Time-synchronized ad hoc network semi-physical simulation method and system
By stripping the software program into semi-physical nodes and establishing discrete event simulation, the time synchronization problem during physical node access in the self-network simulation is solved, and the simulation results with high reality and reliability are achieved, and the reproduction and positioning network are available. The ability to fail.
Patent Information
- Application Number
- CN202411521987.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-29
- Publication Date
- 2025-02-14
AI Technical Summary
The existing self-network simulation methods lack the time synchronization problem of physical nodes accessing to digital systems, resulting in insufficient credibility of simulation results.
By stripping the software program from the physical node into a semi-physical node, and establishing discrete event simulation of an ad hoc network based on such semi-physical nodes, using a discrete event scheduler to achieve time synchronization, ensuring that the system time of the digital node and the physical node is consistent with the system time of the digital node and the physical node .
The ability to reproduce and locate actual network failures is realized, the authenticity and reliability of simulation results are improved, and the problem of inconsistent simulation time and real time is avoided.
Smart Images
Figure CN119450546A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of network simulation technology, and in particular to a method and system for semi-physical simulation of a time-synchronized self-organizing network. Background Art
[0002] A self-organizing network is a wireless communication network composed of mobile communication nodes. The network has the characteristics of being decentralized, multi-hop, node-independent, dynamic topology, and self-organizing. The nodes in the self-organizing network can not only send and receive data as hosts, but also participate in data packet forwarding and network maintenance as routers. Large-scale self-organizing networks have the characteristics of a large number of nodes and complex network topology changes. Verifying their functional performance indicators in different application scenarios through simulation is an effective means to reduce the consumption of manpower, material resources, and financial resources.
[0003] Semi-physical simulation is also called system-in-the-loop or hardware-in-the-loop, which combines mathematical models with physical models or physical models to form a complex simulation system. The simulation results of semi-physical system simulation are more realistic, and it is a simulation experiment technology that is closer to reality, and the simulation results provided are more reliable. For self-organizing networks with a large number of nodes, it is difficult to conduct large-scale physical node experiments in a laboratory environment. Therefore, in order to approach a more realistic simulation experiment, semi-physical simulation technology is introduced to connect physical nodes to a large-scale wireless self-organizing network built by software in some way to realize a hardware-in-the-loop network.
[0004] In the patent "Semi-physical simulation element design method for large-scale unmanned cluster networks", a semi-physical simulation element design method for large-scale unmanned cluster networks was designed. However, this simulation method lacks consideration of the time synchronization problem of physical nodes accessing the digital system, and lacks modeling considerations for the authenticity of digital nodes, which may lead to insufficient credibility of the simulation results.
[0005] Traditional self-organizing network simulation solutions are usually full-digital simulations, which construct network models in simulation scenarios by digitally modeling physical nodes and communication channels. Fully digital network simulations have the problems of coarse simulation granularity and insufficient simulation results. Faults that occur in actual networks are difficult to reproduce and locate in the simulation system.
[0006] Introducing physical nodes into digital simulation can make the simulation results closer to reality. However, for ad hoc network simulation, especially large-scale ad hoc network simulation, the speed of digital simulation is much lower than the running speed of physical nodes, resulting in inconsistent system time between digital nodes and physical nodes, and physical nodes cannot be connected to the digital simulation system. Summary of the invention
[0007] The embodiments of the present application provide a time-synchronized semi-physical simulation method and system for a self-organizing network, which separates the software program from the physical node into a semi-physical node, and establishes a discrete event simulation of the self-organizing network based on such a semi-physical node, thereby achieving the purpose of reproducing and locating actual network failures.
[0008] The present invention provides a method for semi-physical simulation of a time-synchronized ad hoc network, comprising the following steps:
[0009] Complete the development of the physical node software source program in advance;
[0010] Compile the developed software source program into target files, link the target files, create position-independent codes, and generate shared library files;
[0011] The shared library is called by semi-physical nodes to simulate physical nodes. During the simulation, the self-organizing network nodes are nodes of the same type, and a data queue is established for each node to store the global variables involved in the shared library. After the shared library program is executed, the global variables in the shared library are read and stored in the data queue of the corresponding node.
[0012] Optionally, it also includes unified management of global variables involved in the software during the software source program development process.
[0013] Optionally, it also includes configuring a discrete event scheduler;
[0014] Using the discrete event scheduler to set the time and order of initial interrupt events according to initial simulation configuration parameters, and sequentially triggering corresponding nodes to call the shared library to complete the simulation of node workflow; and
[0015] The discrete event scheduler inserts newly generated interrupt events into the simulation time.
[0016] Optionally, when multiple interrupt events are triggered at the same time, they are triggered serially in a specific order or a random order, and the simulation time is advanced only after all interrupt events are triggered.
[0017] Optionally, using the semi-physical node to call the shared library to implement simulation of the physical node includes:
[0018] Load simulation parameters using discrete event scheduler;
[0019] After all nodes establish connections with the discrete event scheduler, the discrete event scheduler sends simulation parameter configurations to all nodes to complete activation after the virtual node loads the configuration.
[0020] Optionally, the simulation process also includes:
[0021] When using the discrete event scheduler to advance the simulation time, check whether each node generates a discrete event. If a discrete event is generated, it is processed at the corresponding timestamp.
[0022] The embodiment of the present application also proposes a time-synchronized self-organizing network semi-physical simulation system, including a processor and a memory, wherein the memory stores a computer program, and when the computer program is executed by the processor, the steps of the time-synchronized self-organizing network semi-physical simulation method as described above are implemented.
[0023] The embodiment of the present application separates the software program from the physical node into a semi-physical node, and establishes a discrete event simulation of the self-organizing network based on such a semi-physical node to achieve the function of reproducing and locating actual network failures.
[0024] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS
[0025] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present application. Also, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:
[0026] Figure 1 The basic process diagram of the semi-physical simulation method of a self-organizing network in the embodiment of the present application is shown;
[0027] Figure 2 This is a schematic diagram of generating a shared library file for the semi-physical simulation method of a self-organizing network according to an embodiment of the present application;
[0028] Figure 3 A schematic diagram of a self-organizing network semi-physical simulation system of the self-organizing network semi-physical simulation method according to an embodiment of the present application;
[0029] Figure 4 This is a working diagram of network simulation of the semi-physical simulation method of a self-organizing network according to an embodiment of the present application;
[0030] Figure 5 The simulation timeline maintenance diagram of the semi-physical simulation method of the self-organizing network in the embodiment of the present application is shown as follows
[0031] Figure 6 The following is a schematic diagram of the simulation operation loading mechanism of the semi-physical simulation method of a self-organizing network according to an embodiment of the present application. DETAILED DESCRIPTION
[0032] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.
[0033] The embodiment of the present application provides a time-synchronized semi-physical simulation method for a self-organizing network. The semi-physical simulation method for a self-organizing network in the embodiment of the present application is based on a discrete event scheduler, and completes the construction of a simulation system by designing a node model, a channel model, and a network model. It also supports the configuration of simulation parameters such as network environment parameters, channel model parameters, and node model parameters, and initializes parameters such as the number of nodes, communication distance, node distribution range, and node operation trajectory through a configuration file, so that the self-organizing network simulation can adapt to different application requirements. Specifically, Figure 1 , Figure 2 As shown, the following steps are included:
[0034] In step S101, the development of the physical node software source program is completed in advance. In some embodiments, the global variables involved in the software are uniformly managed during the software source program development process.
[0035] In step S102, the developed software source program is compiled into a target file, and the target file is linked to create a position-independent code to generate a shared library file. The generated shared library file can be dynamically loaded into the memory.
[0036] In practical applications, the nodes in the ad hoc network are all nodes of the same type. When multiple nodes involve calling the same shared library, the global variables in the shared library will be tampered. In step S103, the embodiment of the present application uses a semi-physical node to call the shared library to simulate the physical node. During the simulation, the ad hoc network nodes are nodes of the same type, and a data queue for storing the global variables involved in the shared library is established for each node. After the shared library program is executed, the global variables in the shared library are read and stored in the data queue of the corresponding node. After the simulation is completed, the simulation results can be obtained from the data queues of each node.
[0037] The embodiment of the present application separates the software program from the physical node into a semi-physical node, and establishes a discrete event simulation of the self-organizing network based on such a semi-physical node to achieve the function of reproducing and locating actual network failures.
[0038] In some embodiments, Figure 3 As shown, it also includes configuring a discrete event scheduler;
[0039] The discrete event scheduler is used to set the time and order of the initial interrupt event according to the initial simulation configuration parameters, and trigger the corresponding nodes to call the shared library in sequence to complete the simulation of the node workflow. That is, in the specific example, the discrete event scheduler maintains the time consistency of all simulation nodes, and the discrete event scheduler sets the time and order of the initial interrupt event according to the initial simulation configuration parameters, and triggers them in sequence.
[0040] The discrete event scheduler inserts the newly generated interruption event into the simulation time. In some specific examples, the operation of the node may cause a new interruption event to occur, and the discrete event scheduler inserts the newly generated interruption event into the simulation timeline.
[0041] In some embodiments, when multiple interrupt events are triggered at the same time, they are triggered serially in a specific order or a random order, and the simulation time is advanced only after all interrupt events are triggered. Figure 4 , Figure 5 As shown in the figure, taking the self-organizing network using TDMA access system as an example, the discrete event scheduler advances the time unit at the time slot level. Different from the standard TDMA time slot advancement method, the time slot interval in the discrete event scheduler is related to the speed of discrete event processing in the time slot. If there is no discrete event in the time slot, the discrete event scheduler advances quickly. If there is a discrete event in the time slot, the discrete event scheduler advances slowly.
[0042] In some specific examples, after starting the simulation system, the discrete event scheduler maintains the consistency of simulation time. As the middle-end events are triggered, the data queue of the node is updated.
[0043] When the interrupt event that ends the simulation is triggered, the simulation stops, and the simulation results are obtained by sorting out the data queues of each node.
[0044] In some embodiments, Figure 6 As shown, using the semi-physical node to call the shared library to realize the simulation of the physical node includes: using the discrete event scheduler to load the simulation parameters; after all nodes are connected to the discrete event scheduler, the discrete event scheduler sends the simulation parameter configuration to all nodes to complete the activation after the virtual node loads the configuration. In a specific example, the specific loading mechanism of the simulation system operation is that after the discrete event scheduler loads the simulation parameters such as the channel model and the network model, it enters the node management mode and waits for all nodes to establish a connection with the discrete event scheduler. After all nodes are connected, the discrete event scheduler sends parameter configuration to all nodes and waits for the virtual node to load the configuration and complete activation.
[0045] In some embodiments, the simulation process further includes:
[0046] When using the discrete event scheduler to advance the simulation time, check whether each node generates a discrete event. If a discrete event is generated, it is processed at the corresponding timestamp. If no discrete event is generated, the simulation time is accelerated.
[0047] The semi-physical simulation method for a self-organizing network in the embodiment of the present application does not involve the access of physical nodes to the simulation system, thus avoiding the problem of inconsistency between simulation time and real time. At the same time, the node model does not involve simulation modeling, and a semi-physical simulation node is generated by calling a software program of a physical node. The simulation node and the physical node execute the same software program, and the obtained simulation result is more realistic and reliable.
[0048] The physical node of the semi-physical simulation method of the embodiment of the present application includes two parts: hardware and software. The software program runs on the hardware, and the self-organizing network simulation mainly focuses on the logical characteristics of the software program. Therefore, the software program is separated from the physical node into a semi-physical node, and a discrete event simulation system of the self-organizing network is established based on such a semi-physical node. All nodes of the semi-physical simulation method of the embodiment of the present application are semi-physical node models with the characteristics of time synchronization; and all nodes have the same logical characteristics as physical nodes, and the obtained simulation results are highly realistic and can achieve the ability to reproduce and locate actual network failures.
[0049] The embodiment of the present application also proposes a time-synchronized self-organizing network semi-physical simulation system, including a processor and a memory, wherein the memory stores a computer program, and when the computer program is executed by the processor, the steps of the time-synchronized self-organizing network semi-physical simulation method as described above are implemented.
[0050] It should be noted that in the various embodiments of the present application, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the presence of other identical elements in the process, method, article or device including the element.
[0051] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.
[0052] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for a terminal (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods described in each embodiment of the present application.
[0053] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.
Claims
1. A time-synchronized semi-physical simulation method for a self-organizing network, characterized in that: The steps include: Complete the development of the physical node software source program in advance; Compile the developed software source program into target files, link the target files, create position-independent codes, and generate shared library files; The shared library is called by semi-physical nodes to simulate physical nodes. During the simulation, the self-organizing network nodes are nodes of the same type, and a data queue is established for each node to store the global variables involved in the shared library. After the shared library program is executed, the global variables in the shared library are read and stored in the data queue of the corresponding node.
2. The method for semi-physical simulation of a time-synchronized ad hoc network according to claim 1, characterized in that: It also includes unified management of global variables involved in the software during the software source program development process.
3. The time-synchronized self-organizing network semi-physical simulation method according to claim 1, characterized in that: It also includes configuring a discrete event scheduler; The discrete event scheduler is used to set the time and order of the initial interrupt event according to the initial simulation configuration parameters, and the corresponding nodes are triggered to call the shared library in turn to complete the simulation of the node workflow; as well as, The discrete event scheduler inserts newly generated interrupt events into the simulation time.
4. The method for semi-physical simulation of a time-synchronized ad hoc network as claimed in claim 3, characterized in that: In the case of multiple interrupt events that are triggered at the same time, they are triggered serially in a specific order or a random order, and the simulation time is advanced only after all interrupt events are triggered.
5. The method for semi-physical simulation of a time-synchronized ad hoc network according to claim 4, characterized in that: Using the semi-physical node to call the shared library to simulate the physical node includes: Load simulation parameters using discrete event scheduler; After all nodes establish connections with the discrete event scheduler, the discrete event scheduler sends simulation parameter configurations to all nodes to complete activation after the virtual node loads the configuration.
6. The method for semi-physical simulation of a time-synchronized ad hoc network according to claim 5, characterized in that: The simulation process also includes: When using the discrete event scheduler to advance the simulation time, check whether each node generates a discrete event. If a discrete event is generated, it is processed at the corresponding timestamp.
7. A time-synchronized self-organizing network semi-physical simulation system, characterized in that: The method comprises a processor and a memory, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the steps of the time-synchronized self-organizing network semi-physical simulation method as claimed in any one of claims 1 to 6 are implemented.