A signaling processing method, apparatus, device, storage medium, and product

Abstract

Embodiments of the present application provide a signaling processing method, device, equipment, storage medium and product, which are applied to a cloud node in a signaling processing system, the system also includes an edge node, the method comprises: in response to a signaling addition request carrying target information, determining a signaling type according to the target information, and generating a to-be-executed signaling according to the target information and the signaling type; storing the to-be-executed signaling into a first database which is a distributed database; in the process of monitoring the first database, if it is monitored that the signaling in the first database is updated, the edge node acquires the to-be-executed signaling from the first database and executes the operation indicated by the to-be-executed signaling. By the way of monitoring the first database by the edge node to acquire the to-be-executed signaling and execute it, the embodiments of the present application can execute the task in near real time, reduce the delay of signaling execution, and can cope with time delay sensitive application requests.

Description

Technical Field

[0001] This application relates to computer technology, specifically to a signaling processing method, a signaling processing apparatus, a signaling processing device, a computer-readable storage medium, and a computer program product. Background Technology

[0002] With the development of information technology, edge computing is a technology that provides services closer to the end device by using an open platform that integrates core capabilities of networking, computing, storage, and applications, located near the source of the data or physical object. Compared to cloud computing, edge computing is closer to the end device, which can reduce network load and meet the needs of latency-sensitive applications, thereby improving the efficiency of computing resource utilization.

[0003] Edge computing is managed by the cloud. The cloud can generate pending signaling to be executed by the edge. The edge can periodically poll to check if there are any new pending signaling, and then obtain the latest pending signaling and execute the operation corresponding to the pending signaling.

[0004] While polling at the edge terminal can retrieve the latest pending signaling, excessively long polling cycles can negatively impact the real-time performance of these signals. Conversely, excessively short polling cycles can result in the cloud receiving numerous invalid polling requests, increasing cloud processing load and system risk. Summary of the Invention

[0005] This application provides a signaling processing method, apparatus, device, storage medium, and product. The edge terminal can process newly acquired signaling to be executed in near real-time through monitoring, reducing the latency of signaling processing. This is beneficial for handling latency-sensitive application requests and can be applied to scenarios with high real-time requirements. Furthermore, any type of information can be transmitted between the cloud and the edge terminal through signaling, improving the applicability of the system.

[0006] In a first aspect, embodiments of this application provide a signaling processing method applied to a cloud node in a signaling processing system, wherein the signaling processing system further includes edge nodes, and the method includes:

[0007] In response to a new signaling request carrying target information, the signaling type is determined based on the target information, and a signaling to be executed is generated based on the target information and the signaling type.

[0008] The aforementioned signaling to be executed is stored in a first database, which is a distributed database;

[0009] If the edge node detects an update to the signaling in the first database during its monitoring of the first database, it retrieves the signaling to be executed from the first database and executes the operation indicated by the signaling to be executed.

[0010] In one implementation, the above method further includes:

[0011] Store the aforementioned pending signaling in the second database;

[0012] The signaling in the first database is compared with the signaling in the second database at set time intervals, and the second database is different from the first database;

[0013] If the comparison result indicates that the signaling in the first database is inconsistent with the signaling in the second database, then the signaling in the first database is updated according to the signaling in the second database.

[0014] In one implementation, the process of generating the signaling to be executed based on the target information and the signaling type includes:

[0015] When the above signaling type is a device signaling type, the device to be monitored is determined based on the device information included in the above target information;

[0016] A monitoring signaling message is generated for the aforementioned device to be monitored, and this monitoring signaling message is identified as a signaling message to be executed.

[0017] In one implementation, the above method further includes:

[0018] Receive device status information about the device to be monitored sent by the aforementioned edge node; wherein, the aforementioned device status information is collected by the aforementioned edge node in response to the aforementioned monitoring signaling and by performing status monitoring on the device to be monitored;

[0019] The above status information is displayed on the device management interface located at the aforementioned cloud node.

[0020] Secondly, embodiments of this application provide a signaling processing method applied to an edge node in a signaling processing system, wherein the signaling processing system further includes a cloud node, and the method includes:

[0021] During the monitoring of the first database of stored signaling, if an update of the signaling in the first database is detected, the signaling to be executed is obtained; wherein, the signaling to be executed is generated and stored in the first database by the cloud node in response to the signaling addition request carrying target information, determining the signaling type according to the target information, and generating and storing the signaling in the first database according to the target information and the signaling type, and the first database is a distributed database.

[0022] Perform the operation indicated by the above pending signaling.

[0023] In one implementation, obtaining the signaling to be executed includes:

[0024] The signaling in the first database is compared with the signaling in the third database, and the third database is different from the first database;

[0025] If the comparison result indicates that the signaling in the first database is inconsistent with the signaling in the third database, then the signaling included in the first database but not included in the third database will be determined as the signaling to be executed.

[0026] In one implementation, the above method further includes:

[0027] Store the aforementioned pending signaling in the aforementioned third database;

[0028] If the third database contains the aforementioned signaling to be executed, and the first database does not contain the aforementioned signaling to be executed, then the operation indicated by the aforementioned signaling to be executed is stopped.

[0029] In one implementation, when the signaling type is a device signaling type, the signaling to be executed is a monitoring signaling. The monitoring signaling is generated by the cloud node based on the device information included in the target information to determine the device to be monitored and for the device to be monitored.

[0030] The operations instructed by the aforementioned pending signaling include:

[0031] In response to the above monitoring signaling, the status of the above-mentioned device to be monitored is monitored, and the status information of the above-mentioned device to be monitored is collected;

[0032] The above methods also include:

[0033] The collected status information of the aforementioned devices to be monitored is sent to the cloud node, so that the cloud node can display the status information on the device management interface located on the cloud node.

[0034] Thirdly, embodiments of this application provide a signaling processing apparatus, which includes units for implementing any implementation of the first aspect, or the signaling processing apparatus includes units for implementing any implementation of the second aspect.

[0035] Fourthly, embodiments of this application provide a signaling processing apparatus, which includes a processor adapted to implement a computer program; and a computer-readable storage medium storing the computer program, wherein the computer program is adapted to be loaded by the processor and execute the signaling processing method as described in any implementation of the first aspect, or to execute the signaling processing method as described in any implementation of the second aspect.

[0036] Fifthly, embodiments of this application provide a computer-readable storage medium storing a computer program, the computer program including program instructions, which, when executed by a processor, cause a computer device having the processor to implement the signaling processing method as described in any implementation of the first aspect, or to implement the signaling processing method as described in any implementation of the second aspect.

[0037] Sixthly, embodiments of this application provide a computer program product, which includes a computer program or computer instructions. When the computer program or computer instructions are executed by a processor, they implement the signaling processing method described in any implementation of the first aspect, or implement the signaling processing method described in any implementation of the second aspect.

[0038] In this embodiment, the signaling processing system consists of cloud nodes and edge nodes. The cloud node responds to a new signaling request carrying target information, determines the signaling type based on the target information, and generates a signaling message to be executed based on the target information and the signaling type. The cloud node then stores this signaling message in a first database, which is a distributed database. The edge node continuously monitors the first database. If an update to the signaling message in the first database is detected during monitoring, the edge node can retrieve the newly added signaling message to be executed from the first database and execute the operation indicated by the signaling message. By storing the signaling message to be executed in the first database through the cloud node and monitoring the first database through the edge node, the edge node can obtain near real-time information about signaling changes, thereby retrieving the signaling message and executing the operation indicated by it. This approach is beneficial for handling latency-sensitive application requests and can be applied to scenarios with high real-time requirements. Furthermore, it eliminates the need for edge nodes to periodically poll for the signaling message to be executed, reducing the processing pressure on the cloud node and ensuring system stability. Attached Figure Description

[0039] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0040] Figure 1 This is a schematic diagram of the architecture of a signaling processing system provided in an embodiment of this application;

[0041] Figure 2 This is a schematic diagram of the structure of cloud nodes and edge nodes in a signaling processing system provided in an embodiment of this application;

[0042] Figure 3 This is a schematic flowchart of a signaling processing method provided in an embodiment of this application;

[0043] Figure 4 This is a timing diagram of a signaling processing method provided in an embodiment of this application;

[0044] Figure 5 This is another schematic flowchart of a signaling processing method provided in an embodiment of this application;

[0045] Figure 6 This is a user interface diagram of a signaling processing interface provided in an embodiment of this application;

[0046] Figure 7 This is another user interface diagram of a signaling processing interface provided in an embodiment of this application;

[0047] Figure 8 This is another user interface diagram of a signaling processing interface provided in the embodiments of this application;

[0048] Figure 9 This is another user interface diagram of a signaling processing interface provided in an embodiment of this application;

[0049] Figure 10 This is another flowchart illustrating a signaling processing method provided in an embodiment of this application;

[0050] Figure 11 This is a schematic diagram illustrating a signaling processing method provided in this application embodiment applied to an edge device management scenario;

[0051] Figure 12 This is a schematic diagram illustrating a signaling processing method provided in this application embodiment applied to an edge inference task scenario;

[0052] Figure 13This is a schematic diagram of the structure of a signaling processing device provided in an embodiment of this application;

[0053] Figure 14 This is a schematic diagram of the structure of a signaling processing device provided in an embodiment of this application;

[0054] Figure 15 This is a schematic diagram of the structure of a signaling processing device provided in an embodiment of this application.

[0055] Specific implementation

[0056] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0057] Before providing a further detailed description of the embodiments of this application, the nouns and terms involved in the embodiments of this application will be explained, and the nouns and terms involved in the embodiments of this application shall be interpreted as follows.

[0058] Kubernetes (K8S) is a distributed container cluster management platform that enables automated deployment, scaling, and maintenance of container clusters. Kubernetes allows for rapid application deployment, rapid application scaling, seamless integration with new application features, and optimized hardware resource utilization.

[0059] A container is a means of packaging an application or service and everything it needs to run in an environment-independent manner. It can be understood as a defined package containing the program that needs to be executed and all its dependencies, such as code, system libraries, etc., thereby enabling the packaging or isolation of the application and its entire runtime environment (all the files required to run the application) so that the application can be migrated to different environments (such as development, testing and production environments) while retaining all the application's functionality.

[0060] Process / Service / Instance (Pod): The smallest / simplest basic unit for creation or deployment in Kubernetes. A Pod represents a microservice process running on the cluster, and a microservice process can be called an instance. A microservice process encapsulates a container (or multiple containers) that provides the service, storage resources, an independent network address (Internet Protocol Address, IP address), and policy options for managing and controlling how the container runs.

[0061] Nodes are the fundamental elements of a container cluster. A node can be a virtual machine or a physical machine, its form depending on the business requirements; essentially, it's a machine used to host Pods. Each node contains the basic components needed to run a Pod, such as a container management component (kubelet) or a network proxy component (Kube-proxy). Nodes can be divided into two types: master nodes and worker nodes. The master node is the cluster control node, primarily used to manage and control the entire container cluster. A resource access component (API server) runs on this node, providing the entry point for resource operations and offering mechanisms for authentication, authorization, access control, and Application Programming Interface (API) registration and discovery. The master node also includes a runtime management control component (kube-controller-manager) for maintaining cluster state, such as fault detection, automatic scaling, and rolling updates, as well as a scheduling component (kube-scheduler) for resource scheduling, allocating Pods to appropriate machines according to predefined scheduling policies. Worker nodes can communicate with the master node through the container management component (kubelet) and the network proxy component (Kube-proxy).

[0062] Custom Resource Definitions (CRDs): In addition to built-in resources, container clusters also include user-defined resources. CRDs are an extension mechanism provided by Kubernetes. Users can define a new resource through CRDs, which is equivalent to a custom resource. This custom resource is a specific object defined using a user-defined name and schema. Kubernetes can provide storage and access services for this custom resource.

[0063] ETCD (ETCD Storage System): A distributed key-value database, typically providing data storage services for container clusters and offering an HTTP API for interaction. It's understood that the resources of the aforementioned CRDs are all stored in ETCD. ETCD stores data information for the container cluster, and the resource access component (API server) serves as the unified entry point; any data operation must pass through the API server. Clients (container management component kubelet / scheduler / controller-manager) can monitor the create, update, and delete events of resources in the API server using list-watch and call the corresponding event handling functions based on the event type. The list-watch mechanism can be used to monitor both built-in resources in the container cluster and user-defined resources, i.e., the aforementioned CRDs.

[0064] Statefulset: This means that Pods are not identical replicas. Each Pod has a unique identifier, a unique network identifier, and a unique storage disk.

[0065] Signaling: A string of text information in a specific format, such as a JavaScript Object Notation (JSON) string. Signaling can include different types, which can be defined by the application request / business logic used. For example, it could be specific signaling defined by device management business logic, which could belong to the device signaling type.

[0066] This application proposes a signaling processing scheme applicable to cloud-edge-device signaling processing scenarios. The cloud-edge-device scenario includes three roles: the cloud, the edge, and the terminal device. A cloud-edge-device signaling processing scenario refers to a scenario where signaling (to be executed) is generated by the cloud and executed by the edge device. The data source for the signaling executed by the edge device can be the terminal device, and the content of the signaling is also related to the terminal device. In this application embodiment, a cloud node represents the processing node in the cloud, and an edge node represents the processing node in the edge device. The cloud node can generate the signaling to be executed by the edge node. The edge node can monitor the database storing signaling in the cloud node. When an update to the signaling in the database is detected, the edge node retrieves the newly generated signaling and executes the operation indicated by that signaling. By monitoring signaling data stored on cloud nodes through edge nodes, the system can obtain pending signaling in near real-time after updates to the signaling in the database and execute the operations indicated by that signaling. This avoids high latency in signaling execution caused by long polling cycles, enabling applications with high latency requirements to handle latency-sensitive application requests. It also avoids increased cloud pressure due to excessively short polling cycles, thus improving system stability.

[0067] The signaling processing scheme proposed in this application involves technologies such as cloud technology, cloud computing, artificial intelligence, and machine learning, wherein:

[0068] Cloud technology refers to a hosting technology that unifies hardware, software, and network resources within a wide area network (WAN) or local area network (LAN) to achieve data computation, storage, processing, and sharing. Cloud technology is a collective term for network technology, information technology, integration technology, management platform technology, and application technology applied based on the cloud computing business model. It can form resource pools, be used on demand, and is flexible and convenient. Cloud computing technology will become a crucial support. Backend services of technical network systems require substantial computing and storage resources, such as video websites, image websites, and many portal websites. With the rapid development and application of the internet industry, every item may have its own identification mark in the future, requiring transmission to backend systems for logical processing. Data of different levels will be processed separately, and various industry data will require robust system support, which can only be achieved through cloud computing.

[0069] Cloud computing is a computing model that distributes computing tasks across a large pool of computers, enabling various application systems to access computing power, storage space, and information services as needed. The network providing these resources is called the "cloud." From the user's perspective, resources in the "cloud" appear infinitely scalable, readily available, on-demand, and expandable, with payment based on usage. As a provider of fundamental cloud computing capabilities, a cloud resource pool (referred to as a cloud platform, generally called an IaaS (Infrastructure as a Service) platform) is established. Various types of virtual resources are deployed within this pool for external customers to choose from. The cloud resource pool mainly includes: computing devices (virtualized machines containing operating systems), storage devices, and network devices. Logically, a PaaS (Platform as a Service) layer can be deployed on top of the IaaS layer, and a SaaS (Software as a Service) layer can be deployed on top of the PaaS layer. Alternatively, SaaS can be directly deployed on top of IaaS. PaaS is a platform for running software, such as databases and web containers. SaaS refers to various types of business software, such as web portals and bulk SMS senders. Generally, SaaS and PaaS are upper layers compared to IaaS.

[0070] Artificial Intelligence (AI) is the theory, methods, technology, and application systems that use digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to achieve optimal results. In other words, AI is a comprehensive technology within computer science that attempts to understand the essence of intelligence and produce a new kind of intelligent machine that can react in a way similar to human intelligence. AI studies the design principles and implementation methods of various intelligent machines, enabling them to have perception, reasoning, and decision-making capabilities. AI technology is a comprehensive discipline involving a wide range of fields, encompassing both hardware and software technologies. Fundamental AI technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing, operating (interactive) systems, and mechatronics. AI software technologies mainly include computer vision, speech processing, natural language processing, and machine learning (deep learning).

[0071] Machine learning (ML) is a multidisciplinary field involving probability theory, statistics, approximation theory, convex analysis, and algorithm complexity theory. It specifically studies how computers can simulate or implement human learning behavior to acquire new knowledge or skills and reorganize existing knowledge structures to continuously improve their performance. Machine learning is the core of artificial intelligence and the fundamental way to endow computers with intelligence; its applications span all areas of artificial intelligence. Machine learning and deep learning (DL) typically include techniques such as artificial neural networks, belief networks, reinforcement learning, transfer learning, inductive learning, and instructional learning.

[0072] Based on the above description, please refer to Figure 1 , Figure 1 This is a schematic diagram of the architecture of a signaling processing system provided in an embodiment of this application. Figure 1 As shown, a signaling processing system can include three parts: the cloud, the edge, and the terminal device. The cloud can refer to a cluster deploying the core business system, which may include one or more servers providing cloud computing services. Depending on the specific deployment, the cloud can be categorized into public cloud, centralized cloud, and private cloud, among others. The edge refers to servers or small computing clusters deployed in specific areas, which offload some of the computing / control logic from the core business system; these may include one or more servers. Examples include campus computer rooms and street office servers. The terminal device, often simply called the "end," refers to specific devices that collect data; it is the data source in cloud-edge-end collaboration. Different terminal devices may be used in different application scenarios. For example… Figure 1 As shown, the terminal device can be a smartphone, laptop, desktop computer, tablet, smart speaker, smartwatch, augmented reality (AR) device, virtual reality (VR) device, etc. For example, in a monitoring scenario, the terminal device can also be a monitoring device, such as a network camera (Internet Protocol Camera, IPC) used in campus security, a snapshot camera, or a national standard device. In a vehicle-to-everything (V2X) scenario, the terminal device can also be an in-vehicle terminal, etc.

[0073] It should be noted that, Figure 1 The devices and quantities shown are for illustrative purposes only and do not constitute a limitation on the embodiments of this application. Here, a cloud node can refer to a processing node deployed in the cloud, and can be hosted on... Figure 1 Similarly, in the cloud-based servers or server clusters shown, edge nodes can represent processing nodes deployed at the edge, and can be used to... Figure 1In the signaling processing system of this application, the edge server or server cluster shown can have one or more edge nodes, and this application does not limit this. In the embodiments of this application, the cloud node can be the master node in the container cluster, and one or more edge nodes can be worker nodes in the container cluster. For ease of description, the following description uses an example of a signaling processing system including one cloud node and one edge node.

[0074] In one implementation, a cloud node in the signaling processing system can respond to a signaling addition request carrying target information. The cloud node can determine the signaling type based on the target information and then generate a signaling to be executed based on the target information and the signaling type. The cloud node can then store this signaling to be executed in a first database (ETCD), which is a distributed database. Edge nodes in the signaling processing system include processes (Pods). Edge nodes can monitor the signaling in the first database. If an update to the signaling is detected during monitoring, the edge node can retrieve the signaling to be executed from the first database and execute the operation indicated by the signaling to be executed. Optionally, the edge node can execute the operation indicated by the signaling to be executed through a process within the edge node.

[0075] Please refer to the following: Figure 2 , Figure 2 This is a schematic diagram of the structure of cloud nodes and edge nodes in a signaling processing system provided in an embodiment of this application. It should be noted that, for ease of description, Figure 2 This explanation uses a signaling processing approach involving one cloud node and one edge node as an example, without limiting the number of cloud nodes and edge nodes. In practical applications, it can include at least one cloud node and at least one edge node. Figure 2 As shown, the cloud node includes a business module, a signaling management module, a resource access module (API server), and a client module. The edge node includes a client module and a process, such as process-0 (Pid-0). The business module and signaling management module in the cloud node can be modules running through containers, and can represent a process (service).

[0076] In one embodiment, a business module in a cloud node is used to process business information. This module can be specifically defined based on the business type and usage scenario. For example, if the business information in this module is device information, it can also be defined as a device management module. This business module can use the business information as target information to trigger a signaling addition request. It can also call the interface of the signaling management module to add or delete signaling. The signaling management module can add or delete signaling. It can use the business information as target information, parse the target information to obtain its content, determine the signaling type based on the content, and generate a signaling to be executed based on the target information and signaling type. Further, the signaling management module can store the generated signaling to be executed in a first database, which is a distributed database. Specifically, the signaling management module stores the signaling to be executed in the first database by writing the signaling to be executed, including the target information, into a CRD (Content Request Request) via a resource access module (API server), and then storing it in the first database (ETCD).

[0077] It's important to understand that the first database (ETCD) includes at least one CRD, with different CRDs corresponding to different identifiers (e.g., names). Signaling includes various signaling types. Executable signaling for different signaling types is written to the corresponding CRD. For example, if the target information includes task information, it can be determined that the target information is a task signaling type, and the resource access module (API server) can write the executable signaling generated according to the task signaling type into the corresponding task CRD. Similarly, if the target information includes terminal device information, it can be determined that the target information is a device signaling type, and the resource access module (API server) can write the executable signaling generated according to the device signaling type into the corresponding device CRD. Furthermore, since ETCD is a distributed database, the client module in the edge node is equivalent to the aforementioned container management component (kubelet), which can monitor resources in the resource access module (API server). The client module can store newly added executable signaling under the push change of the resource access module (API server) and notify the edge node (the process in the edge node).

[0078] Furthermore, upon notification from the client module, the processes in the edge node effectively detect, in near real-time, an update to the signaling in the first database of the distributed database. The edge node acquires the latest signaling information, specifically the signaling to be executed including target information, and executes the operation indicated by that signaling. Optionally, the edge node can monitor the signaling of one or more specified CRDs in the first database. When the signaling in one or more monitored CRDs is updated, it can acquire the signaling to be executed for each monitored CRD and execute the operation indicated by the signaling to be executed in each CRD through a process (process-0 / Pod-0).

[0079] Optionally, the edge node may include multiple processes. When generating signaling to be executed, the cloud node can schedule the signaling, that is, add scheduling information to the signaling, specifying that a certain process in the edge node will execute the operation indicated by the signaling. Then, after obtaining the signaling, the edge node can determine the process through the scheduling information and execute the operation indicated by the specified process. The processes in the edge node can be deployed using a statefulset. The cloud node can obtain the process load of each process and determine the scheduling information based on the process load and process identifier. Alternatively, the signaling processing system may include multiple edge nodes, each of which may include at least one process. Similarly, the cloud node can obtain the process load of each process and determine the scheduling information based on the process load and process identifier. After detecting an update in the signaling, each edge node obtains the signaling to be executed, which includes target information and scheduling information. Each edge node determines whether the process corresponding to the process identifier in the scheduling information is included. If an edge node determines that the process corresponding to the process identifier is not included, the edge node will not execute the operation indicated by the signaling to be executed. If an edge node determines that the process corresponding to the process identifier is included, the edge node will execute the operation indicated by the signaling to be executed through the process corresponding to the process identifier.

[0080] In this embodiment, the signaling processing system consists of cloud nodes and edge nodes. The cloud node responds to a new signaling request carrying target information, determines the signaling type based on the target information, and generates a signaling message to be executed based on the target information and the signaling type. The cloud node then stores this signaling message in a first database, which is a distributed database. The edge node continuously monitors the first database. If an update to the signaling message in the first database is detected during monitoring, the edge node can retrieve the newly added signaling message to be executed from the first database and execute the operation indicated by the signaling message. By storing the signaling message to be executed in the first database through the cloud node and monitoring the first database through the edge node, the edge node can obtain near real-time information about signaling changes, thereby retrieving the signaling message and executing the operation indicated by it. This approach is beneficial for handling latency-sensitive application requests and can be applied to scenarios with high real-time requirements. Furthermore, it eliminates the need for edge nodes to periodically poll for the signaling message to be executed, reducing the processing pressure on the cloud node and ensuring system stability.

[0081] It is understood that the signaling processing system described in the embodiments of this application is for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and does not constitute a limitation on the technical solutions provided in the embodiments of this application. As those skilled in the art will know, with the evolution of system architecture and the emergence of new business scenarios, the technical solutions provided in the embodiments of this application are also applicable to similar technical problems.

[0082] Based on the above description Figure 1 and Figure 2 The signaling processing methods involved in the signaling processing system shown can be found in [reference needed]. Figure 3 , Figure 3 This is a flowchart illustrating a signaling processing method provided in an embodiment of this application. The signaling processing method is implemented through interaction between a cloud node 31 and an edge node 32, and may include the following steps 301-305, wherein:

[0083] 301. In response to a new signaling request carrying target information, the cloud node determines the signaling type based on the target information and generates a signaling to be executed based on the target information and the signaling type.

[0084] In one implementation, the cloud node can respond to a signaling addition request. This signaling addition request may be triggered by a business module within the cloud node. The signaling addition request carries target information, which may be business information from different categories of services. The cloud node can receive or trigger the signaling addition request and then respond to it. The cloud node can provide a user interface to receive the signaling addition request. For example, this user interface could be a user interface for a specific category of services in the business system. The user can input business information through the user interface, and this business information is then used as the target information to trigger the signaling addition request. The cloud node can also receive or trigger the signaling addition request in other ways, which are not limited in this application.

[0085] Furthermore, the cloud node determines the signaling type based on the target information and generates execution signaling based on the target information and signaling type. The target information can be business information for a specific category of service, and may vary depending on the application scenario or business category. For example, the target information may include task information, device information, billing information, etc. The cloud node can parse the target information, determine its content, and then determine the signaling type based on the content of the target information and the content conditions of each signaling type. The signaling can carry any type of target information, such as text information or structured data like the aforementioned task information, device information, and billing information. For ease of description, this application uses task signaling type and device signaling type as examples; this application does not limit the type of signaling.

[0086] After determining the signaling type, the cloud node can generate a signaling message to be executed based on the target information and the signaling type. This signaling message instructs the edge node (the process within the edge node) to perform an operation. Different signaling messages can be generated based on different signaling types and target information to obtain the signaling message to be executed. For example, if the signaling type is determined to be a task signaling message, the cloud node can generate a task signaling message based on the task information included in the target information and designate this task signaling message as the signaling message to be executed. If the signaling type is determined to be a device signaling message, the cloud node can identify the device to be monitored based on the device information included in the target information, generate a monitoring signaling message based on the device to be monitored, and designate this monitoring signaling message as the signaling message to be executed.

[0087] Optionally, the signaling processing system provided in this application embodiment may include cloud nodes and edge nodes. Each edge node may include at least one process (Pod), and the signaling processing system may also include multiple edge nodes, each edge node including at least one process (Pod). Each process is deployed as a stateful set, and each process corresponds to a process identifier. The cloud node can determine the process used to execute the operation indicated by the signaling to be executed. That is, the signaling to be executed also includes scheduling information determined according to the process identifier. This scheduling information can be used to indicate the target process that needs to execute the aforementioned signaling to be executed, and the target process is one of the processes in the aforementioned signaling processing system.

[0088] 302. The cloud node stores the aforementioned pending signaling in the first database.

[0089] In one implementation, the first database can be a distributed database, such as ETCD. The cloud node can write the generated signaling to be executed into a CRD, i.e., store it in the ETCD as a CRD. The signaling management module in the cloud node can pass the signaling to be executed generated based on the target information to the resource access module (API server), which then stores the signaling in the ETCD. Since the target information can be business information of different service types, the cloud node can determine the CRD to be written based on the signaling type of the target information; that is, different signaling types can be written into different CRDs, and different CRDs correspond to different identifiers (names).

[0090] In one implementation, the cloud node can also store the signaling to be executed generated based on the target information in a second database, which is different from the first database. The second database can be a cache database or a local database; for example, it could be a MySQL database. MySQL is a relational database that can receive commands from Structured Query Language (SQL) statements and perform corresponding operations. These commands can include various operations such as deleting files and retrieving file content. The first database is a Kubernetes (K8S) database, and the second database can be understood as a local database relative to the first. The cloud node can synchronize all or part of the signaling from the first database to the second database at set time intervals (such as the first time interval), thereby maintaining data consistency.

[0091] In one implementation, the cloud node can store the signaling to be executed generated based on the target information in a second database. Then, at a set time interval (e.g., a second time interval), it compares the signaling in the first database with that in the second database. If the comparison indicates a discrepancy between the two databases, the cloud node can update the signaling in the first database based on the signaling in the second database. This is because the resource access module (API server) in the cloud node asynchronously stores the signaling to be executed (transmitted by the signaling management module). Therefore, the API server might fail to store the signaling to be executed, meaning the first database might not contain it. However, the signaling management module is unaware of this. Thus, the cloud node can use a second database (not the same as the first database) as a backup and periodically compare the signaling stored in the first and second databases, thereby maintaining database consistency.

[0092] 303. Edge nodes monitor the aforementioned first database.

[0093] In one implementation, since the first database is a distributed database (i.e., ETCD), edge nodes can monitor this first database, specifically the ETCD, to check for updates to signaling. The edge nodes monitor CRDs (Content Registries) within the ETCD, and can specify the CRD to monitor based on its identifier. After the cloud node stores the signaling to be executed in the corresponding CRD in the ETCD, its resource access module (API server) can push the client module to update the stored signaling. Following the update, the cloud node notifies the edge nodes (processes within these edge nodes) that the signaling in the first database has been updated. Subsequently, the edge nodes (processes within these edge nodes) monitoring the CRD complete the monitoring upon notification from the client module and can retrieve the stored signaling from the first database.

[0094] 304. If an edge node detects an update to the signaling in the first database mentioned above, it will obtain the signaling to be executed.

[0095] In one implementation, the edge node monitors one or more CRDs in the first database (i.e., ETCD). When one of the CRDs is updated, the edge node (a process within the edge node) receives a notification from the client module and then obtains the signaling to be executed. Specifically, the edge node can obtain the CRD or all signaling stored in the ETCD and compare it with the signaling previously stored in the third database. The signaling included in the first database (or CRD) but not included in the third database is identified as the signaling to be executed, and the operation indicated by the signaling to be executed is then executed. The third database differs from the first database; it can be a cache database or a local database of the edge node. Similar to the second database, it can be understood as the edge node's local database relative to the first database. Edge nodes can store signaling in a third database, different from the first database. Similarly, the edge node acts as a backup. Upon detecting a change in signaling, it retrieves the (changed) signaling from the first database (the latest signaling content) and compares it with the signaling in the third database (i.e., the backup of the previously stored signaling in the first database). Based on the comparison result, it can determine the updated signaling in the first database. Optionally, the third database can be the same MySQL database as the second database, with the cloud node and edge node storing data in different tables. Alternatively, the third database and the second database can be different MySQL databases, with the cloud node and edge node storing data in different databases; this application does not impose any limitations on this.

[0096] 305. The edge node executes the operation indicated by the above-mentioned pending signaling.

[0097] In one implementation, when an edge node detects an update to the signaling in the first database and the addition of new signaling to be executed, the edge node can parse the signaling to be executed to determine its specific signaling type. For example, when the cloud node determines that the signaling type of the target information is a device signaling type, the specific signaling type of the signaling to be executed can be a monitoring signaling. The target information includes device information, which is used to indicate the device to be monitored by the edge node (the process within the edge node). Furthermore, the edge node (the process within the edge node) can respond to the monitoring signaling, perform status monitoring on the device to be monitored, and collect the status information of the device to be monitored. The edge node can also send the collected status information of the device to be monitored to the cloud node, which can then display the status information in its device management interface. As another example, when the cloud node determines that the signaling type of the target information is a task signaling type, the specific signaling type of the signaling to be executed can also be a task signaling. The target information includes task information, which is used to instruct the edge node (the process in the edge node) to perform a task, such as a task involving AI processing, such as face recognition, image processing, video processing, audio recognition, etc. The data source of the task comes from the device on the terminal device. Furthermore, the edge node can respond to the task signaling and execute the operation specified in the task signaling. Optionally, the edge node can also send the execution result of the task signaling to the cloud node.

[0098] Please refer to the following: Figure 4 , Figure 4 This is a timing diagram of a signaling processing method provided in an embodiment of this application. Figure 4 As shown, the upper part represents the cloud portion, the middle part represents the edge portion, and the lower part represents the terminal device portion. The cloud portion includes the service modules, signaling management modules, resource access modules (API servers), first database, and second database of cloud nodes; the edge portion includes edge nodes, and each edge node includes processes; the terminal device portion includes devices. Optionally, the edge portion may include multiple edge nodes, and each edge node includes at least one process. Figure 4 Let's take an example where the edge part includes an edge node, and this edge node contains a process.

[0099] Specifically, the business module of the cloud node can store business information (target information) in the second database, trigger a signaling addition request, and in response to the signaling addition request, call the interface of the signaling management module in the cloud node to add the signaling to be executed. The signaling management module determines the signaling type according to the target information, and generates the signaling to be executed according to the target information and the signaling type. Then, the signaling management module can store the generated signaling to be executed in the second database and store it in the first database (ETCD), which is a distributed database, in the form of CRD. The signaling management module can write the corresponding signaling type CRD in the first database according to the signaling type of the target information, or write the signaling to be executed into the corresponding CRD according to the signaling type of the generated signaling to be executed.

[0100] Furthermore, the edge node (the process in the edge node) monitors the signaling in the first database, which is a distributed database. Specifically, it monitors the signaling in one or more specified CRDs in the first database. If the signaling of at least one CRD in the one or more specified CRDs in the first database is updated, the edge node can obtain the signaling to be executed from the first database, parse the signaling to be executed, and execute the operation indicated by the signaling to be executed.

[0101] In this embodiment, the signaling processing system consists of cloud nodes and edge nodes. The cloud node responds to a new signaling request carrying target information, determines the signaling type based on the target information, and generates a signaling message to be executed based on the target information and the signaling type. The cloud node then stores this signaling message in a first database, which is a distributed database. The edge node continuously monitors the first database. If an update to the signaling message in the first database is detected during monitoring, the edge node can retrieve the newly added signaling message to be executed from the first database and execute the operation indicated by the signaling message. By storing the signaling message to be executed in the first database through the cloud node and monitoring the first database through the edge node, the edge node can obtain near real-time information about signaling changes, thereby retrieving the signaling message and executing the operation indicated by it. This approach is beneficial for handling latency-sensitive application requests and can be applied to scenarios with high real-time requirements. Furthermore, it eliminates the need for edge nodes to periodically poll for the signaling message to be executed, reducing the processing pressure on the cloud node and ensuring system stability.

[0102] Based on the above description, please refer to Figure 5 , Figure 5 This is another schematic flowchart of a signaling processing method provided in an embodiment of this application. This signaling processing method can be... Figure 3 In the illustrated embodiment, the cloud node 31 executes the signaling processing method, which may include the following steps 501-502, wherein:

[0103] 501. In response to a new signaling request carrying target information, determine the signaling type based on the target information, and generate a signaling to be executed based on the target information and the signaling type.

[0104] In one implementation, the cloud node can respond to a signaling addition request carrying target information. This signaling addition request may be triggered by a business module within the cloud node, and the target information may be business information of the business module. For example, the target information may be task information executed by an edge node, device information used to indicate a terminal device (device on the terminal device), billing information, etc., and this application does not limit this. The cloud node can provide a user interface, whereby the user inputs business information through a terminal device, and the business module receives the user-input business information to trigger a signaling addition request. The cloud node can also receive business information sent by other nodes or other devices, using this business information as target information to trigger a signaling addition request, and this application does not limit this. Furthermore, the cloud node determines the signaling type based on the target information and generates a signaling to be executed based on the target information and the signaling type.

[0105] In one implementation, the cloud node can determine the signaling type of the target information based on the content it includes. Each signaling type can be a pre-defined signaling type of the cloud node, and each signaling type corresponds to different content conditions. The cloud node can match the content included in the target information with these content conditions to determine the signaling type of the target information. For example, if the target information contains task information, the cloud node can determine that the signaling type of the target information is a task signaling type; if the target information contains device information, the cloud node can determine that the target information is a device signaling type, and so on. The cloud node can then generate the signaling to be executed based on the target information and the signaling type.

[0106] Optionally, the signaling processing system provided in this application embodiment may include cloud nodes and edge nodes. Each edge node may include multiple processes (Pods). In scenarios where the signaling processing system includes multiple processes, each process is deployed as a stateful set, and each process corresponds to a different identifier. The cloud node can obtain the process identifiers and process loads of each process, and then determine the target process for executing the signaling to be executed. The target process is one of the processes. Furthermore, the cloud node can determine scheduling information based on the process identifier of the target process and add this scheduling information during the generation of the signaling to be executed. The scheduling information is used to instruct the target process to execute the signaling to be executed.

[0107] In one implementation, the cloud node can also respond to signaling deletion requests. These requests delete generated signaling, which can be either unexecuted or currently being executed. It's understood that the business modules in the cloud node are for processing business information. Both adding and deleting signaling requests can be handled by these modules. The cloud node can also provide a user interface to receive and respond to user-triggered signaling deletion requests. Furthermore, the business modules in the cloud node can invoke the signaling management module to synchronously delete the deleted signaling from the first database (corresponding CRD), effectively stopping the edge nodes from executing the deleted signaling.

[0108] Please refer to the following: Figures 6-8 , Figures 6-8 These are all user interface diagrams illustrating a signaling processing interface provided in embodiments of this application. The explanation will take the application of a signaling processing scheme in a monitoring scenario as an example. Figure 6 As shown, this user interface is a device management interface located on a cloud node. The displayed devices are the monitoring devices in the monitoring scenario. This device management interface can include a grouping section and a device section. The grouping section allows administrators to group devices in the cloud, with each group corresponding to a group identifier. The device section includes multiple monitoring devices. The device management interface displays the device name, device ID, device type, edge area, status, creation time, and operations for each device. Operations include editing, deleting, and viewing data. The edge area can be a geographically defined region or a logically defined region by administrators; this application does not limit this. The status refers to the status information of the monitoring device. In this device management interface located on the cloud node, users can add new terminal devices by triggering the add device control. The cloud node can then provide services such as... Figure 7 The user interface shown.

[0109] like Figure 7As shown, IPC devices can be added in the monitoring scenario. The addition interface can include device information input by the user, such as device name, manufacturer, model, IP address, port, username, password, Real-Time Streaming Protocol (RTSP) address, cluster type, edge region, and device group. The newly added IPC device can then be saved by triggering a save control, which in turn triggers a signaling addition request. The target information can be the aforementioned input device information. The cloud node can determine the device signaling type based on the target information, identify the device to be monitored based on the device information of the IPC device included in the target information, generate monitoring signaling for the device to be monitored (the IPC device), and designate the monitoring signaling as the signaling to be executed. Optionally, in the monitoring scenario, the terminal devices can include IPCs, snapshot cameras, and national standard monitoring devices, etc. The user interface for adding new devices differs for different types of devices.

[0110] Furthermore, the cloud node can store the signaling to be executed in a CRD within the first database (ETCD) of the distributed database, such as a device CRD, whose identifier could be, for example, a "tiedgedevice". The edge node can then detect updates to the "tiedgedevice's" CRD, obtain the signaling to be executed, and perform status monitoring on the IPC device, collecting its status information. The edge node can access the IPC device via the RTSP address to collect its status information, thus achieving status monitoring. The edge node can then send the collected status information to the cloud node, which can display this information in its device management interface. Figure 8 As shown, the dashed box contains the newly added IPC device, and the current status information collected by the edge node is online.

[0111] Please refer to the following: Figure 9 , Figure 9 This is a user interface diagram illustrating a signaling processing interface provided in an embodiment of this application. In this embodiment, the signaling processing method can be applied to scenarios involving edge inference tasks. Edge inference tasks refer to specific inference tasks processed at the edge, where the inference task refers to a specific AI algorithm task that uses a pre-trained model deployed at the edge to process data. For example, the edge can perform algorithmic recognition based on video streams / images input to a pre-trained model, such as face recognition, vehicle recognition, etc. Target information may include task information used to perform the inference task. The cloud node can determine the signaling type as a task signaling type based on the target information and generate signaling to be executed.

[0112] Figure 9 This is the task management interface, which includes one or more tasks. Each task has a task name, task ID, task description, workflow, workflow type, modifier, modification time, and operation, including pause, delete, start, and edit. Figure 9 Taking the task of identifying very important persons (VIPs) under device monitoring as an example, the task name is edge-vip, the task ID is task-1, the workflow is VIP monitoring and identification - cloud-edge, the workflow type is cloud-edge, the modifier is superadmin, and the modification time is 2022.1.08 19:30:53. This task information includes instructions for edge nodes to perform face recognition on images or video streams captured by monitoring devices (e.g., IPCs), thereby obtaining face recognition results. Then, the edge node can send the face recognition results to the cloud node, which can then match the face images in the VIP face image library with the face images identified by the edge node to determine whether the monitored user is a VIP. Specifically, such as... Figure 9 As shown, the VIP recognition task deployed by this device can be expanded to display specific task information, including the data source name, execution ID, data source type, execution start time, execution end time, and status. This specific task information can be information related to the terminal device within the task. The data source name can be the name of the data source captured by the network camera, such as "people" ("people / 35010000001320000003") or "other" ("test / 35010000001320000004"). The data source type can be a smart device. The execution start time is the time when the task begins, which is also the time when the edge node acquires the video stream from the network camera for face recognition processing. Currently, the task is in progress, so there is no execution end time yet.

[0113] It is understood that in the implementation of the system in this application, data such as device information and task information input by the user are involved. When the above embodiments of this application are applied to system products or technologies, the relevant data must be authorized or agreed to by the relevant user, and the collection, use and processing of the relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0114] 502. Store the above-mentioned signaling to be executed in the first database.

[0115] In one implementation, after generating the signaling to be executed, the cloud node can store the signaling in a first database, specifically writing it into the corresponding CRD. The signaling management module in the cloud node can then pass the signaling to be executed to the resource access module (API server). The resource access module (API server) stores the signaling in the first database (ETCD) as a CRD. ETCD is a distributed database storing multiple CRDs, such as CRDs for task signaling (identified as `tiedgetask`) and CRDs for device signaling (identified as `tiedgedevice`). Optionally, the different CRDs can be specified by the signaling management module when passing the signaling to be executed to the resource access module (API server), or determined by the resource access module (API server) based on the signaling type of the signaling to be executed. This application does not limit this.

[0116] In one implementation, the cloud node can also store the signaling to be executed in a second database. This second database differs from the first database; it can be any database other than the first database (ETCD), such as a cache database or a local database. The signaling management module in the cloud node can store the signaling to be executed in the second database, either in a table within the second database or persistently by writing to a file. This application does not limit this. The cloud node can synchronize all or part of the signaling in the second database to the first database at set intervals (such as a first time interval) to ensure data consistency. This is because the resource access module (API server) processes the signaling to be executed transmitted by the signaling management module asynchronously. Therefore, the resource access module (API server) may fail to store the signaling to be executed in the first database initially, but the signaling management module is unaware of this. Thus, when there are no new signaling to be executed, the signaling management module in the cloud node can periodically synchronize all or part of the signaling in the second database to the first database at set intervals (the first time interval), i.e., re-upload the signaling through the resource access module (API server). The synchronous signaling can be all signaling or partial signaling, such as signaling to be executed generated within a certain time period, or multiple signaling for a pre-set project. This application does not limit this.

[0117] In one implementation, after storing the signaling to be executed in the second database, the cloud node can compare the signaling in the first database (ETCD) with the signaling in the second database (e.g., a MySQL database) at set time intervals (e.g., a second time interval). If the comparison result indicates that the signaling in the second database is inconsistent with the signaling in the first database, the cloud node can update the signaling in the first database based on the signaling in the second database. Specifically, the business modules in the cloud node can periodically call the signaling management module to query all current signaling and obtain whether the signaling information of each signaling is consistent with the signaling information stored in the second database. If they are inconsistent, the business module can call the signaling management module again to update the signaling in the first database based on the signaling in the second database. The business module's query for all current signaling is obtained by the signaling management module sending a query request to the resource access module (API server). This ensures that if the resource access module (API server) fails to upload signaling after asynchronous processing, resulting in inconsistent data, or if a business module in the cloud node deletes a signaling message in the second database and successfully calls the signaling management module interface to delete the signaling message, but the deletion operation fails after the signaling management module sends a deletion request to the resource access module (API server), the signaling message is not actually deleted and becomes a zombie signaling message.

[0118] In this embodiment, the signaling processing system consists of cloud nodes and edge nodes. The cloud node responds to a new signaling request carrying target information, determines the signaling type based on the target information, and generates a signaling message to be executed based on the target information and the signaling type. The cloud node then stores this signaling message in a first database, which is a distributed database. The edge node continuously monitors the first database. If an update to the signaling message in the first database is detected during monitoring, the edge node can retrieve the newly added signaling message to be executed from the first database and execute the operation indicated by the signaling message. By storing the signaling message to be executed in the first database through the cloud node and monitoring the first database through the edge node, the edge node can obtain near real-time information about signaling changes, thereby retrieving the signaling message and executing the operation indicated by it. This approach is beneficial for handling latency-sensitive application requests and can be applied to scenarios with high real-time requirements. Furthermore, it eliminates the need for edge nodes to periodically poll for the signaling message to be executed, reducing the processing pressure on the cloud node and ensuring system stability.

[0119] Please refer to the following: Figure 10 , Figure 10 This is another schematic flowchart of a signaling processing method provided in an embodiment of this application. This signaling processing method can be... Figure 3In the embodiment shown, edge node 32 executes the signaling processing method, which may include the following steps 1001-1002, wherein:

[0120] 1001. During the monitoring of the first database of stored signaling, if an update of the signaling in the first database is detected, the signaling to be executed is obtained.

[0121] In one implementation, since the first database (ETCD) is a distributed database, edge nodes can monitor the first database storing signaling. Specifically, edge nodes (processes within edge nodes) monitor the CRDs in the first database. An edge node can monitor updates to signaling in one or more CRDs. The edge node specifies the CRD to monitor by specifying its identifier. For example, an edge node can monitor a task signaling type CRD (like the edge inference task mentioned above) by inputting the identifier "tiedgetask," and a device signaling type CRD (like the monitoring signaling mentioned above) by inputting the identifier "tiedgedevice." The monitoring is performed using the list-watch mechanism in Kubernetes. This mechanism consists of two parts: the first part, the list, which lists all signaling in the specified CRD during initial monitoring, implemented using short HTTP connections; and the second part, the watch, which monitors resource change events of the specified CRD, implemented using long HTTP connections. The client module of the edge node can monitor resource changes in the resource access module (APIserver) and notify the edge node (processes within the edge node).

[0122] In one implementation, after an edge node (a process within the edge node) retrieves all signaling in a CRD based on a list, it can cache all signaling in a third database, which is different from the first database. Then, by monitoring changes to the signaling in a specified CRD within the first database (i.e., the distributed database ETCD), and detecting an update in the first database, it can retrieve all signaling in the first database (which may contain all signaling from a specified CRD) through the resource access module (API server). This retrieved signaling is then compared with the previously cached signaling in the third database. If the comparison indicates a discrepancy between the signaling in the first and third databases, the signaling included in the first database but not in the third database is identified as pending execution signaling, i.e., newly added pending execution signaling. Similarly, signaling detected as included in the third database but not in the first database is identified as signaling deleted by the cloud node. The third database can be any database other than the first database (ETCD). It is a database that the edge node uses to back up the signaling in the first database. After the edge node detects a change in the signaling in the first database (the specified CRD), it can obtain the signaling in the first database (the specified CRD) and compare it with the signaling backed up in the third database to determine the updated signaling in the first database (the specified CRD).

[0123] 1002. Execute the operation indicated by the above pending signaling.

[0124] In one implementation, after acquiring the signaling to be executed, the edge node can parse the signaling to determine its specific signaling type, such as a monitoring signaling or a task signaling. If the edge node determines the signaling to be executed is a monitoring signaling, it can execute the operation indicated by the monitoring signaling. Specifically, it can monitor the status of the device to be monitored, as indicated by the device information in the target information of the monitoring signaling, i.e., collect the status information of the device to be monitored and report the collected status information to the cloud node. To achieve the monitoring purpose, the edge node can periodically collect the status information of the device to be monitored and report it to the cloud node. If the edge node determines the signaling to be executed is a task signaling, such as the aforementioned edge inference task, it can execute the operation indicated by the edge inference task, such as acquiring a captured video stream and performing face recognition. Similarly, if the edge node detects that a task is included in the third database but not in the first database, it determines that the cloud node has deleted the task and can stop executing the operation indicated by the signaling to be executed.

[0125] Optionally, if the signaling to be executed includes scheduling information, the scheduling information is used to instruct the target process to perform the operation indicated by the signaling to be executed. The target process is one of the processes of an edge node in the signaling processing system. After obtaining the signaling to be executed, each edge node in the signaling processing system can determine whether it includes the target process, and then execute the operation indicated by the signaling to be executed at the edge node that determines that it includes the target process.

[0126] Please refer to the following: Figure 11 , Figure 11 This is a schematic diagram illustrating a signaling processing method provided in this application embodiment applied to an edge device management scenario. Figure 11 As shown, this edge device management takes the status monitoring of terminal devices (such as IPC devices) as an example. The cloud node can provide a device management interface, which is located on the cloud node. When a new monitoring device (such as an IPC device) is added, a signaling addition request can be triggered, thereby adding a signaling message to be executed. After the edge node obtains the signaling message to be executed, it determines the device to be monitored, i.e., as shown... Figure 11 The IPC device in the cloud, wherein the signaling to be executed includes device information input by the user through the user interface, which may include, but is not limited to, device name, device manufacturer, device model, IP address, port, username, password, RTSP address, cluster type, edge region, and device group. The edge node (processes within the edge node) can then access the IPC device via the RTSP address, collect the RTSP device's status information, and send this status information to the cloud node. The cloud node can then display this status information in the device management interface, such as... Figure 8 The status shown is "online".

[0127] Optionally, in the monitoring scenario, the monitoring equipment may include IPCs, snapshot cameras, national standard monitoring equipment, and other devices. For IPCs, edge nodes (processes within edge nodes) can access the IPC device via RTSP addresses to collect its status information. For snapshot cameras, edge nodes can adapt to the camera's protocol and periodically access the camera to collect its status information. For national standard monitoring equipment, the equipment can actively connect to the edge node, allowing the edge node to collect its status information. For other devices, they can periodically send status information to the edge node, which in turn receives status information from them. Optionally, the edge node can determine whether the monitored device is online or offline. It can also capture video streams or images from these streams and send them to the cloud node, treating the acquired video streams or images as a status indicator. Specific configurations can be tailored to the specific application or business scenario.

[0128] Please refer to the following: Figure 12 , Figure 12 This is a schematic diagram illustrating a signaling processing method provided in this application, applied to an edge inference task scenario. For example... Figure 12 As shown, taking the aforementioned face recognition task as an example, the cloud node generates a signaling message to be executed. The edge node obtains and parses this signaling message, determining it to be a task signaling message. The edge node can then execute the task signaling instruction, meaning it can acquire the video stream captured by the network camera on the terminal device and perform face recognition processing to obtain the face recognition result (structured data and image). The edge node can then upload the face recognition result to the cloud node. Figure 12 Taking a single user as an example, the actual number of users can be determined based on the specific application scenario. Furthermore, after receiving the facial recognition result from the edge node, the cloud node can compare it with facial images in the stored VIP facial image library to determine whether the user is a VIP user. Optionally, the cloud node can send the recognition result to a preset terminal device or display it in the user interface of the task execution results.

[0129] In edge computing scenarios, edge nodes or devices can periodically poll to obtain and execute signaling to be executed. Conversely, cloud nodes can synchronize process (Pod) information to trigger updates to the configuration file (configmap) and add new signaling to be executed. After detecting an update to the configuration file (configmap), the edge node remounts the configuration file to obtain and execute the signaling to be executed. Please refer to Table 1, which shows the processing effects of the above two methods and the signaling processing method provided in this application's embodiments.

[0130] Table 1

[0131]

[0132]

[0133] As can be seen, the signaling latency using polling can be the interval between polling cycles. However, excessively long polling cycles lead to high task latency, while excessively short cycles cause system instability. By updating the mounted configuration file, the signaling latency can be the default synchronization period (10s) + the Time To Live (TTL) value of the local cached configuration file + the configuration file detection period. With the signaling processing method in this solution, signaling latency is almost zero, allowing for near real-time acquisition and execution of signaling to be executed.

[0134] In this embodiment, the signaling processing system consists of cloud nodes and edge nodes. The cloud node responds to a new signaling request carrying target information, determines the signaling type based on the target information, and generates a signaling message to be executed based on the target information and the signaling type. The cloud node then stores this signaling message in a first database, which is a distributed database. The edge node continuously monitors the first database. If an update to the signaling message in the first database is detected during monitoring, the edge node can retrieve the newly added signaling message to be executed from the first database and execute the operation indicated by the signaling message. By storing the signaling message to be executed in the first database through the cloud node and monitoring the first database through the edge node, the edge node can obtain near real-time information about signaling changes, thereby retrieving the signaling message and executing the operation indicated by it. This approach is beneficial for handling latency-sensitive application requests and can be applied to scenarios with high real-time requirements. Furthermore, it eliminates the need for edge nodes to periodically poll for the signaling message to be executed, reducing the processing pressure on the cloud node and ensuring system stability.

[0135] Please see Figure 13 , Figure 13 This is a schematic diagram of a signaling processing device provided in an embodiment of this application. The signaling processing device 130 is applied to a cloud node, and the signaling processing device 90 can be used to perform... Figure 3 , Figure 5 The corresponding steps in the signaling processing method shown are illustrated. Please refer to [link / reference]. Figure 13 The signaling processing device 130 includes the following units:

[0136] The determining unit 1301 is configured to respond to a signaling addition request carrying target information, determine the signaling type based on the target information, and generate a signaling to be executed based on the target information and the signaling type;

[0137] Storage unit 1302 is used to store the aforementioned signaling to be executed into a first database, wherein the first database is a distributed database;

[0138] If the edge node detects an update to the signaling in the first database during its monitoring of the first database, it retrieves the signaling to be executed from the first database and executes the operation indicated by the signaling to be executed.

[0139] In one implementation, the storage unit 1302 is further configured to store the signaling to be executed in a second database, which is different from the first database;

[0140] The comparison unit 1303 is used to compare the signaling in the first database with the signaling in the second database at set time intervals.

[0141] The update unit 1304 is used to update the signaling in the first database according to the signaling in the second database if the comparison result indicates that the signaling in the first database is inconsistent with the signaling in the second database.

[0142] In one implementation, the determining unit 1301 generates a signaling to be executed based on the target information and the signaling type, specifically for:

[0143] When the above signaling type is a device signaling type, the device to be monitored is determined based on the device information included in the above target information;

[0144] A monitoring signaling message is generated for the aforementioned device to be monitored, and this monitoring signaling message is identified as a signaling message to be executed.

[0145] In one implementation, the signaling processing device 130 further includes:

[0146] The receiving unit 1305 is used to receive the device status information about the device to be monitored sent by the edge node; wherein the device status information is collected by the edge node in response to the monitoring signal and when it performs status monitoring on the device to be monitored.

[0147] Display unit 1306 is used to display the status information on the device management interface located at the cloud node.

[0148] According to one embodiment of this application, Figure 3 and Figure 5 Each step involved in the method shown can be performed by... Figure 13 This is performed by each unit in the signaling processing apparatus shown. For example, Figure 3 Step 301 shown is by Figure 13 The determination unit 1301 shown is responsible for executing step 302. Figure 13 The storage unit 1302 shown is used for execution. For example, Figure 5 Step 501 shown is by Figure 13 The determination unit 1301 shown is responsible for executing step 502. Figure 13 The storage unit 1302 shown is used to perform the operation.

[0149] According to one embodiment of this application, Figure 13The signaling processing apparatus 130 shown can be configured by combining each unit into one or more other units, or some of the units can be further divided into multiple functionally smaller units. This can achieve the same operation without affecting the technical effect of the embodiments of this application. The above units are based on logical function division. In practical applications, the function of one unit can be implemented by multiple units, or the function of multiple units can be implemented by one unit. In other embodiments of this application, the signaling processing apparatus 90 may also include other units. In practical applications, these functions can also be implemented with the assistance of other units, and can be implemented by multiple units working together. According to another embodiment of this application, a general-purpose computing device that can perform functions such as processing elements and storage elements, such as a central processing unit (CPU), random access memory (RAM), and read-only memory (ROM), can be run on a general-purpose computing device. Figure 3 , Figure 5 The computer program (including program code) for each step involved in the corresponding method shown, to construct such... Figure 9 The signaling processing apparatus 130 shown herein, and the signaling processing method for implementing the embodiments of this application, are described. The computer program may be recorded on, for example, a computer-readable storage medium, and loaded onto, via the computer-readable storage medium. Figure 1 The cloud-based signaling processing system shown Figure 2 The signaling processing system shown is located in the cloud node and runs within it.

[0150] Please see Figure 14 , Figure 14 This is a schematic diagram of a signaling processing device provided in an embodiment of this application. The signaling processing device 140 is applied to an edge node and can be used to perform... Figure 3 , Figure 9 The corresponding steps in the signaling processing method shown are illustrated. Please refer to [link / reference]. Figure 14 The signaling processing device 140 includes the following units:

[0151] The acquisition unit 1401 is used to acquire the signaling to be executed if an update is detected in the first database of stored signaling during the monitoring process; wherein the signaling to be executed is generated and stored in the first database by the cloud node in response to a signaling addition request carrying target information, the target information is used to determine the signaling type, and the target information and the signaling type are used to generate and store the signaling in the first database, wherein the first database is a distributed database.

[0152] The execution unit 1402 is used to execute the operation indicated by the above-mentioned signaling to be executed.

[0153] In one implementation, obtaining the signaling to be executed includes:

[0154] The signaling in the first database is compared with the signaling in the third database, which is different from the first database.

[0155] If the comparison result indicates that the signaling in the first database is inconsistent with the signaling in the third database, then the signaling included in the first database but not included in the third database will be determined as the signaling to be executed.

[0156] In one implementation, the signaling processing device 140 further includes:

[0157] Storage unit 1403 is used to store the aforementioned signaling to be executed into the aforementioned third database;

[0158] The stop unit 1404 is configured to stop executing the operation indicated by the signaling to be executed if it is detected that the third database includes the signaling to be executed and the first database does not include the signaling to be executed.

[0159] In one implementation, when the signaling type is a device signaling type, the signaling to be executed is a monitoring signaling. The monitoring signaling is generated by the cloud node based on the device information included in the target information to determine the device to be monitored and for the device to be monitored.

[0160] The aforementioned execution unit 1402 performs the operation indicated by the aforementioned pending signaling, specifically for:

[0161] In response to the above monitoring signaling, the status of the above-mentioned device to be monitored is monitored, and the status information of the above-mentioned device to be monitored is collected;

[0162] The signaling processing device 140 further includes:

[0163] The sending unit 1405 is used to send the collected status information of the device to be monitored to the cloud node, so that the cloud node can display the status information on the device management interface located on the cloud node.

[0164] According to one embodiment of this application, Figure 3 and Figure 9 Each step involved in the method shown can be performed by... Figure 14 This is performed by each unit in the signaling processing apparatus shown. For example, Figure 3 Steps 303-304 shown are by Figure 14 The acquisition unit 1401 shown is used to execute step 305. Figure 14 The determination unit 1402 shown is used to execute this. For example, Figure 9Step 901 shown is by Figure 14 The acquisition unit 1401 shown is used to execute step 902. Figure 14 The determination unit 1402 shown is used to perform this.

[0165] According to one embodiment of this application, Figure 14 The signaling processing apparatus 140 shown can be configured by combining each unit into one or more other units, or one or more of the units can be further divided into multiple functionally smaller units. This can achieve the same operation without affecting the technical effect of the embodiments of this application. The above units are based on logical function division. In practical applications, the function of one unit can also be implemented by multiple units, or the function of multiple units can be implemented by one unit. In other embodiments of this application, the signaling processing apparatus 140 may also include other units. In practical applications, these functions can also be implemented with the assistance of other units, and can be implemented by multiple units working together. According to another embodiment of this application, a general-purpose computing device that can perform functions such as processing elements and storage elements, such as a central processing unit (CPU), random access memory (RAM), and read-only memory (ROM), can be run on a general-purpose computer that includes processing elements and storage elements such as a central processing unit (CPU), random access memory (RAM), and read-only memory (ROM). Figure 3 , Figure 9 The computer program (including program code) for each step involved in the corresponding method shown, to construct such... Figure 14 The signaling processing apparatus 140 shown herein, and the signaling processing method for implementing the embodiments of this application, are described. The computer program may be recorded on, for example, a computer-readable storage medium, and loaded onto, via the computer-readable storage medium. Figure 1 The signaling processing system shown at the edge and Figure 2 It is located in the edge node of the signaling processing system shown, and runs within it.

[0166] In this embodiment, the signaling processing system consists of cloud nodes and edge nodes. The cloud node responds to a new signaling request carrying target information, determines the signaling type based on the target information, and generates a signaling message to be executed based on the target information and the signaling type. The cloud node then stores this signaling message in a first database, which is a distributed database. The edge node continuously monitors the first database. If an update to the signaling message in the first database is detected during monitoring, the edge node can retrieve the newly added signaling message to be executed from the first database and execute the operation indicated by the signaling message. By storing the signaling message to be executed in the first database through the cloud node and monitoring the first database through the edge node, the edge node can obtain near real-time information about signaling changes, thereby retrieving the signaling message and executing the operation indicated by it. This approach is beneficial for handling latency-sensitive application requests and can be applied to scenarios with high real-time requirements. Furthermore, it eliminates the need for edge nodes to periodically poll for the signaling message to be executed, reducing the processing pressure on the cloud node and ensuring system stability.

[0167] Based on the description of the above signaling processing method embodiments, this application also discloses a signaling processing device. Please refer to [link to relevant documentation]. Figure 15 The signaling processing device 150 may include at least a processor 1501, an input device 1502, an output device 1503, and a memory 1504. The processor 1501, input device 1502, output device 1503, and memory 1504 within the signaling processing device 150 may be connected via a bus or other means.

[0168] The aforementioned memory 1504 is a memory device in the signaling processing device 150, used to store programs and data. It is understood that the memory 1504 here can include the built-in storage medium of the signaling processing device, or it can include extended storage media supported by the signaling processing device 150. The memory 1504 provides storage space that stores the operating system of the signaling processing device 150. Furthermore, the computer program (including program code) is also stored in this storage space. It should be noted that the computer storage medium here can be a high-speed RAM memory; optionally, it can also be at least one computer storage medium located away from the aforementioned processor, which can be called a Central Processing Unit (CPU), the core and control center of the signaling processing device, used to run the computer program stored in the aforementioned memory 1504.

[0169] In one implementation, a processor 1501 can load and execute a computer program stored in memory 1504 to implement the corresponding steps of the method applied to the cloud node in the above-described signaling processing method embodiments; specifically, the processor 1501 loads and executes the computer program stored in memory 1504 for:

[0170] In response to a new signaling request carrying target information, the signaling type is determined based on the target information, and a signaling to be executed is generated based on the target information and the signaling type.

[0171] The aforementioned signaling to be executed is stored in a first database, which is a distributed database;

[0172] If the edge node detects an update to the signaling in the first database during its monitoring of the first database, it retrieves the signaling to be executed from the first database and executes the operation indicated by the signaling to be executed.

[0173] In one implementation, the processor 1501 loads and executes the computer program stored in the memory 1504, and is further configured to:

[0174] The aforementioned signaling to be executed is stored in a second database, which is different from the first database.

[0175] The signaling in the first database is compared with the signaling in the second database at set time intervals.

[0176] If the comparison result indicates that the signaling in the first database is inconsistent with the signaling in the second database, then the signaling in the first database is updated according to the signaling in the second database.

[0177] In one implementation, when generating the signaling to be executed based on the aforementioned target information and signaling type, the processor 1501 loads and executes the computer program stored in the memory 1504, which can be specifically used for:

[0178] When the above signaling type is a device signaling type, the device to be monitored is determined based on the device information included in the above target information;

[0179] A monitoring signaling message is generated for the aforementioned device to be monitored, and this monitoring signaling message is identified as a signaling message to be executed.

[0180] In one implementation, the processor 1501 loads and executes the computer program stored in the memory 1504, and is further configured to:

[0181] Receive device status information about the device to be monitored sent by the aforementioned edge node; wherein, the aforementioned device status information is collected by the aforementioned edge node in response to the aforementioned monitoring signaling and by performing status monitoring on the device to be monitored;

[0182] The above status information is displayed on the device management interface located at the aforementioned cloud node.

[0183] In one implementation, a processor 1501 can load and execute a computer program stored in memory 1504 to implement the corresponding steps of the method applied to edge nodes in the above-described signaling processing method embodiments; specifically, the processor 1501 loads and executes the computer program stored in memory 1504 for:

[0184] During the monitoring of the first database of stored signaling, if an update of the signaling in the first database is detected, the signaling to be executed is obtained; wherein, the signaling to be executed is generated and stored in the first database by the cloud node in response to the signaling addition request carrying target information, determining the signaling type according to the target information, and generating and storing the signaling in the first database according to the target information and the signaling type, and the first database is a distributed database.

[0185] Perform the operation indicated by the above pending signaling.

[0186] In one implementation, when acquiring a signaling instruction to be executed, the processor 1501 loads and executes the computer program stored in the memory 1504, which can be specifically used for:

[0187] The signaling in the first database is compared with the signaling in the third database. The third database is different from the first database.

[0188] If the comparison result indicates that the signaling in the first database is inconsistent with the signaling in the third database, then the signaling included in the first database but not included in the third database will be determined as the signaling to be executed.

[0189] In one implementation, the processor 1501 loads and executes the computer program stored in the memory 1504, and is further configured to:

[0190] Store the aforementioned pending signaling in the aforementioned third database;

[0191] If the third database contains the aforementioned signaling to be executed, and the first database does not contain the aforementioned signaling to be executed, then the operation indicated by the aforementioned signaling to be executed is stopped.

[0192] In one implementation, when the signaling type is a device signaling type, the signaling to be executed is a monitoring signaling. The monitoring signaling is generated by the cloud node based on the device information included in the target information to determine the device to be monitored and for the device to be monitored.

[0193] When executing the operation indicated by the aforementioned pending signaling, the processor 1501 loads and executes the computer program stored in the memory 1504, which can be specifically used for:

[0194] In response to the above monitoring signaling, the status of the above-mentioned device to be monitored is monitored, and the status information of the above-mentioned device to be monitored is collected;

[0195] The processor 1501 loads and executes the computer program stored in memory 1504, and is also used for:

[0196] The collected status information of the aforementioned devices to be monitored is sent to the cloud node, so that the cloud node can display the status information on the device management interface located on the cloud node.

[0197] It should be understood that, in the embodiments of this application, the processor 1501 may be a central processing unit (CPU), and the processor 1101 may also be 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. The general-purpose processor may be a microprocessor or any conventional processor.

[0198] In this embodiment, the signaling processing system consists of cloud nodes and edge nodes. The cloud node responds to a new signaling request carrying target information, determines the signaling type based on the target information, and generates a signaling message to be executed based on the target information and the signaling type. The cloud node then stores this signaling message in a first database, which is a distributed database. The edge node continuously monitors the first database. If an update to the signaling message in the first database is detected during monitoring, the edge node can retrieve the newly added signaling message to be executed from the first database and execute the operation indicated by the signaling message. By storing the signaling message to be executed in the first database through the cloud node and monitoring the first database through the edge node, the edge node can obtain near real-time information about signaling changes, thereby retrieving the signaling message and executing the operation indicated by it. This approach is beneficial for handling latency-sensitive application requests and can be applied to scenarios with high real-time requirements. Furthermore, it eliminates the need for edge nodes to periodically poll for the signaling message to be executed, reducing the processing pressure on the cloud node and ensuring system stability.

[0199] This application provides a computer-readable storage medium storing a computer program, which includes program instructions. When the program instructions are executed by a processor, they can perform the steps described in all the above embodiments.

[0200] This application also provides a computer program product or computer program, which includes computer instructions stored in a computer-readable storage medium. When the computer instructions are executed by the processor of a computer device, they perform the methods described in all the above embodiments.

[0201] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0202] The above description discloses only one preferred embodiment of the present invention, and should not be construed as limiting the scope of the present invention. Those skilled in the art will understand that all or part of the processes of the above embodiments can be implemented, and equivalent changes made in accordance with the claims of the present invention are still within the scope of the invention.

Claims

1. A signaling processing method, characterized in that, The method applies to a cloud node in a signaling processing system, the signaling processing system further including edge nodes and terminal devices, the edge nodes being connected to the cloud node, the terminal devices being connected to the edge nodes, and the edge node comprising multiple processes. In response to a signaling addition request carrying target information, a signaling type is determined based on the target information, and a signaling to be executed is generated based on the target information and the signaling type; the signaling to be executed is used to instruct the terminal device or the data collected by the terminal device to perform a service operation. Based on the process load of each process of the edge node, scheduling information is added to the signaling to be executed, and the scheduling information includes a process identifier that specifies the process used to execute the signaling to be executed. Through asynchronous storage, the signaling to be executed is stored in the target resource custom file corresponding to the signaling type in the first database. The first database is a distributed database, which includes multiple resource custom files. Different resource custom files are used to record different types of signaling. The signaling to be executed is stored in a second database, which is different from the first database. The signaling in the first database is compared with the signaling in the second database at set time intervals. If the comparison result indicates that the signaling in the first database is inconsistent with the signaling in the second database, the signaling in the first database is updated according to the signaling in the second database. If the edge node is configured to actively monitor the target resource custom file, and the edge node detects an update in the signaling of the target resource custom file during the active monitoring of the target resource custom file in the first database, then the edge node obtains the signaling to be executed from the target resource custom file, and executes the service operation indicated by the signaling to be executed for the terminal device or the data collected by the terminal device through the process corresponding to the process identifier. The service operation includes collecting the status of the terminal device and executing inference tasks. The system receives the execution result of the signaling to be executed returned by the edge node and displays the execution result on the device management interface.

2. The method according to claim 1, characterized in that, The step of generating the signaling to be executed based on the target information and the signaling type includes: When the signaling type is a device signaling type, the device to be monitored is determined based on the device information included in the target information; A monitoring signaling is generated for the device to be monitored, and the monitoring signaling is determined as a signaling to be executed.

3. The method according to claim 2, characterized in that, The step of receiving the execution result of the signaling to be executed returned by the edge node and displaying the execution result on the device management interface includes: The device receives device status information about the device to be monitored from the edge node; wherein the device status information is collected by the edge node in response to the monitoring signaling and by performing status monitoring on the device to be monitored. The status information is displayed on the device management interface located on the cloud node.

4. A signaling processing method, characterized in that, An edge node is used in a signaling processing system, the signaling processing system also including a cloud node and terminal devices, the edge node is connected to the cloud node, the terminal devices are connected to the edge node, the edge node includes multiple processes, and the method includes: During the active monitoring of target resource custom files in the first database storing signaling, if an update to the signaling in the target resource custom file is detected, the signaling to be executed is retrieved from the target resource custom file. The signaling to be executed is generated by the cloud node in response to a signaling addition request carrying target information, determining the signaling type based on the target information, and generating the signaling based on the target information and the signaling type. The cloud node adds scheduling information to the signaling to be executed based on the process load of each process of the edge node, and stores the signaling to be executed with added scheduling information asynchronously in the target resource custom file corresponding to the signaling type in the first database. The first database is a distributed database and includes multiple resource custom files. Different resource custom files are used to record different types of signaling. The edge node is configured to actively monitor the target resource custom files. The signaling to be executed is used to instruct the terminal device or the data collected by the terminal device to perform business operations. The scheduling information includes a process identifier that specifies the process used to execute the signaling to be executed. The cloud node also stores the signaling to be executed in a second database, which is different from the first database. The signaling in the first database is compared with the signaling in the second database at set time intervals. If the comparison result indicates that the signaling in the first database is inconsistent with the signaling in the second database, the signaling in the first database is updated according to the signaling in the second database. The process corresponding to the process identifier executes the service operation indicated by the signaling to be executed, which is directed to the terminal device or the data collected by the terminal device. The service operation includes collecting the status of the terminal device and executing inference tasks. The execution result for the signaling to be executed is sent to the cloud node, and the execution result is used by the cloud node to display it on the device management interface.

5. The method according to claim 4, characterized in that, The acquisition of the signaling to be executed includes: The signaling in the first database is compared with the signaling in the third database, which is different from the first database; If the comparison result indicates that the signaling in the first database is inconsistent with the signaling in the third database, then the signaling included in the first database but not included in the third database is determined as the signaling to be executed.

6. The method according to claim 5, characterized in that, The method further includes: The signaling to be executed is stored in the third database; If the third database contains the signaling to be executed, and the first database does not contain the signaling to be executed, then the operation indicated by the signaling to be executed is stopped.

7. The method according to any one of claims 4-6, characterized in that, When the signaling type is a device signaling type, the signaling to be executed is a monitoring signaling. The monitoring signaling is generated by the cloud node based on the device information included in the target information to determine the device to be monitored and for the device to be monitored. The operation of executing the signaling to be executed includes: In response to the monitoring signal, the device under monitoring is monitored for status, and the status information of the device under monitoring is collected; The step of sending the execution result of the signaling to be executed to the cloud node includes: The collected status information of the device to be monitored is sent to the cloud node so that the cloud node can display the status information on the device management interface located on the cloud node.

8. A signaling processing apparatus, characterized in that, It includes units for implementing the signaling processing method as described in any one of claims 1-3, or includes units for implementing the signaling processing method as described in any one of claims 4-7.

9. A signaling processing device, characterized in that, The signaling processing equipment includes: Processor, suitable for implementing computer programs; and, A computer-readable storage medium storing the computer program, the computer program being adapted to be loaded by the processor and to execute the signaling processing method as described in any one of claims 1-3, or to execute the signaling processing method as described in any one of claims 4-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, the computer program including program instructions, which, when executed by a processor, cause a computer device having the processor to implement the signaling processing method as described in any one of claims 1-3, or to implement the signaling processing method as described in any one of claims 4-7.

11. A computer program product, characterized in that, The computer program product includes a computer program or computer instructions, which, when executed by a processor, implement the signaling processing method as described in any one of claims 1-3, or implement the signaling processing method as described in any one of claims 4-7.

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