Method and system for using WasmEdge as cloud native edge node

Abstract

The invention relates to the technical field of cloud native edge nodes, in particular to a method and system for using WasmEdge as a cloud native edge node, and the method comprises the following steps: deploying WasmEdge on edge equipment as an edge node operation environment; the WasmEdge is used for supporting a WebAssembly standard and an extended API (Application Program Interface) related to a cloud native application scene, so that communication between the edge node and the center node is realized; the method comprises the following steps of: integrating WasmEdge into a Docker tool and Kubernetes through a runtime specification of an OCI (Open Common Interface), so as to realize management and arrangement of edge nodes of the WasmEdge; the method and system for taking the WasmEdge as the cloud native edge node have the beneficial effects that the WasmEdge is taken as the edge node based on the WasmEdge, and the WasmEdge is combined with a technology of taking a real-time operating system and a non-real-time operating system as intelligent AI nodes in a cloud native system, so that the application of the real-time operating system and the non-real-time operation is realized by using hypervisor virtualization; as a cloud native edge node, lightweight real-time response can be realized, and the defects of a real-time operating system can be enhanced by combining powerful functions of a common operating system to collect, store and configure.

Description

Technical Field

[0001] The present invention relates to the technical field of cloud-native edge nodes, and specifically to a method and system using WasmEdge as a cloud-native edge node. Background Art

[0002] Currently, cloud native technology has been widely used in the field of edge computing and has become an important force in promoting the development of edge computing. With the widespread application of the Internet of Things (IoT) and intelligent AI technology, real-time operating systems (RTOS) have gradually become the basis for edge node applications due to their high real-time performance and low latency. RTOS plays a key role in edge devices. It is responsible for real-time processing of data from IoT devices and efficient communication with the cloud to achieve real-time data analysis and decision-making.

[0003] In cloud-native infrastructure, WasmEdge is gradually emerging as an innovative edge computing solution. WasmEdge not only supports the standard WebAssembly specification, but also provides extended APIs related to cloud-native application scenarios, making it easy to integrate into various cloud-native environments. WasmEdge's lightweight, high performance, and security make it an ideal choice for microservices, serverless functions, and plugins, providing strong technical support for edge computing.

[0004] However, in edge computing scenarios, edge devices often have limited computing, storage, and network resources. Although traditional Linux containers are powerful, they are too cumbersome to run on resource-constrained edge devices and cannot meet the lightweight, fast, and real-time requirements of edge applications. Therefore, it is imperative to find a lightweight container technology that is more suitable for edge devices. Summary of the invention

[0005] The purpose of the present invention is to provide a method and system using WasmEdge as a cloud-native edge node to solve the problems raised in the above background technology.

[0006] To achieve the above object, the present invention provides the following technical solution: a method using WasmEdge as a cloud-native edge node, the method comprising the following steps:

[0007] Deploy WasmEdge on edge devices as the edge node operating environment;

[0008] Use WasmEdge to support WebAssembly specifications and cloud-native application scenario-related extension APIs to achieve communication between edge nodes and central nodes;

[0009] Through the OCI runtime specification, WasmEdge is integrated into Docker tools and Kubernetes to achieve the management and orchestration of WasmEdge edge nodes;

[0010] A microkernel system runs on the hypervisor, and a Linux operating system runs in parallel on the same hardware as a guest OS to provide file system, network, and user information functions;

[0011] Deploy the WasmEdge agent on the Linux guest OS to upload, store, and hot-deploy WasmEdge bytecode files, and execute the bytecode through the WasmEdge runner to achieve lightweight and fast operation of edge nodes.

[0012] Preferably, the method further comprises the following steps:

[0013] Taking advantage of the extensibility of WasmEdge, host functions are added to WasmEdge from shared native libraries, allowing WasmEdge WebAssembly bytecode programs to easily access hardware resources;

[0014] WasmEdge enables real-time data collection and high-performance processing of edge nodes in offline state, ensuring the independent working ability of edge nodes when they lose connection with the central node.

[0015] Preferably, WasmEdge edge nodes pass the formal verification of WebAssembly programs to ensure the security and stability of edge nodes, making them highly reliable when running as critical systems.

[0016] Preferably, the communication between the WasmEdge agent and the WasmEdge runner adopts an efficient data transmission protocol to reduce communication delays and improve the response speed of edge nodes.

[0017] Preferably, the method further comprises the following steps:

[0018] Configure the access rights and security policies of the WasmEdge agent on the Linux guest OS to ensure the legitimacy and security of the WasmEdge bytecode files;

[0019] Monitor the operating status and performance indicators of WasmEdge edge nodes, discover and handle abnormal situations in a timely manner, and ensure the continuous and stable operation of edge nodes.

[0020] A system using WasmEdge as a cloud-native edge node, applied to a method using WasmEdge as a cloud-native edge node, the system comprising:

[0021] Edge devices, on which the WasmEdge runtime environment is deployed to execute WebAssembly bytecode applications;

[0022] Hypervisor, used to run the microkernel system and Linux operating system as guest OS on the same hardware;

[0023] Linux guest OS, which provides file system, network, user information, shell and CLI functions and tools;

[0024] WasmEdge agent, deployed on Linux guest OS, is used to receive, store and manage WasmEdge bytecode files, and hot deploy and execute these bytecodes in the microkernel system through WasmEdge runner;

[0025] WasmEdge runner, installed in the microkernel system, is used to execute WebAssembly bytecode applications managed by the WasmEdge agent, enabling lightweight and fast operation of edge nodes.

[0026] Preferably, the WasmEdge runtime environment supports the standard WebAssembly specification and extended APIs related to cloud-native application scenarios, enabling WasmEdge edge nodes to communicate with central nodes in real-time, offline, and reconnected ways, and realize real-time data collection and high-performance processing.

[0027] Preferably, the WasmEdge agent is integrated with the Docker tool and Kubernetes through the OCI runtime specification, so that the WasmEdge edge nodes are effectively managed and orchestrated by Docker and Kubernetes, improving the flexibility and scalability of the system.

[0028] Preferably, the WasmEdge runtime environment is scalable, and host functions are added from the shared native library, so that the WebAssembly bytecode program can easily access hardware resources and realize the intelligence and real-time performance of the edge node.

[0029] Preferably, the system also includes a monitoring module for monitoring the operating status and performance indicators of the WasmEdge edge node, promptly detecting and handling abnormal situations, ensuring the continuous and stable operation of the edge node, and providing necessary alarm and logging functions.

[0030] Compared with the prior art, the present invention has the following beneficial effects:

[0031] The present invention proposes a method and system using WasmEdge as a cloud-native edge node. WasmEdge is used as the basis of the edge node and combines a real-time operating system and a non-real-time operating system as the technology of an intelligent AI node in a cloud-native system. Hypervisor virtualization is used to implement the application of real-time operating system and non-real-time operation. As a cloud-native edge node, it can not only respond in real time in a lightweight manner, but also combine the powerful functions of ordinary operating systems to collect, store, and configure to strengthen the shortcomings of real-time operating systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 is a flow chart of the method of the present invention;

[0033] Figure 2 This is a schematic diagram of the application of WasmEdge in the development of smart Internet of Things. DETAILED DESCRIPTION

[0034] In order to make the purpose and technical solution of the present invention clearly and completely described, and the advantages more clearly understood, the embodiments of the present invention are further described in detail with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are part of the embodiments of the present invention, rather than all of the embodiments, and are only used to explain the embodiments of the present invention, and are not used to limit the embodiments of the present invention. All other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0035] For example, see Figure 1 to Figure 2 The present invention provides a technical solution: a method for using WasmEdge as a cloud-native edge node, the method comprising the following steps:

[0036] Edge devices have limited computing, storage, and network resources. Running a full K8s node on an edge device is often too resource-intensive. Standard Linux containers are still too bulky to run edge workloads on small devices. And it takes several seconds to start a full CPU. But edge applications are usually leaner, and Linux containers take up too much storage, CPU, and battery resources on resource-constrained devices. In order to achieve lightweight, lean, and fast functions, WasmEdge is used as an edge node to ensure that the edge node can be lightweight and work offline.

[0037] In the intelligent Internet of Things system, it is necessary to realize the communication between edge nodes and central nodes in real time, offline, and reconnection. In order to realize fast and lightweight communication between edge and central nodes, the lightweight edge node wasmedge and non-real-time operating system are combined to realize the functions of real-time data collection and high-performance data processing.

[0038] In addition to the standard WebAssembly specification, WasmEdge supports extended API WebAssembly related to cloud-native application scenarios, and implements hot deployment and sharing of file systems, networks, user information, etc. through hypervisor. Another aspect is that WebAssembly programs are usually formally verified like microkernel systems, so wasmedgez is very suitable as an edge node and a key system.

[0039] In edge container application scenarios, WasmEdge is used through OCI runtime specifications, managed and orchestrated by Docker tools and Kubernetes, and a WebAssembly management agent is built for microkernel systems and WasmEdge. It allows WebAssembly bytecode applications to be easily deployed and executed on real-time operating systems.

[0040] Deploy the microkernel system to the hypervisor and run it. Start the Linux operating system on the same hardware (server) and run it on the hypervisor in parallel. The Linux operating system runs on the hypervisor as a guest OS. The Linux guest OS is used for file systems, networks, user information, shells, and CLI functions and tools, but the Linux guest OS is not a real-time operating system. Run the WasmEdge agent, i.e., WasmEdge agent, on the guest OS (Linux OS). Upload and store the WasmEdge bytecode file in the guest OS (Linux OS). Use the WasmEdge runner installed in the microkernel system to use the agent to hot deploy and execute the bytecode as an edge node. Use WasmEdge scalability to achieve real-time performance of system nodes. Adding host WasmEdge WebAssembly bytecode programs to WasmEdge from shared native libraries can easily access hardware, thereby combining edge nodes (WasmEdge) with non-real-time operating systems to achieve real-time performance, provide computing power, and provide file systems, making edge nodes more intelligent.

[0041] The solution of using WasmEdge as the edge node brings the following effects:

[0042] Lightweight and efficient: WasmEdge is lightweight and can run efficiently on resource-constrained edge devices. Compared with traditional Linux containers, WasmEdge occupies less storage, CPU, and battery resources, starts faster, and can significantly improve the operating efficiency and performance of edge devices.

[0043] Real-time and reliability: Combined with a real-time operating system (RTOS), WasmEdge can achieve high real-time and low-latency data processing on edge nodes. This is especially important for mission-critical systems such as smart cars and aerospace, ensuring the timeliness and accuracy of data and improving the overall reliability of the system.

[0044] Flexibility and scalability: WasmEdge supports standard WebAssembly specifications and extended APIs related to cloud-native application scenarios, making it easy to integrate into various cloud-native environments. This flexibility and scalability make WasmEdge applicable to multiple cloud-native fields such as smart cars, aerospace, and smart IoT, meeting application requirements in different scenarios.

[0045] Security and isolation: WasmEdge provides strong security and isolation for edge applications through a sandbox execution environment. This helps prevent malicious code attacks and data leakage, and protects the normal operation of edge devices and the integrity of data.

[0046] Simplified deployment and management: WasmEdge supports integration with Docker tools and Kubernetes through OCI's runtime specification, making the deployment and management of edge nodes simpler and more efficient. This reduces operation and maintenance costs and improves the scalability and flexibility of the system.

[0047] Embodiment 2, based on Embodiment 1, proposes a system using WasmEdge as a cloud-native edge node, which is applied to a method using WasmEdge as a cloud-native edge node, and the system includes:

[0048] Edge devices, on which the WasmEdge runtime environment is deployed to execute WebAssembly bytecode applications;

[0049] Hypervisor, used to run the microkernel system and Linux operating system as guest OS on the same hardware;

[0050] Linux guest OS, which provides file system, network, user information, shell and CLI functions and tools;

[0051] The WasmEdge agent is deployed on the Linux guest OS and is used to receive, store and manage WasmEdge bytecode files, as well as hot deploy and execute these bytecodes in the microkernel system through the WasmEdge runner; the WasmEdge runtime environment supports the standard WebAssembly specification and extended APIs related to cloud-native application scenarios, enabling WasmEdge edge nodes to communicate with central nodes in real time, offline, and reconnect, and realize real-time data collection and high-performance processing; the WasmEdge agent is integrated with the Docker tool and Kubernetes through the OCI runtime specification, so that the WasmEdge edge nodes are effectively managed and orchestrated by Docker and Kubernetes, improving the flexibility and scalability of the system.

[0052] WasmEdge runner, installed in the microkernel system, is used to execute WebAssembly bytecode applications managed by the WasmEdge agent, enabling lightweight and fast operation of edge nodes.

[0053] The WasmEdge runtime environment is scalable and adds host functions from shared native libraries, allowing WebAssembly bytecode programs to easily access hardware resources and achieve intelligence and real-time performance of edge nodes.

[0054] The system also includes a monitoring module, which is used to monitor the operating status and performance indicators of WasmEdge edge nodes, detect and handle abnormal situations in a timely manner, ensure the continuous and stable operation of edge nodes, and provide necessary alarm and logging functions.

[0055] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method using WasmEdge as a cloud-native edge node, characterized by: The method comprises the following steps: Deploy WasmEdge on edge devices as the edge node operating environment; Use WasmEdge to support WebAssembly specifications and cloud-native application scenario-related extension APIs to achieve communication between edge nodes and central nodes; Through the OCI runtime specification, WasmEdge is integrated into Docker tools and Kubernetes to achieve the management and orchestration of WasmEdge edge nodes; A microkernel system is run on the hypervisor, and a Linux operating system is run in parallel on the same hardware as a guest OS to provide file system, network, and user information functions; Deploy the WasmEdge agent on the Linux guest OS to upload, store, and hot-deploy WasmEdge bytecode files, and execute the bytecode through the WasmEdge runner to achieve lightweight and fast operation of edge nodes.

2. A method for using WasmEdge as a cloud-native edge node according to claim 1, characterized in that: The following steps are also included: Taking advantage of the extensibility of WasmEdge, host functions are added to WasmEdge from shared native libraries, allowing WasmEdgeWebAssembly bytecode programs to easily access hardware resources; WasmEdge enables real-time data collection and high-performance processing of edge nodes in offline state, ensuring the independent working ability of edge nodes when they lose connection with the central node.

3. A method for using WasmEdge as a cloud-native edge node according to claim 2, characterized in that: WasmEdge edge nodes ensure the security and stability of edge nodes through formal verification of WebAssembly programs, making them highly reliable when running as critical systems.

4. The method of using WasmEdge as a cloud-native edge node according to claim 1, characterized in that: The communication between the WasmEdge agent and the WasmEdge runner uses an efficient data transmission protocol to reduce communication latency and improve the response speed of edge nodes.

5. The method of using WasmEdge as a cloud-native edge node according to claim 1, characterized in that: The following steps are also included: Configure the access rights and security policies of the WasmEdge agent on the Linux guest OS to ensure the legitimacy and security of the WasmEdge bytecode files; Monitor the operating status and performance indicators of WasmEdge edge nodes, discover and handle abnormal situations in a timely manner, and ensure the continuous and stable operation of edge nodes.

6. A system using WasmEdge as a cloud-native edge node, applied to the method using WasmEdge as a cloud-native edge node as described in any one of claims 1 to 5, characterized in that: The system comprises: Edge devices, on which the WasmEdge runtime environment is deployed to execute WebAssembly bytecode applications; Hypervisor, used to run the microkernel system and Linux operating system as guest OS on the same hardware; Linux guest OS, which provides file system, network, user information, shell and CLI functions and tools; WasmEdge agent, deployed on Linux guest OS, is used to receive, store and manage WasmEdge bytecode files, and hot deploy and execute these bytecodes in the microkernel system through WasmEdge runner; WasmEdge runner, installed in the microkernel system, is used to execute WebAssembly bytecode applications managed by the WasmEdge agent, enabling lightweight and fast operation of edge nodes.

7. A system using WasmEdge as a cloud-native edge node according to claim 6, characterized in that: The WasmEdge runtime environment supports standard WebAssembly specifications and extended APIs related to cloud-native application scenarios, enabling WasmEdge edge nodes to communicate with central nodes in real time, offline, and reconnect, and achieve real-time data collection and high-performance processing.

8. A system using WasmEdge as a cloud-native edge node according to claim 6, characterized in that: The WasmEdge agent is integrated with Docker tools and Kubernetes through the OCI runtime specification, so that WasmEdge edge nodes are effectively managed and orchestrated by Docker and Kubernetes, improving the flexibility and scalability of the system.

9. A system using WasmEdge as a cloud-native edge node according to claim 6, characterized in that: The WasmEdge runtime environment is scalable and adds host functions from shared native libraries, allowing WebAssembly bytecode programs to easily access hardware resources and achieve intelligence and real-time performance of edge nodes.

10. A system using WasmEdge as a cloud-native edge node according to claim 6, characterized in that: The system also includes a monitoring module, which is used to monitor the operating status and performance indicators of WasmEdge edge nodes, detect and handle abnormal situations in a timely manner, ensure the continuous and stable operation of edge nodes, and provide necessary alarm and logging functions.

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