Internet of Things pressure test method and system based on digital twinning

Abstract

The invention relates to the technical field of digital twinning, Internet of Things and the like, and provides an Internet of Things pressure test method and system based on digital twinning, digital twinning representation is carried out on physical equipment to simulate virtual equipment corresponding to the physical equipment, the virtual equipment is used for reflecting the structure, behavior and performance of the physical equipment, and the physical equipment is used for testing the pressure of the Internet of Things based on digital twinning. The method comprises the following steps: acquiring real-time data of physical equipment in real time, synchronously transmitting the acquired real-time data of the physical equipment to virtual equipment so as to update the virtual equipment in real time to obtain the virtual equipment which keeps real-time updating, copying the virtual equipment which keeps real-time updating to obtain the virtual equipment of which the number is increased progressively; according to the method, the virtual devices with the increasing number are controlled to be connected and communicated with the IoT platform server, and the performance of the IoT platform server is tested, so that the testing efficiency of the IoT platform server is improved, the testing cost is reduced, and the IoT platform server is tested more comprehensively.

Description

Technical Field

[0001] The present invention relates to the technical fields of digital twins, the Internet of Things and the like, and in particular to an Internet of Things stress testing method based on digital twins. Background Art

[0002] With the rapid development of IoT technology, the number of physical devices on the IoT platform has exploded. How to test the stability, compatibility, security and efficiency of these physical devices when they are connected to the IoT platform has become an urgent problem to be solved in the IoT field. Traditional testing methods rely on manual testing or simple automated testing tools. When faced with the testing needs of large-scale physical device access, they are inefficient and difficult to discover potential compatibility and stability issues. In addition, the test environment requires a large number of IoT devices, which increases manpower and material costs.

[0003] In summary, the existing IoT testing technology has technical problems such as low efficiency, high cost, and incomplete testing. Summary of the invention

[0004] In view of the shortcomings of the above-mentioned prior art, the present invention provides an Internet of Things stress testing method and system based on digital twins to improve the testing efficiency of the IoT platform server, reduce the testing cost, and test the IoT platform server more comprehensively.

[0005] In a first aspect, the present invention provides an Internet of Things stress testing method based on digital twins, comprising: Performing a digital twin representation on a physical device to simulate a virtual device corresponding to the physical device, wherein the virtual device is used to reflect the structure, behavior and performance of the physical device; Collecting real-time data of the physical device in real time, and synchronously transmitting the collected real-time data of the physical device to the virtual device, so as to update the virtual device in real time, thereby obtaining a virtual device that keeps updating in real time; The virtual devices that are kept updated in real time are copied to obtain an increasing number of virtual devices, the increasing number of virtual devices are controlled to connect and communicate with the IoT platform server, and the performance of the IoT platform server is tested.

[0006] Furthermore, testing the performance of the IoT platform server includes testing the communication pressure that the IoT platform server can withstand.

[0007] Furthermore, the communication pressure that the IoT platform server can withstand is tested, including: controlling an increasing number of the virtual devices to initiate registration requests to the IoT platform server to register the IoT platform, and testing the normal response limit of the IoT platform server when responding normally to the registration request.

[0008] Furthermore, the communication pressure that the IoT platform server can withstand is tested, including: controlling an increasing number of the virtual devices to upload data to the IoT platform through the IoT platform server, and testing the upload data pressure that the IoT platform server can withstand.

[0009] Furthermore, the communication pressure that the IoT platform server can withstand is tested, including: controlling the IoT platform to issue instructions to an increasing number of virtual devices through the IoT platform server, and testing the instruction issuance pressure that the IoT platform server can support.

[0010] Furthermore, when testing the performance of the IoT platform server, it also includes: controlling the increasing number of virtual devices to access the IoT platform through the IoT platform server, and testing whether the IoT platform server can successfully access the increasing number of virtual devices to the IoT platform.

[0011] Furthermore, when testing the performance of the IoT platform server, it also includes: controlling the sending and receiving of information between the increasing number of virtual devices and the IoT platform through the IoT platform server, and testing whether the increasing number of virtual devices can normally send and receive information through the IoT platform server.

[0012] Furthermore, when testing the performance of the IoT platform server, it also includes: controlling the increasing number of virtual devices to initiate communication requests to the IoT platform server, and testing the response time of the IoT platform server in responding to the communication requests.

[0013] Further, after testing the performance of the IoT platform server, a test report is generated to optimize the performance of the IoT platform server.

[0014] In a second aspect, the present invention provides an Internet of Things stress testing system based on digital twins, comprising: The IoT platform server is connected and communicated with an increasing number of virtual devices, providing services for communication between the IoT platform and the increasing number of virtual devices; the virtual devices are obtained by digitally twinning the physical devices to reflect the structure, behavior and performance of the physical devices; The test server is connected and communicated with the increasing number of virtual devices, the IoT platform server and the physical device, and runs the above-mentioned digital twin-based IoT stress testing method to test the performance of the IoT platform server.

[0015] Compared with the prior art, the present invention has the following beneficial effects: The present invention provides an Internet of Things stress testing method and system based on digital twins. The method and system perform digital twin representation on physical devices to simulate and obtain virtual devices corresponding to the physical devices. The virtual devices are used to reflect the structure, behavior and performance of the physical devices. Real-time data of the physical devices are collected in real time. The collected real-time data of the physical devices are synchronously transmitted to the virtual devices to update the virtual devices in real time to obtain virtual devices that are kept updated in real time. The virtual devices that are kept updated in real time are copied to obtain an increasing number of virtual devices. The increasing number of virtual devices are controlled to connect and communicate with an IoT platform server to test the performance of the IoT platform server, thereby improving the testing efficiency of the IoT platform server, reducing the testing cost, and testing the IoT platform server more comprehensively. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of the present invention. The exemplary embodiments of the present invention and their description are used to explain the present invention and do not constitute an improper limitation of the present invention. Some specific embodiments of the present invention will be described in detail in an exemplary and non-restrictive manner with reference to the drawings. The same reference numerals in the drawings indicate the same or similar components or parts. It should be understood by those skilled in the art that these drawings are not necessarily drawn to scale. In the drawings: Figure 1 It is a flow chart of a method for stress testing the Internet of Things based on digital twins according to an embodiment of the present invention; Figure 2 It is an architectural diagram of an Internet of Things stress testing system based on digital twins in an embodiment of the present invention. DETAILED DESCRIPTION

[0017] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiment of the present invention. Obviously, the described embodiment is only an embodiment of a part of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work should fall within the scope of protection of the present invention.

[0018] Embodiment 1 An embodiment of the present invention provides an Internet of Things stress testing method based on digital twins, which performs digital twin representation on a physical device to simulate a virtual device corresponding to the physical device, wherein the virtual device is used to reflect the structure, behavior and performance of the physical device, collect real-time data of the physical device in real time, synchronously transmit the collected real-time data of the physical device to the virtual device, update the virtual device in real time, obtain a virtual device that keeps updating in real time, copy the virtual device that keeps updating in real time, obtain an increasing number of virtual devices, control the increasing number of virtual devices to connect and communicate with an IoT platform server, test the performance of the IoT platform server, thereby improving the testing efficiency of the IoT platform server, reducing the testing cost, and testing the IoT platform server more comprehensively.

[0019] See also Figure 1-Figure 2 , the Internet of Things stress testing method based on digital twins provided in this embodiment includes the following steps: S101, performing a digital twin representation on a physical device to simulate a virtual device corresponding to the physical device, wherein the virtual device is used to reflect the structure, behavior, and performance of the physical device; S102, collecting real-time data of the physical device in real time, and synchronously transmitting the collected real-time data of the physical device to the virtual device, so as to update the virtual device in real time, thereby obtaining a virtual device that keeps being updated in real time; S103, copying the virtual devices that are updated in real time to obtain an increasing number of virtual devices, controlling the increasing number of virtual devices to connect and communicate with the IoT platform server, and testing the performance of the IoT platform server.

[0020] It should be noted that digital twins can highly simulate the structure, behavior and performance of physical devices, reduce dependence on real physical devices, and thus greatly simplify the configuration of the test environment. During testing, there is no need to manually configure complex hardware test scenarios, thereby reducing labor input and resource consumption. In step S101, by replacing real devices with virtual devices, the test scenario can be quickly initialized, avoiding repeated configuration of hardware resources, reducing the need to purchase, maintain and deploy a large number of physical devices, and saving hardware costs. In step S102, physical device data is collected in real time and virtual devices are updated synchronously, so that virtual devices can accurately reflect the current status of physical devices, covering a variety of working modes and operating scenarios. For example, it covers simulated load fluctuations, abnormal behaviors (such as data loss, delays), etc., to ensure that the test is close to the actual operating environment. Dynamic data synchronization allows virtual devices to show the state changes of real devices, such as simulating behaviors under high load or abnormal conditions, thereby comprehensively testing the processing capabilities of IoT platform servers. In step S103, by copying virtual devices that are updated in real time, the number of virtual devices can be quickly increased to simulate large-scale concurrent device access scenarios. Compared with the deployment of physical devices one by one, this process is more efficient. By simulating high-concurrency scenarios (such as large-scale device registration, data upload, and command delivery), we can test the stability and performance bottlenecks of the IoT platform server under stress, thereby evaluating the performance of the IoT platform server. In addition, the number of virtual devices increases dynamically, which can reflect the device growth curve in the real environment and evaluate the adaptability of the IoT platform server to the gradually increasing access pressure.

[0021] In some further embodiments, when a physical device is represented by a digital twin to simulate a virtual device corresponding to the physical device, it can include: collecting key data of the physical device, the key data including structural data, behavioral data and performance data, the structural data reflecting the hardware parameters of the physical device, the behavioral data reflecting the operating logic and functional behavior of the physical device, and the performance data reflecting the performance indicators of the physical device; storing the key data in a unified format (such as JSON, XML) as the basis of the digital twin; building a virtual device based on the collected device data using modeling tools (such as MATLAB Simulink, Ansys, CAD software), the virtual device including a physical model, a functional model and a performance model; and communicating with the virtual device through MQTT, CoAP, HTTP Protocols such as , establish two-way communication between physical devices and virtual devices, configure data collection nodes (such as sensor gateways) and cloud platforms, and transmit real-time data of physical devices during operation to virtual devices; compare the static characteristics (such as size and weight) of virtual devices and physical devices to ensure the basic accuracy of virtual devices, and compare the operation data of physical devices in preset scenarios with the simulation results of virtual devices to verify the consistency of virtual devices with physical devices in dynamic operation; encapsulate the virtual devices that have passed the verification into independent executable modules (such as Docker containers, virtual machine images) to obtain virtual devices corresponding to the physical devices that are easy to copy and deploy to the test environment. It should be noted that in this embodiment, by completely collecting the hardware parameters (structural data), operation logic (behavior data) and performance indicators (performance data) of physical devices, comprehensive and accurate basic information is provided for the construction of virtual devices. In addition, unified format storage (such as JSON, XML) can standardize data processing, which is convenient for subsequent model development and system integration. In addition, the accuracy of virtual device models can be verified through static and dynamic comparisons. Static comparisons (such as size and weight) ensure the consistency of basic properties of virtual devices with physical devices. Dynamic scenario simulation and physical device operation data comparison and verification can ensure that the performance of virtual devices under different operating conditions is consistent with that of physical devices, laying the foundation for high reliability in testing. In addition, in this embodiment, constructing virtual devices (physical, functional, performance) in layers can separate characteristics of different dimensions, ensure the flexibility and modularity of virtual devices, and adapt to multi-scenario testing requirements. The use of standard protocols such as MQTT, CoAP, and HTTP can achieve real-time interaction between virtual devices and physical devices, ensuring that virtual devices can dynamically reflect the current status and operating conditions of physical devices. In addition, encapsulated virtual devices are easy to copy on a large scale and quickly deploy to the test environment, support diversified test scenarios and the generation of increasing numbers of virtual devices, and improve the efficiency and coverage of stress testing.

[0022] In some preferred embodiments, when testing the performance of the IoT platform server, it includes testing the communication pressure that the IoT platform server can withstand. Further, testing the communication pressure that the IoT platform server can withstand includes: controlling the increasing number of virtual devices to initiate registration requests to the IoT platform to the IoT platform server, and testing the normal response limit of the IoT platform server when responding to the registration request normally. Further, testing the communication pressure that the IoT platform server can withstand includes: controlling the increasing number of virtual devices to upload data to the IoT platform through the IoT platform server, and testing the upload data pressure that the IoT platform server can withstand. Further, testing the communication pressure that the IoT platform server can withstand includes: controlling the IoT platform to issue instructions to the increasing number of virtual devices through the IoT platform server, and testing the instruction issuance pressure that the IoT platform server can support. It should be noted that device registration is the starting point of all communication operations of the IoT platform, involving core processes such as device authentication, resource allocation, and connection establishment. Testing the registration request pressure can verify the platform's carrying capacity when a large number of devices are connected concurrently. In addition, device data upload is one of the core tasks of the IoT platform, involving the upload of multiple types of data such as sensor data, video streams, event logs, etc. The processing capacity of uploaded data directly determines the stability and operating efficiency of the platform. Through testing, the processing capacity of network bandwidth, database throughput, and message queues can be evaluated, so as to find the bottleneck of the IoT platform server under high load. In addition, the IoT platform needs to send various control instructions (such as status query, parameter modification, operation execution, etc.) to the device through the IoT platform server. By testing the pressure of sending instructions, the processing efficiency and stability of the IoT platform server when sending instructions can be evaluated.

[0023] In some preferred embodiments, when testing the performance of the IoT platform server, it also includes: controlling the increasing number of virtual devices to access the IoT platform through the IoT platform server, and testing whether the IoT platform server can successfully access the increasing number of virtual devices to the IoT platform. It should be noted that the device access test focuses on the processing capability of the IoT platform server in the device connection phase, including key processes such as identity authentication, session resource allocation, and connection establishment. Unlike the communication stress test, this test focuses on the performance verification of the initial access phase, and evaluates whether the IoT platform server can stably complete device access and reasonably allocate resources when the number of devices continues to increase. Increasing virtual device access can reveal the performance limits of modules such as authentication efficiency, session management, or connection scheduling during device access. Through testing, the bottlenecks of these stages can be accurately identified, providing clear directions for resource allocation optimization (such as dynamic thread management) or architecture upgrades (such as distributed access load balancing), and ensuring that the IoT platform server has good scalability and stability in the device access link.

[0024] In some preferred embodiments, when testing the performance of the IoT platform server, it also includes: controlling the increasing number of virtual devices to send and receive information with the IoT platform through the IoT platform server, and testing whether the increasing number of virtual devices can normally send and receive information through the IoT platform server. It should be noted that in this embodiment, the focus is on whether the process of sending and receiving information can be completed normally, including the accuracy, completeness and timeliness of message delivery. This is the core capability of the IoT platform server to ensure reliable communication between devices and platforms in daily operation. The test can evaluate whether there are problems such as message loss, sequence error or increased delay when the server sends and receives messages concurrently by large-scale devices, and ensure the quality of communication. In this embodiment, the increasing number of virtual devices can examine the message processing logic and resource management (such as memory cache, message queue) of the IoT platform server under high concurrency, and can verify whether the server has recovery capabilities and system stability under abnormal conditions (such as high load, partial message loss or delay burst).

[0025] In some preferred embodiments, when testing the performance of the IoT platform server, it also includes: controlling the increasing number of virtual devices to initiate communication requests to the IoT platform server, and testing the response time of the IoT platform server in response to the communication request. It should be noted that the test virtual devices incrementally initiate communication requests and measure the server response time, aiming to quantify the processing efficiency of the server. Response time is an important indicator for measuring server performance, which directly reflects the server's ability to quickly process communication requests under high load. This test focuses on evaluating the task scheduling, network communication and resource management performance of the server to ensure that it can maintain low latency when multiple devices communicate concurrently, meeting the requirements for real-time and efficiency in actual IoT scenarios. As the number of virtual devices increases, the concurrent pressure of communication requests will reveal the performance limit of the server under different loads. By observing the changing trend of response time with increasing load, the server processing bottleneck (such as CPU scheduling, thread pool saturation, database response delay, etc.) can be identified. These results can provide key basis for optimizing resource allocation, improving task scheduling strategies and upgrading system architecture.

[0026] In some preferred embodiments, after testing the performance of the IoT platform server, a test report is generated to optimize the performance of the IoT platform server. It should be noted that the test report can record in detail the performance indicators (such as response time, resource occupancy, throughput, etc.) and bottleneck information of the server under different load scenarios to help developers clearly understand the performance of the server. Based on the analysis results provided by the report, developers can accurately locate performance deficiencies (such as increased latency or resource exhaustion under high load), thereby formulating efficient optimization plans to improve the operating efficiency and stability of the server.

[0027] In some further embodiments, the performance status data corresponding to the IoT platform server obtained by testing when different numbers and types of virtual devices communicate with the IoT platform server is counted to obtain the correlation data of the number of different types of virtual devices participating in the communication and the performance of the IoT platform server; the deep learning model used to predict the performance of the IoT platform server is trained using the correlation data to obtain the prediction model of the IoT platform server. It should be noted that different numbers and types of virtual devices have significant differences in the performance impact on the IoT platform server (such as bandwidth occupancy, processing complexity, etc.). By counting these correlation data and training with a deep learning model, a mapping relationship between quantity, type and performance indicators can be established. The prediction model can quickly estimate the performance of the server in various complex scenarios without actual testing, thereby realizing the prediction and advance planning of server performance. It should be noted that through the prediction model, the performance limit of the server under different load conditions can be quickly simulated and analyzed based on fewer actual tests. This not only reduces the consumption of test resources, but also can intelligently assist decision-making, provide a scientific basis for server optimization (such as resource allocation, architecture improvement), and support dynamic adjustment of strategies to adapt to real-time changes in the number or type of devices.

[0028] Embodiment 2 See also Figure 1-Figure 2 , this embodiment provides an Internet of Things stress testing system based on digital twins, including: The IoT platform server is connected and communicated with an increasing number of virtual devices, providing services for communication between the IoT platform and the increasing number of virtual devices; the virtual devices are obtained by digitally twinning the physical devices to reflect the structure, behavior and performance of the physical devices; A test server is connected and communicated with the increasing number of virtual devices, the IoT platform server and the physical device, and runs the IoT stress testing method based on digital twins described in any of the above embodiments, and simulates a virtual device corresponding to the physical device by digital twin representation of the physical device, and the virtual device is used to reflect the structure, behavior and performance of the physical device, collect real-time data of the physical device in real time, and synchronously transmit the collected real-time data of the physical device to the virtual device to update the virtual device in real time to obtain a virtual device that keeps updating in real time, and copy the virtual device that keeps updating in real time to obtain an increasing number of virtual devices, and control the increasing number of virtual devices to connect and communicate with the IoT platform server, and test the performance of the IoT platform server, so as to improve the testing efficiency of the IoT platform server, reduce the testing cost, and test the IoT platform server more comprehensively.

[0029] It should be pointed out that the above embodiments are only preferred specific implementation modes of the present invention, and the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by any technician familiar with the technical field within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention. The protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A digital twin-based Internet of Things stress testing method, characterized in that: include: Performing a digital twin representation on a physical device to simulate a virtual device corresponding to the physical device, wherein the virtual device is used to reflect the structure, behavior and performance of the physical device; Collecting real-time data of the physical device in real time, and synchronously transmitting the collected real-time data of the physical device to the virtual device, so as to update the virtual device in real time, thereby obtaining a virtual device that keeps updating in real time; The virtual devices that are kept updated in real time are copied to obtain an increasing number of virtual devices, the increasing number of virtual devices are controlled to connect and communicate with the IoT platform server, and the performance of the IoT platform server is tested.

2. The Internet of Things stress testing method based on digital twins according to claim 1, characterized in that: Testing the performance of the IoT platform server includes testing the communication pressure that the IoT platform server can withstand.

3. The Internet of Things stress testing method based on digital twins according to claim 2, characterized in that: Testing the communication pressure that the IoT platform server can withstand includes: controlling an increasing number of the virtual devices to initiate registration requests for registering the IoT platform to the IoT platform server, and testing the normal response limit of the IoT platform server when responding normally to the registration request.

4. The Internet of Things stress testing method based on digital twins according to claim 2, characterized in that: The communication pressure that the IoT platform server can withstand is tested, including: controlling an increasing number of the virtual devices to upload data to the IoT platform through the IoT platform server, and testing the upload data pressure that the IoT platform server can withstand.

5. The Internet of Things stress testing method based on digital twins according to claim 2, characterized in that: Testing the communication pressure that the IoT platform server can withstand includes: controlling the IoT platform to issue instructions to an increasing number of virtual devices through the IoT platform server, and testing the instruction issuance pressure that the IoT platform server can support.

6. The Internet of Things stress testing method based on digital twins according to claim 1, characterized in that: When testing the performance of the IoT platform server, it also includes: controlling the increasing number of virtual devices to access the IoT platform through the IoT platform server, and testing whether the IoT platform server can successfully access the increasing number of virtual devices to the IoT platform.

7. The Internet of Things stress testing method based on digital twins according to claim 1, characterized in that: When testing the performance of the IoT platform server, it also includes: controlling the increasing number of virtual devices to send and receive information with the IoT platform through the IoT platform server, and testing whether the increasing number of virtual devices can normally send and receive information through the IoT platform server.

8. The Internet of Things stress testing method based on digital twins according to claim 5, characterized in that: When testing the performance of the IoT platform server, it also includes: controlling the increasing number of virtual devices to initiate communication requests to the IoT platform server, and testing the response time of the IoT platform server in responding to the communication requests.

9. The Internet of Things stress testing method based on digital twins according to any one of claims 1 to 8, characterized in that: After testing the performance of the IoT platform server, a test report is generated to optimize the performance of the IoT platform server.

10. An IoT stress testing system based on digital twins, characterized in that: include: The IoT platform server connects and communicates with the increasing number of virtual devices, and provides services for the communication between the IoT platform and the increasing number of virtual devices; The virtual device is obtained by performing digital twin representation on the physical device, and is used to reflect the structure, behavior and performance of the physical device; The test server is connected and communicated with the increasing number of virtual devices, the IoT platform server and the physical device, and runs the Internet of Things stress testing method based on digital twins as described in any one of claims 1 to 9 to test the performance of the IoT platform server.

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