration center to obtain signed resource capability descriptors and device communication descriptors; and an encryption unit, configured to encrypt the signed resource capability descriptors and the device communication descriptors to obtain encrypted resource capability descriptors and device communication descriptors, and to encrypt the encrypted resource capability descriptors. The device communication descriptor is sent to the edge container adapter; a parsing unit is used to parse the encrypted resource capability descriptor and the device communication descriptor using the edge container adapter to obtain the parsed resource capability descriptor and the device communication descriptor, and write the parsed resource capability descriptor and the device communication descriptor into the hot-load state machine; a mapping unit is used to perform real-time data mapping using the parsed device communication descriptor through the edge container adapter to convert the original communication data into a unified data model; a processing unit is used to map the control instruction into a device-understandable instruction according to the register address or object mapping in the device communication descriptor when the edge container adapter receives the control instruction based on the unified data model.

[0018] Optionally, the signature unit includes: a signature module, used to perform SHA-256 digital signature and CRC32 verification on the resource capability descriptor and the device communication descriptor in the cloud configuration center to obtain the signed resource capability descriptor and the device communication descriptor.

[0019] Optionally, the encryption unit includes: an encryption module, configured to encrypt the signed resource capability descriptor and the device communication descriptor using TLS 1.3 and national cryptographic standards to obtain the encrypted resource capability descriptor and the device communication descriptor.

[0020] Optionally, the encryption unit includes: a transmission module, configured to transmit the encrypted resource capability descriptor and the device communication descriptor to the edge container adapter via OTA service.

[0021] Optionally, the multi-scenario resource processing device further includes: a notification unit, used to monitor changes in the configuration file through the file change notification mechanism of the edge container adapter after the parsed resource capability descriptor and the device communication descriptor are written into the hot-loading state machine, and obtain monitoring results; and a startup unit, used to start the hot-loading state machine when the monitoring results indicate that new resource capability descriptors and device communication descriptors have arrived, so as to speed up the loading speed of protocol plugins.

[0022] Optionally, the processing unit includes: a conversion module, configured to linearly convert the original data values ​​in the device communication protocol of the original communication data into physical values ​​under the unified data model using the parsed device communication descriptor through the edge container adapter.

[0023] Optionally, the multi-scenario resource processing device further includes: a caching unit, used to cache the unified data model data to a local storage medium through the edge container adapter when the device is offline; and a retransmission unit, used to automatically retransmit the unified data model data to the cloud when the device recovers its network.

[0024] According to another aspect of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored program, wherein the program executes the multi-scenario resource processing method described in any one of the above embodiments.

[0025] According to another aspect of the present invention, a processor is also provided, the processor being configured to run a program, wherein the program, when running, executes the multi-scenario resource processing method described in any one of the above embodiments.

[0026] According to another aspect of the present invention, a computer program product is also provided, including computer instructions, which, when executed by a processor, perform the multi-scenario resource processing method described in any one of the above embodiments.

[0027] In this embodiment of the invention, resource capability descriptors and device communication descriptors are generated through a graphical interface in a cloud configuration center. The resource capability descriptors define the adjustable capabilities and constraints of the device, while the device communication descriptors describe communication information. The cloud configuration center signs the resource capability descriptors and device communication descriptors to obtain signed resource capability descriptors and device communication descriptors. The signed resource capability descriptors and device communication descriptors are then encrypted to obtain encrypted resource capability descriptors and device communication descriptors, which are then sent to an edge container adapter. The edge container adapter parses the encrypted resource capability descriptors and device communication descriptors to obtain parsed resource capability descriptors and device communication descriptors, which are then written into a hot-load state machine. The edge container adapter uses the parsed device communication descriptors for real-time data mapping to convert the original communication data into a unified data model. When the edge container adapter receives control commands based on the unified data model, it maps the control commands into device-understandable commands according to the register addresses or object mappings in the device communication descriptors. The technical solution provided by this invention achieves the goal of managing UDM and pushing configuration files through a cloud configuration center, performing protocol parsing, data mapping, and security management by edge adapters, and enabling communication between heterogeneous terminals on-site. Through the rapid generation, transmission, and parsing of RCD and DCD, as well as the hot-loading capability of edge container adapters, the access time for new devices is shortened from several weeks in traditional methods to less than 30 minutes, significantly improving the efficiency of device access, reducing the cost and time of on-site debugging, and thus solving the technical problem of long on-site debugging cycles caused by the existing "one case, one solution" driven development method due to the large differences in the brands, communication protocols, and data models of distributed energy resources. Attached Figure Description

[0028] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0029] Figure 1 This is a hardware structure block diagram of a mobile terminal for a multi-scenario resource processing method according to an embodiment of the present invention.

[0030] Figure 2 This is a flowchart of a multi-scenario resource processing method according to an embodiment of the present invention;

[0031] Figure 3 This is an example diagram of the Resource Capability Descriptor (RCD) according to an embodiment of the present invention;

[0032] Figure 4 This is an example diagram of a Device Communication Descriptor (DCD) according to an embodiment of the present invention;

[0033] Figure 5 This is a system architecture diagram of a multi-scenario resource processing method according to an embodiment of the present invention;

[0034] Figure 6 This is a schematic diagram of a hot-loading state machine according to an embodiment of the present invention;

[0035] Figure 7 This is a flowchart of an optional multi-scenario resource processing method according to an embodiment of the present invention;

[0036] Figure 8 This is a schematic diagram of a multi-scene resource processing device according to an embodiment of the present invention.

[0037] The above figures include the following reference numerals:

[0038] 102. Processor; 104. Memory; 106. Transmission device; 108. Input / output device. Detailed Implementation

[0039] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. 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 should fall within the scope of protection of the present invention.

[0040] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0041] As described in the background section, due to the significant differences in brands, communication protocols, and data models among distributed energy resources, existing "case-by-case" development methods result in long on-site debugging cycles. This invention provides a multi-scenario resource processing method and apparatus, a computer-readable storage medium, a processor, and a computer program product, encompassing plug-and-play access to distributed energy resources, communication protocol abstraction, unified data modeling, containerized microservices, and interconnectivity of energy management systems (EMS).

[0042] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0043] The methods and embodiments provided in this invention can be executed on a mobile terminal, a computer terminal, or a similar computing device. Taking running on a mobile terminal as an example, Figure 1 This is a hardware structure block diagram of a mobile terminal for a multi-scenario resource processing method according to an embodiment of the present invention. For example... Figure 1 As shown, a mobile terminal may include one or more ( Figure 1 Only one is shown in the diagram. A processor 102 (which may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.) and a memory 104 for storing data are also shown. The mobile terminal may further include a transmission device 106 for communication functions and an input / output device 108. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the mobile terminal described above. For example, the mobile terminal may also include components that are more... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0044] The memory 104 can be used to store computer programs, such as application software programs and modules, like the computer program corresponding to the multi-scenario resource processing method in this embodiment of the invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, thereby implementing the above-described method. The memory 104 may include high-speed random access memory and non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to the mobile terminal via a network. Examples of the aforementioned networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof. The transmission device 106 is used to receive or send data via a network. Specific examples of the aforementioned networks may include wireless networks provided by the mobile terminal's communication provider. In one instance, the transmission device 106 includes a network interface controller (NIC), which can be connected to other network devices via a base station to communicate with the Internet. In one example, the transmission device 106 may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0045] Example 1

[0046] According to an embodiment of the present invention, a method embodiment of a multi-scenario resource processing method is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0047] Figure 2 This is a flowchart of a multi-scenario resource processing method according to an embodiment of the present invention, such as... Figure 2 As shown, this multi-scenario resource processing method includes the following steps:

[0048] Step S202: In the cloud configuration center, a resource capability descriptor and a device communication descriptor are generated through a graphical interface. The resource capability descriptor is used to define the adjustable capabilities and constraint information of the device, and the device communication descriptor is used to describe the communication information.

[0049] Optionally, the above Resource Capability Descriptor (RCD) JSON template includes the device type, rated parameters, adjustable services, and constraints. Figure 3 This is an example diagram of the Resource Capability Descriptor (RCD) according to an embodiment of the present invention. Figure 4This is an example diagram of a Device Communication Descriptor (DCD) according to an embodiment of the present invention, such as... Figure 3 and Figure 4 As shown, the RCD describes in detail the device's adjustability, rated parameters, and constraints, while the DCD contains detailed information about the device's communication protocol, such as register addresses, object mappings, and communication parameters.

[0050] In this embodiment, basic information and functional parameters of the device are collected in the cloud through an easy-to-use graphical user interface to generate a Resource Capability Descriptor (RCD) and a Device Communication Descriptor (DCD). The RCD details the device's adjustable capabilities, rated parameters, and constraints, while the DCD contains detailed information about the device's communication protocol, such as register addresses, object mappings, and communication parameters.

[0051] Here, a cloud-based configuration center centrally manages and distributes RCD and DCD configuration files, while the edge container adapters parse these files locally and enable real-time communication with devices. This architecture separates policy formulation from execution, improving system flexibility and scalability.

[0052] Step S204: The resource capability descriptor and device communication descriptor are signed through the cloud configuration center to obtain the signed resource capability descriptor and device communication descriptor.

[0053] In this embodiment, the cloud configuration center uses the SHA-256 algorithm to digitally sign the RCD and DCD files, while performing CRC32 verification to ensure file integrity. Then, TLS 1.3 and national cryptographic standards (SM2 / SM3) are used to encrypt the signed files to protect sensitive information during transmission.

[0054] Step S206: Encrypt the signed resource capability descriptor and device communication descriptor to obtain encrypted resource capability descriptors and device communication descriptors, and send the encrypted resource capability descriptors and device communication descriptors to the edge container adapter.

[0055] In this embodiment, the encrypted RCD and DCD files are wirelessly transmitted to each edge container adapter via OTA service. The edge container adapter is responsible for parsing the encrypted files, extracting the original contents of the RCD and DCD, and writing this information into a hot-load state machine to prepare for the fast-start protocol plugin.

[0056] Step S208: Use the edge container adapter to parse the encrypted resource capability descriptor and device communication descriptor to obtain the parsed resource capability descriptor and device communication descriptor, and write the parsed resource capability descriptor and device communication descriptor into the hot-load state machine.

[0057] In this embodiment, the edge container adapter maps the raw communication data uploaded by the device to the unified data model (UDM) in real time according to the device communication protocol information in the DCD, thereby achieving data standardization for different devices and protocols.

[0058] The hot-load state machine allows new RCD and DCD files to take effect instantly in the edge container adapter without restarting the system or device. It quickly activates the corresponding protocol plugins through a dynamic loading mechanism, speeding up device access and reducing on-site debugging time.

[0059] Step S210: Real-time data mapping is performed using the parsed device communication descriptor through the edge container adapter to convert the raw communication data into a unified data model.

[0060] UDM is a standardized data model designed to unify information from different devices and energy flows, enabling upper-layer applications to process data from distributed energy resources in a consistent manner and simplifying the logic of data analysis and decision-making.

[0061] The core fields of the Unified Data Model (UDM) mentioned above are as follows:

[0062] struct UDM {

[0063] std::string deviceId; / / Global UUID

[0064] double value; / / Real-time measurement

[0065] Quantity quantity; / / Enumeration: ELECTRIC_POWER_ACTIVE / THERMAL_FLOW_MASS / …

[0066] int64_t ts; / / Millisecond timestamp

[0067] RegRange ctrlRange; / / Adjustable range [Pmin, Pmax]

[0068] }

[0069] In this way, the main station system only needs to process UDM data and does not need to pay attention to the communication protocol details of specific devices. This avoids version fragmentation caused by adding new device types, simplifies the maintenance of the main station code, and reduces development and operation costs.

[0070] Step S212: When the edge container adapter receives a control instruction based on the unified data model, it maps the control instruction into a device-understandable instruction according to the register address or object mapping in the device communication descriptor.

[0071] In this embodiment, when the edge container adapter receives a UDM-based control instruction, it looks up the register address or object mapping information related to the specific device in the DCD, and converts the general control instruction into a device-specific instruction to ensure that the control intent is effectively executed.

[0072] As described above, in this embodiment of the invention, resource capability descriptors and device communication descriptors are generated through a graphical interface in the cloud configuration center. The resource capability descriptor defines the adjustable capabilities and constraint information of the device, and the device communication descriptor describes the communication information. The cloud configuration center performs signature processing on the resource capability descriptors and device communication descriptors to obtain signed resource capability descriptors and device communication descriptors. The signed resource capability descriptors and device communication descriptors are then encrypted to obtain encrypted resource capability descriptors and device communication descriptors, which are then sent to the edge container adapter. The edge container adapter parses the encrypted resource capability descriptors and device communication descriptors to obtain parsed resource capability descriptors and device communication descriptors, and the parsed resource capability descriptors are then sent to the edge container adapter. Capability descriptors and device communication descriptors are written into the hot-load state machine; real-time data mapping is performed using the parsed device communication descriptors through the edge container adapter to convert the raw communication data into a unified data model; when the edge container adapter receives control commands based on the unified data model, it maps the control commands into device-understandable commands according to the register address or object mapping in the device communication descriptor. This achieves the goal of managing UDM and pushing configuration files through the cloud configuration center, performing protocol parsing, data mapping, and security management by the edge adapter, and enabling communication between heterogeneous terminals in the field. Through the rapid generation, transmission, and parsing of RCDs and DCDs, as well as the hot-load capability of the edge container adapter, the access time for new devices is shortened from several weeks in the traditional method to less than 30 minutes, significantly improving the efficiency of device access and reducing the cost and time of on-site debugging.

[0073] Therefore, the technical solutions provided by the embodiments of the present invention solve the technical problem in the related technologies that the existing "one case, one discussion" driven development method leads to a long on-site debugging cycle due to the large differences in the brands, communication protocols and data models of distributed energy resources.

[0074] Figure 5 This is a system architecture diagram of a multi-scenario resource processing method according to an embodiment of the present invention, such as... Figure 5As shown, the system includes a cloud-based configuration center, edge container adapters, and heterogeneous on-site terminals (photovoltaics, energy storage, charging piles, steam, loads, etc.). The cloud only needs to maintain a unified data model (UDM), and all business modules (scheduling, trading, settlement, visualization) run around the UDM, eliminating the need to modify code for each new device. The edge container has a built-in hot-swappable protocol plugin library supporting multiple protocols such as Modbus-TCP / RTU, IEC 61850, OCPP, BACnet, and MQTT. When adding a device, the user generates two JSON / YAML files through a graphical configuration editor: a Resource Capability Descriptor (RCD) defining the device's adjustable capabilities, rated parameters, and constraints, and a Device Communication Descriptor (DCD) describing register addresses, object mappings, and communication parameters. The configuration center pushes these two files to the edge container via OTA, which completes protocol plugin loading, data mapping, certificate verification, and breakpoint resume settings within 30 seconds, achieving "zero-code" access. Any control command issued by the master station carries only a globally unique DeviceID and target value. The edge container uses DCD to translate the command into register write operations or BACnet method calls that the device can recognize in real time, ensuring precise control down to the specific valve, inverter, or charging pile. This solution enables multi-energy flow devices such as photovoltaics, energy storage, charging piles, combined cooling, heating and power, building air conditioning, steam boilers, and compressed air to operate on the grid under a unified semantic framework. The access cycle is shortened from the traditional 2-4 weeks to less than 30 minutes. The master station version achieves zero branching and permanent reuse, significantly reducing development, debugging, and operation and maintenance costs, while also taking into account the TLS1.3+ national cryptographic dual-certificate security system, meeting the secondary security requirements of the power grid.

[0075] It should be noted that in this embodiment of the invention, the edge box has the following specifications: 4×ARM Cortex-A72 + 4 GB RAM + 32 GB eMMC, with a built-in national cryptographic security chip; communication interfaces include: 2×Gigabit Ethernet, 1×4G / 5G, 1×RS-485, and 1×CAN; the operating system is Ubuntu 20.04 LTS + Docker 20.10 + eBPF network acceleration.

[0076] As described above, the physical system comprises three layers: a unified configuration center in the cloud (microservice cluster, Kubernetes deployment); containerized resource adapters on the edge (ARM / x86 edge boxes, Docker + eBPF network acceleration); and heterogeneous terminals on-site (PV inverters, energy storage EMS, air conditioning PLCs, V2G charging piles, steam flow meters, etc.). The main station implements a "Unified Data Model (UDM)" only once, and all protocol differences are mapped with zero code by the edge containers through "RCD + DCD + protocol plugins"; when adding a new device type, only two JSON / YAML configuration files need to be issued.

[0077] Furthermore, in this embodiment of the invention, the computer program modules are divided as follows: ConfigLoader: responsible for signature verification, CRC check, and hot loading of RCD / DCD; ProtocolPluginMgr: SO dynamic library loader, runtime symbol resolution; DataMapper: based on register / object address mapping table, converts raw packets to UDM; ControlExecutor: reverse maps UDM control instructions to register writes or BACnet method calls; SecurityMgr: TLS1.3 + SM2 / SM3 national cryptographic dual certificate handshake, whitelist, replay detection; OfflineCache: 7-day offline caching, MQTT QoS2 retransmission.

[0078] According to the above embodiments of the present invention, the resource capability descriptor and the device communication descriptor are signed by a cloud configuration center to obtain the signed resource capability descriptor and the device communication descriptor, including: performing SHA-256 digital signature and CRC32 verification on the resource capability descriptor and the device communication descriptor in the cloud configuration center to obtain the signed resource capability descriptor and the device communication descriptor.

[0079] In this embodiment, at the cloud configuration center, the Resource Capability Descriptor (RCD) and Device Communication Descriptor (DCD) are digitally signed using the SHA-256 algorithm, while integrity is verified using the CRC32 algorithm. These operations are performed immediately after the configuration file is generated, ensuring the file's integrity and tamper-proof status before transmission.

[0080] SHA-256 is a secure hash algorithm used to generate a fixed-length hash value for a file; even minor changes to the file content will result in a completely different hash value. The CRC32 algorithm, on the other hand, is used to detect errors during data transmission, ensuring data integrity.

[0081] The introduction of signature and verification mechanisms here significantly enhances the security and reliability of configuration file transmission, preventing data tampering or damage during transmission and ensuring that the information received by the edge container adapter is accurate.

[0082] According to the above embodiments of the present invention, encrypting the signed resource capability descriptor and device communication descriptor to obtain encrypted resource capability descriptors and device communication descriptors includes: encrypting the signed resource capability descriptor and device communication descriptor through TLS 1.3 and national cryptographic standards to obtain encrypted resource capability descriptors and device communication descriptors.

[0083] In this embodiment, the signed and verified RCD and DCD files are encrypted using the TLS 1.3 protocol and national cryptographic standards (SM2 / SM3) to ensure the confidentiality and security of the data during transmission. The encrypted files are then sent to the edge container adapter via a secure channel.

[0084] TLS 1.3, mentioned above, is currently the most secure transport layer security protocol, providing encrypted communication and data integrity protection. SM2 and SM3 are used to implement data encryption and decryption.

[0085] By adopting advanced encryption standards, the security of configuration file transmission has been greatly improved, ensuring the confidentiality and integrity of data, while also meeting the requirements of national cryptographic policies and enhancing the overall security protection capabilities of the system.

[0086] According to the above embodiments of the present invention, sending the encrypted resource capability descriptor and device communication descriptor to the edge container adapter includes: transmitting the encrypted resource capability descriptor and device communication descriptor to the edge container adapter via OTA service.

[0087] In this embodiment, the cloud configuration center sends the encrypted configuration file to the edge container adapter via OTA (Over-The-Air) service, enabling remote automatic updates and configuration deployment. This process requires no physical contact, and the device can automatically receive and apply the latest configuration information.

[0088] OTA is an over-the-air update technology that allows devices to receive software updates via a wireless network without human intervention, reducing the complexity and cost of on-site deployment.

[0089] The adoption of OTA (Over-The-Air) transmission mechanism significantly shortens device access time, reduces the need for on-site debugging, and improves system response speed and operational efficiency. The edge container adapter can instantly receive the latest RCD and DCD, enabling rapid device access and configuration updates.

[0090] According to the above embodiments of the present invention, after the parsed resource capability descriptors and device communication descriptors are written into the hot-loading state machine, the multi-scenario resource processing method further includes: monitoring changes in the configuration file through the file change notification mechanism of the edge container adapter to obtain monitoring results; and starting the hot-loading state machine when the monitoring results indicate that new resource capability descriptors and device communication descriptors have arrived, so as to speed up the loading speed of the protocol plugin.

[0091] In this embodiment, the edge container adapter monitors changes to the RCD and DCD files in real time via a file change notification mechanism, such as inotify. Once a new configuration file is detected, a hot-load state machine is immediately started, allowing the protocol plugin to be loaded and activated without restarting the system, thus enabling rapid onboarding of new devices.

[0092] The aforementioned inotify is a file system event listening mechanism provided by the Linux kernel, which can respond in real time to events such as file creation, modification, and deletion. A hot-load state machine is a software mechanism that dynamically loads configurations and plugins, allowing for immediate processing of new configuration information without requiring a system reboot.

[0093] By combining real-time monitoring and hot-loading mechanisms, the system can quickly respond to the access needs of new devices, reduce the waiting time for device access, improve the system's flexibility and real-time response capabilities, and reduce the risk of interruption caused by system restarts.

[0094] Figure 6 This is a schematic diagram of a hot-loading state machine according to an embodiment of the present invention, as shown below. Figure 6 As shown, the process is: Idle → ConfigArrived → ValidateSign → LoadPlugin → Running, that is, loading the dynamic link library (... The .so file is mapped to the process's virtual address space, and once symbol resolution is complete, it has real-time resolution / control capabilities.

[0095] According to the above embodiments of the present invention, real-time data mapping is performed using the parsed device communication descriptor through the edge container adapter to convert the original communication data into a unified data model, including: using the parsed device communication descriptor through the edge container adapter to linearly convert the original data values ​​in the device communication protocol in the original communication data into physical values ​​under the unified data model.

[0096] In this embodiment, the edge container adapter parses the DCD file and maps the raw communication data into physical values ​​under the Unified Data Model (UDM) in real time based on the register addresses, object mappings and communication parameters therein, thereby achieving standardization and unification of data from different protocols.

[0097] Here, data mapping uses mathematical transformations, such as linear transformations, to convert device-specific communication protocol data into a unified data format, i.e., UDM, thus eliminating data processing barriers caused by differences in communication protocols.

[0098] The introduction of a unified data model simplifies the data processing workflow and improves data compatibility and operability. The main station system does not need to concern itself with the communication protocols of the underlying devices; it only needs to process UDM data, which greatly reduces development and maintenance costs and improves the system's scalability and interoperability.

[0099] According to the above embodiments of the present invention, the multi-scenario resource processing method further includes: caching unified data model data to local storage medium through an edge container adapter when the device is offline; and automatically rewriting the unified data model data to the cloud when the monitoring device restores the network.

[0100] In this embodiment, when the network is interrupted, the edge container adapter caches UDM-based data to local storage media; when the network is restored, the cached data is automatically retransmitted to the cloud to ensure data continuity and integrity.

[0101] This approach utilizes local caching and network recovery retransmission mechanisms to ensure continuous data transmission even in cases of network instability or interruption. The caching mechanism stores data during network outages, while the retransmission mechanism automatically sends the cached data upon network reconnection, preventing data loss.

[0102] By combining a network outage caching mechanism with a network recovery retransmission mechanism, the system's stability and data continuity are ensured when facing network fluctuations, reducing the risk of data loss and enhancing the system's robustness and user experience.

[0103] Figure 7 This is a flowchart of an optional multi-scenario resource processing method according to an embodiment of the present invention, such as... Figure 7 As shown, the software flow and physical steps of the multi-scenario resource processing method are as follows:

[0104] 1) Configuration distribution phase (cloud → edge):

[0105] a) Users select the device model through the Web editor → generate RCD / DCD → call the cloud API / api / v1 / pushConfig.

[0106] b) The file is SHA-256 signed in the cloud to generate config.zip.sig.

[0107] c) The edge container ConfigLoader receives the OTA push → executes: if(!verifySig(zip,sig)) return ERROR; if(!CRC32(zip)) return ERROR;

[0108] d) After decompression, write RCD / DCD to / run / vpp / , triggering inotify → entering the hot-load state machine.

[0109] 2) Protocol plugin loading stage:

[0110] State machines such as Figure 6 As shown: Idle → ConfigArrived → ValidateSign → LoadPlugin → Running. Physical meaning: Loading the dynamic link library (...) The .so file is mapped to the process's virtual address space, and once symbol resolution is complete, it has real-time resolution / control capabilities.

[0111] 3) Real-time data mapping (Southbound → Northbound):

[0112] a) Edge containers periodically (Δt=1 s) read registers → raw frames via Modbus / OCPP / …

[0113] b) The DataMapper performs a linear transformation based on the register table in the DCD:

[0114] value = (raw - offset) scale;

[0115] c) Write the results to UDM → MQTT publish topic / udm / {deviceId}.

[0116] Physical meaning: Converting the raw bit streams of discrete register voltage, current, flow rate, etc. into physical quantities with unified dimensions (kW, m³ / h, ℃).

[0117] 4) Control command execution (Northbound → Southbound):

[0118] a) The main site sends out JSON:

[0119] {"deviceId":"a1b2c3d4","setPoint":-120,"quantity":"ELECTRIC_POWER_ACTIVE"}.

[0120] b) ControlExecutor verifies the DeviceID in the local whitelist → checks the DCD register address → calculates in reverse:

[0121] raw = int(setPoint / scale + offset);

[0122] c) Construct a Modbus Write Single Register or BACnet WriteProperty message via protocol plugin → Execute on field device.

[0123] Physical meaning: Remapping the abstract power value into specific register bits drives the inverter to limit power or change the valve opening.

[0124] 5) Disconnection caching and recovery: When the network is interrupted, OfflineCache serializes the UDM into / var / vpp / cache.db (SQLite), and retransmits it according to the timestamp after the network is restored, ensuring that energy metering and subsidy settlement are not lost.

[0125] It should be noted that, in this embodiment of the invention, the register linear mapping is as follows: Given the original register value raw∈ [0,65535] and the field range [Pmin,Pmax], then: scale = (Pmax - Pmin) / 65535, offset =Pmin. The direction calculation is similar.

[0126] Additionally, it should be noted that in this embodiment of the invention, the response capability is constrained as follows: the maximum adjustable power of the device, Pdown_max, is constrained by SOC and temperature: Pdown_max = min(P_rated, SoC E_rated / Δt_down), where Δt_down is the scheduling period (usually 4 seconds).

[0127] The technical solutions provided by the above embodiments of the present invention have the following beneficial effects: 1) Access cycle: shortened from an average of 2–4 weeks to ≤30 minutes, reducing on-site debugging manpower by more than 90%. 2) Main station code: zero changes and zero regression testing when adding new device types to the main station, version branches from N→1, completely eliminating fragmentation. 3) Protocol support: 20+ industrial / building protocols can be hot-plugged into a single edge container, and protocol switching does not interrupt services. 4) Unified semantics: electricity, water, gas, and heat are all mapped to the same data model, and the cross-media scheduling algorithm reuse rate is 100%. 5) Control precision: DeviceID + whitelist + national cryptographic dual certificates, command recognition accuracy is 100%, and end-to-end latency is <300 ms. 6) System reliability: 7-day edge network outage caching, OTA gray-scale rollback, overall availability ≥99.9%.

[0128] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0129] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0130] Example 2

[0131] According to embodiments of the present invention, a multi-scenario resource processing apparatus for implementing the above-described multi-scenario resource processing method is also provided. Figure 8 This is a schematic diagram of a multi-scene resource processing device according to an embodiment of the present invention, such as... Figure 8 As shown, the device includes: a generation unit 801, a signature unit 803, an encryption unit 805, a parsing unit 807, a mapping unit 809, and a processing unit 811. The device will be described below.

[0132] The generation unit 801 is used to generate resource capability descriptors and device communication descriptors through a graphical interface in the cloud configuration center. The resource capability descriptor is used to define the adjustable capabilities and constraint information of the device, and the device communication descriptor is used to describe the communication information.

[0133] The signature unit 803 is used to perform signature processing on the resource capability descriptor and the device communication descriptor through the cloud configuration center to obtain the signed resource capability descriptor and the device communication descriptor.

[0134] The encryption unit 805 is used to encrypt the signed resource capability descriptor and device communication descriptor to obtain the encrypted resource capability descriptor and device communication descriptor, and send the encrypted resource capability descriptor and device communication descriptor to the edge container adapter.

[0135] The parsing unit 807 is used to parse the encrypted resource capability descriptor and device communication descriptor using the edge container adapter, obtain the parsed resource capability descriptor and device communication descriptor, and write the parsed resource capability descriptor and device communication descriptor into the hot-load state machine.

[0136] Mapping unit 809 is used to perform real-time data mapping using the parsed device communication descriptor through the edge container adapter, so as to convert the raw communication data into a unified data model.

[0137] The processing unit 811 is configured to, when the edge container adapter receives a control instruction based on a unified data model, map the control instruction into a device-understandable instruction according to the register address or object mapping in the device communication descriptor.

[0138] It should be noted that the above-mentioned generation unit 801, signature unit 803, encryption unit 805, parsing unit 807, mapping unit 809 and processing unit 811 correspond to steps S202 to S212 in the above embodiments. The six units and the corresponding steps implement the same instances and application scenarios, but are not limited to the content disclosed in the above embodiments.

[0139] As can be seen from the above, in the scheme described in the above embodiments of the present invention, a generation unit can be used in a cloud configuration center to generate resource capability descriptors and device communication descriptors through a graphical interface. The resource capability descriptor is used to define the adjustable capabilities and constraint information of the device, and the device communication descriptor is used to describe communication information. A signing unit performs signature processing on the resource capability descriptors and device communication descriptors through the cloud configuration center to obtain signed resource capability descriptors and device communication descriptors. An encryption unit encrypts the signed resource capability descriptors and device communication descriptors to obtain encrypted resource capability descriptors and device communication descriptors, which are then sent to the edge container adapter. A parsing unit uses the edge container adapter to parse the encrypted resource capability descriptors and device communication descriptors to obtain parsed resource capability descriptors and device communication descriptors. The parsed resource capability descriptors and device communication descriptors are written into the hot-load state machine. The mapping unit uses the edge container adapter to perform real-time data mapping using the parsed device communication descriptors to convert the original communication data into a unified data model. When the edge container adapter receives control commands based on the unified data model, the processing unit maps the control commands into device-understandable commands according to the register address or object mapping in the device communication descriptor. This achieves the goal of managing UDM and pushing configuration files through the cloud configuration center, performing protocol parsing, data mapping, and security management by the edge adapter, and enabling communication between heterogeneous terminals in the field. Through the rapid generation, transmission, and parsing of RCD and DCD, and the hot-load capability of the edge container adapter, the access time of new devices is shortened from several weeks in the traditional method to less than 30 minutes, which significantly improves the efficiency of device access and reduces the cost and time of on-site debugging.

[0140] Therefore, the technical solutions provided by the embodiments of the present invention solve the technical problem in the related technologies that the existing "one case, one discussion" driven development method leads to a long on-site debugging cycle due to the large differences in the brands, communication protocols and data models of distributed energy resources.

[0141] Optionally, the signature unit includes: a signature module, used to perform SHA-256 digital signature and CRC32 verification on the resource capability descriptor and device communication descriptor in the cloud configuration center to obtain the signed resource capability descriptor and device communication descriptor.

[0142] Optionally, the encryption unit includes: an encryption module for encrypting the signed resource capability descriptor and device communication descriptor using TLS 1.3 and national cryptographic standards to obtain encrypted resource capability descriptors and device communication descriptors.

[0143] Optionally, the encryption unit includes: a transmission module for transmitting the encrypted resource capability descriptor and device communication descriptor to the edge container adapter via OTA service.

[0144] Optionally, the multi-scenario resource processing device further includes: a notification unit, used to monitor changes in the configuration file through the file change notification mechanism of the edge container adapter after the parsed resource capability descriptor and device communication descriptor are written into the hot-loading state machine, and obtain monitoring results; and a startup unit, used to start the hot-loading state machine when the monitoring results indicate that new resource capability descriptors and device communication descriptors have arrived, so as to speed up the loading speed of protocol plugins.

[0145] Optionally, the processing unit includes: a conversion module, used to linearly convert the raw data values ​​in the device communication protocol in the raw communication data into physical values ​​under a unified data model by using the parsed device communication descriptor through the edge container adapter.

[0146] Optionally, the multi-scenario resource processing device also includes: a caching unit, used to cache unified data model data to local storage medium through an edge container adapter when the device is offline; and a retransmission unit, used to automatically retransmit unified data model data to the cloud when the monitoring device restores the network.

[0147] According to another aspect of the present invention, a processor is also provided, which is used to run a program, wherein the program executes any of the above-described multi-scenario resource processing methods during runtime.

[0148] According to another aspect of the present invention, a computer program product is also provided, including computer instructions, which, when executed by a processor, perform any of the above-described multi-scenario resource processing methods.

[0149] According to another aspect of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored program, wherein the program executes the multi-scenario resource processing method described above.

[0150] Optionally, in this embodiment, the computer-readable storage medium may be located in any computer terminal in a group of computer terminals in a computer network, or in any communication device in a group of communication devices.

[0151] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for performing the following steps: In a cloud configuration center, a resource capability descriptor and a device communication descriptor are generated through a graphical interface, wherein the resource capability descriptor is used to define the adjustable capabilities and constraint information of the device, and the device communication descriptor is used to describe communication information; the resource capability descriptor and the device communication descriptor are signed through the cloud configuration center to obtain signed resource capability descriptors and device communication descriptors; the signed resource capability descriptors and device communication descriptors are encrypted to obtain encrypted resource capability descriptors and device communication descriptors; and the encrypted resource capability descriptors are then... Capability descriptors and device communication descriptors are sent to the edge container adapter. The edge container adapter parses the encrypted resource capability descriptors and device communication descriptors to obtain parsed resource capability descriptors and device communication descriptors, and writes the parsed resource capability descriptors and device communication descriptors into the hot-load state machine. The edge container adapter uses the parsed device communication descriptors to perform real-time data mapping to convert the raw communication data into a unified data model. When the edge container adapter receives control instructions based on the unified data model, it maps the control instructions into device-understandable instructions according to the register address or object mapping in the device communication descriptor.

[0152] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for performing the following steps: performing SHA-256 digital signatures and CRC32 verifications on the resource capability descriptor and device communication descriptor in a cloud configuration center to obtain signed resource capability descriptors and device communication descriptors.

[0153] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for performing the following steps: encrypting the signed resource capability descriptor and device communication descriptor using TLS 1.3 and national cryptographic standards to obtain encrypted resource capability descriptors and device communication descriptors.

[0154] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for performing the following steps: transmitting the encrypted resource capability descriptor and device communication descriptor to the edge container adapter via OTA service.

[0155] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for performing the following steps: after writing the parsed resource capability descriptor and device communication descriptor into the hot-load state machine, monitoring the changes in the configuration file through the file change notification mechanism of the edge container adapter to obtain the monitoring results; when the monitoring results indicate that new resource capability descriptors and device communication descriptors have arrived, starting the hot-load state machine to speed up the loading speed of the protocol plugin.

[0156] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for performing the following steps: using an edge container adapter to linearly convert the raw data values ​​in the device communication protocol in the raw communication data into physical values ​​under a unified data model by utilizing the parsed device communication descriptor.

[0157] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for performing the following steps: caching unified data model data to the local storage medium via an edge container adapter while the device is offline; and automatically rewriting the unified data model data to the cloud when the monitoring device recovers the network.

[0158] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0159] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0160] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0161] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0162] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0163] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0164] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0165] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A multi-scenario resource processing method, characterized in that, include: In the cloud configuration center, resource capability descriptors and device communication descriptors are generated through a graphical interface. The resource capability descriptors are used to define the adjustable capabilities and constraint information of the device, and the device communication descriptors are used to describe communication information. The resource capability descriptor and the device communication descriptor are signed by the cloud configuration center to obtain the signed resource capability descriptor and device communication descriptor. The signed resource capability descriptor and the device communication descriptor are encrypted to obtain encrypted resource capability descriptors and device communication descriptors, which are then sent to the edge container adapter. The encrypted resource capability descriptor and device communication descriptor are parsed using the edge container adapter to obtain the parsed resource capability descriptor and device communication descriptor, and then written into the hot-load state machine. The edge container adapter uses the parsed device communication descriptor to perform real-time data mapping, thereby converting the raw communication data into a unified data model. When the edge container adapter receives a control command based on the unified data model, it maps the control command into a device-understandable command according to the register address or object mapping in the device communication descriptor.

2. The multi-scenario resource processing method according to claim 1, characterized in that, The resource capability descriptor and the device communication descriptor are signed by the cloud configuration center to obtain the signed resource capability descriptor and device communication descriptor, including: The resource capability descriptor and the device communication descriptor are digitally signed using SHA-256 and verified using CRC32 in the cloud configuration center to obtain the signed resource capability descriptor and device communication descriptor.

3. The multi-scenario resource processing method according to claim 1, characterized in that, The signed resource capability descriptor and the device communication descriptor are encrypted to obtain encrypted resource capability descriptors and device communication descriptors, including: The signed resource capability descriptor and the device communication descriptor are encrypted using TLS 1.3 and national cryptographic standards to obtain the encrypted resource capability descriptor and the device communication descriptor.

4. The multi-scenario resource processing method according to claim 1, characterized in that, Sending the encrypted resource capability descriptor and the device communication descriptor to the edge container adapter includes: The encrypted resource capability descriptor and the device communication descriptor are transmitted to the edge container adapter via OTA service.

5. The multi-scenario resource processing method according to claim 1, characterized in that, After writing the parsed resource capability descriptor and device communication descriptor into the hot-load state machine, the multi-scenario resource processing method further includes: Changes to the configuration file are monitored through the file change notification mechanism of the edge container adapter, and monitoring results are obtained. When the monitoring results indicate that new resource capability descriptors and device communication descriptors have arrived, a hot-loading state machine is started to speed up the loading of protocol plugins.

6. The multi-scenario resource processing method according to claim 1, characterized in that, The edge container adapter performs real-time data mapping using the parsed device communication descriptor to convert raw communication data into a unified data model, including: The edge container adapter uses the parsed device communication descriptor to linearly convert the original data values ​​in the device communication protocol of the original communication data into physical values ​​under the unified data model.

7. The multi-scenario resource processing method according to claim 1, characterized in that, The multi-scenario resource processing method also includes: During the period when the device is offline, the unified data model data is cached to the local storage medium through the edge container adapter; When the device recovers its network, the unified data model data is automatically retransmitted to the cloud.

8. A multi-scenario resource processing device, characterized in that, include: The generation unit is used to generate resource capability descriptors and device communication descriptors through a graphical interface in a cloud configuration center. The resource capability descriptors are used to define the adjustable capabilities and constraint information of the device, and the device communication descriptors are used to describe communication information. The signature unit is used to perform signature processing on the resource capability descriptor and the device communication descriptor through the cloud configuration center to obtain the signed resource capability descriptor and device communication descriptor; An encryption unit is used to encrypt the signed resource capability descriptor and the device communication descriptor to obtain encrypted resource capability descriptors and device communication descriptors, and then send the encrypted resource capability descriptors and device communication descriptors to the edge container adapter; The parsing unit is used to parse the encrypted resource capability descriptor and the device communication descriptor using the edge container adapter, to obtain the parsed resource capability descriptor and the device communication descriptor, and to write the parsed resource capability descriptor and the device communication descriptor into the hot-load state machine. The mapping unit is used to perform real-time data mapping using the parsed device communication descriptor through the edge container adapter, so as to convert the raw communication data into a unified data model; The processing unit is configured to, when the edge container adapter receives a control instruction based on the unified data model, map the control instruction into a device-understandable instruction according to the register address or object mapping in the device communication descriptor.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein the program executes the multi-scenario resource processing method according to any one of claims 1 to 7.

10. A computer program product comprising computer instructions, characterized in that, When the computer instructions are executed by the processor, the multi-scenario resource processing method according to any one of claims 1 to 7 is performed.

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