A space-ground integrated network terminal simulation system and method

Abstract

This invention provides a space-air-ground integrated network terminal simulation system, comprising: multiple user terminal simulation models for simulating user terminals in different scenarios within a space-air-ground integrated network, each user terminal simulation model being deployed in a container; multiple base station simulation models for simulating base stations in a space-air-ground integrated network, each base station simulation model being deployed in a container; multiple core network simulation models for simulating the core network in a space-air-ground integrated network, each core network simulation model being deployed in a container; multiple operation and maintenance management units for reporting the status of each container, with one operation and maintenance management unit configured in each container; and a simulation database cluster for storing simulation data generated by each container running in the user resource server node, comprising multiple database nodes, each database node being deployed in a containerized manner.

Description

Technical Field

[0001] This invention relates to the field of satellite communication technology, specifically to the field of simulation of integrated space-ground network design in the field of satellite communication technology, and more specifically, to a simulation system and method for integrated space-ground network terminals during the demonstration, construction, and use of integrated space-ground networks. Background Technology

[0002] The rapid growth of internet access has brought the global population online, reaching a penetration rate of 65.6%. However, the growth rate is now declining sharply and gradually leveling off, reaching a bottleneck. More than 3 billion people worldwide still lack internet access, particularly in remote mountainous areas, oceans, deserts, and even the Arctic and Antarctic, creating a new digital divide and information poverty. Low-Earth orbit (LEO) satellite communication systems offer low latency, global coverage, and high throughput. Furthermore, with advancements in aerospace technology, electronic devices, antenna theory and equipment, and the increasing convergence of communication, computing, and storage, costs are gradually decreasing, making the construction of large-scale broadband LEO satellite constellations possible and helping to address the digital divide and information poverty. In today's 5G era, terrestrial fiber optics and airborne radio waves can no longer meet people's needs. Integrated space-air-ground satellite internet will become a crucial solution for 5G and subsequent 6G. Integrated space-air-ground satellite internet combines LEO satellite networks and terrestrial 5G networks, capable of supporting the massive user base of 5G and subsequent 6G. Before formal network deployment, network testing and verification are necessary. With the advent of the information age, low-Earth orbit (LEO) space has become an increasingly important resource, leading to a growing demand for satellite internet design and testing. Since it's impossible to conduct on-site testing throughout the entire communication system design process, developing a simulation and verification method for building a massive number of integrated space-ground terminal models is essential. However, considering the enormous user and equipment scale of an integrated space-ground satellite internet, testing and verification costs are a significant concern. Therefore, a testing and verification scheme is needed that, before formal network deployment, tests and verifies key performance indicators such as network capacity, access rate, call drop rate, and bit error rate under different combinations of satellites and ground base stations, and with massive user access and service initiation conditions. This provides a theoretical basis for formal network deployment.

[0003] For testing and verifying the construction and parallel processing of scenarios involving massive numbers of terminals (tens of thousands or even hundreds of thousands), traditional methods mainly employ two approaches: one is a modular hardware stacking approach using server clusters; the other is a node thread queuing approach. Currently, high-performance computers typically have 2-3 processor cores processing user equipment in a 5G cell, approximately 200-300 user terminals, achieving a 1:1 simulation ratio. However, this requires large-scale hardware support, significantly increasing cost and management complexity. Adding to the user terminal scale impacts existing simulations, making real-time user scale control impossible. Furthermore, the limited number of hardware ports restricts the access of massive numbers of user terminals. If a simulation node process queuing approach is used, it cannot meet the real-time requirements of simulations under large-scale computational tasks. Summary of the Invention

[0004] Therefore, the purpose of this invention is to overcome the shortcomings of the prior art and provide a space-ground integrated network terminal simulation system and method based on container resource virtualization technology.

[0005] According to a first aspect of the present invention, a space-ground integrated network terminal simulation system is provided. The system includes multiple server nodes, and each server node can be configured with multiple container units, each container unit can run multiple containers. The system further includes: multiple user terminal simulation models for simulating user terminals in different scenarios within the space-ground integrated network, each user terminal simulation model being deployed in a container created by a container unit on a server node; multiple base station simulation models for simulating base stations in the space-ground integrated network, each base station simulation model being deployed in a container created by a container unit on a server node; multiple core network simulation models for simulating the core network in the space-ground integrated network, each core network simulation model being deployed in a container created by a container unit on a server node; multiple operation and maintenance management units for reporting the status of each container, each container being configured with one operation and maintenance management unit; and a simulation database cluster for storing simulation data generated by the operation of each container on the user resource server node, comprising multiple database nodes, each database node being deployed as a container in a container unit on a server node.

[0006] Preferably, the user terminal simulation model is one of the following: a high-concurrency user terminal model, a user terminal access model, a user terminal switching model, and a massive online user terminal model.

[0007] Preferably, the simulated database cluster includes a MySQL cluster, which includes multiple MySQL nodes, each of which is deployed in a container unit of a server node in a containerized manner;

[0008] A Redis cluster consists of multiple Redis nodes, each deployed as a container within a container unit on a server node; a Mongo cluster consists of multiple Mongo nodes, each deployed as a container within a container unit on a server node.

[0009] Preferably, the system further includes: a message probe middleware, used to acquire all simulation data generated by all running server nodes in real time, and to process the simulation data. In some embodiments of the present invention, the message probe middleware includes: a test probe module, used to acquire all simulation data generated by all running containers corresponding to the simulation task in real time; and a RocketMQ cluster, used to process the simulation data acquired by the test probe module, which includes multiple RocketMQ nodes and processes the data using a producer / consumer pattern, wherein each RocketMQ node is deployed as a container in a container unit of a server node.

[0010] Preferably, the system further includes: a resource management service module, used to schedule resources in the server node for the simulation task corresponding to the simulation requirement based on the simulation requirement, create a container for simulation based on the called resources, and destroy the container to release resources after the simulation ends.

[0011] Preferably, the system further includes: a human-computer interaction module, used to provide a human-computer interaction interface for users to configure simulation or trigger the simulation to stop; a scenario service module, used to obtain simulation configuration to generate simulation tasks and system configuration or to generate a command to stop simulation based on the trigger to stop simulation; wherein, the system configuration includes at least simulation protocol configuration and user terminal type configuration; a message queue module, used to store simulation task and system configuration message queues and the command to stop simulation; an operation management service module, used to generate a list of resources required for simulation based on simulation tasks and system configuration, and to request simulation resources, issue simulation tasks to containers related to simulation tasks, start simulation tasks, collect simulation results generated by container operation, and issue push requests to push simulation results to the human-computer interaction module; a model algorithm service module, used to provide algorithm analysis services corresponding to simulation tasks to analyze simulation data generated during container operation to obtain simulation results; and a data analysis and processing service module, used to push simulation results to the human-computer interaction module based on the push request from the operation management service module.

[0012] According to a second aspect of the present invention, a simulation method based on the system described in the first aspect of the present invention is provided. The method includes: S1, acquiring a simulation task and system configuration; S2, invoking required resources based on the simulation task and system configuration; S3, creating multiple containers required for the simulation task from the invoked resources, and deploying the user terminal simulation model, base station simulation model, core network simulation model, simulation operation and maintenance management unit, and simulation database node required for the simulation task in the created containers; S4, running the containers created in step S3 to simulate an integrated air-space-ground network to generate simulation data. Preferably, in step S4, during the simulation process, the physical layer is trimmed according to preset rules before the simulation is performed.

[0013] Compared with existing technologies, the advantages of this invention are as follows: Based on resource virtualization, this invention models, runs, and tests massive terminal scenarios, can achieve 1:1 terminal modeling with relatively few hardware resources, and can realize the clustered deployment, operation, and management of various modules. It can also perform real-time analysis and processing of massive simulation data, realize large-scale scenario simulation and effective verification of key indicators for integrated space-air-ground satellite internet, and provide favorable support for the construction of integrated space-air-ground satellite internet. Attached Figure Description

[0014] The embodiments of the present invention will be further described below with reference to the accompanying drawings, wherein:

[0015] Figure 1 This is a schematic diagram of a container running architecture on a server node according to an embodiment of the present invention;

[0016] Figure 2 This is a schematic diagram of the resource scheduling and management functional structure according to an embodiment of the present invention;

[0017] Figure 3 This is a schematic diagram of a specific protocol simulation architecture according to an embodiment of the present invention;

[0018] Figure 4 This is a schematic diagram illustrating the working principle of the probe reporting middleware according to an embodiment of the present invention;

[0019] Figure 5 is a schematic diagram comparing the protocol flow of a 5G protocol user before and after user plane protocol trimming according to an embodiment of the present invention. In Figure 5(a), the user plane protocol flow of a 5G protocol user is shown in the schematic diagram, and Figure 5(b) is a simplified protocol flow of a 5G protocol simulated user after user plane protocol trimming.

[0020] Figure 6 is a schematic diagram comparing the control plane protocol flow before and after the 5G protocol user protocol trimming according to an embodiment of the present invention. In Figure 6(a), the control plane protocol flow of the 5G protocol user is shown in the schematic diagram, and Figure 6(b) is a simplified protocol flow of the 5G protocol simulated user after the control plane trimming is shown in the schematic diagram.

[0021] Figure 7 This is a schematic diagram illustrating the working principle of a simulation system according to an embodiment of the present invention. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of this invention clearer, the invention is further described in detail below through specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0023] As described in the background section, existing technologies for simulating massive numbers of terminals in integrated space-air-ground satellite internet networks employ either hardware stacking or node threading queuing schemes. The hardware stacking scheme requires a large amount of hardware when dealing with massive numbers of terminals, resulting in high costs and complex management. The node threading scheme, on the other hand, cannot meet real-time requirements. Therefore, this invention proposes a simulation scheme for massive numbers of terminals in integrated space-air-ground networks that is low in hardware cost and can meet real-time requirements.

[0024] In integrated air-space-ground networks, massive terminal simulation is primarily used to simulate massive terminal services under different scenarios to verify the rationality of the integrated air-space-ground network design. Since user terminals are mobile and constantly changing, the situation of user terminals accessing the network is also constantly changing. Therefore, the inventors proposed a container virtualization-based solution to simulate the access of massive user terminals, and used the corresponding network protocols to simulate the user terminal movement trajectory and physical layer information transmission characteristics. Due to the elastic scaling and mutual isolation characteristics of containers, the hardware requirements are far lower than those of hardware stacking simulation solutions, while still meeting real-time requirements.

[0025] To better understand the present invention, the present invention will be described in detail below with reference to the accompanying drawings and embodiments.

[0026] This invention leverages the elastic scaling and isolation characteristics of containers to deploy user terminal simulation models, base station simulation models, and simulation database nodes as services within containers. By scheduling and deploying the resources required for different scenarios, different containers are orchestrated to model various scenarios. In summary, this invention provides a resource virtualization simulation modeling approach based on container technology, enabling distributed management of containers. Through the management of containerized application resources, it achieves automated container deployment and elastic scaling, and employs load balancing strategies to manage applications, thereby realizing the modeling of user terminal models. Figure 1 As shown, based on distributed server computing nodes, a container orchestration system and a container runtime engine schedule server resources to create containers and deploy user models within these containers. The container orchestration management system and container runtime engine also manage resource scheduling to deploy different models for different scenarios, thus achieving simulation system modeling. According to one embodiment of the invention, containers use Docker technology as a platform for resource provision and hosting. A Pod (container unit) is the smallest deployment and running unit. Multiple Pods can exist under a computing node, and one or more containers can be created under a Pod. One or more model services can be deployed within a container. Preferably, one model service is deployed within a container. Services with high business logic coupling are deployed in containers within the same Pod. Each container is configured with an operation and maintenance management unit to report the status of its container and determine whether the container is runnable based on its status. The container orchestration management system and container runtime engine are technologies known to those skilled in the art, and will not be described in detail here. This invention treats them as a whole for resource scheduling and management during the construction of the simulation system. Specifically, as... Figure 2 As shown, resource scheduling and management includes container creation, destruction, restart, and protection, and manages resources based on load balancing strategies. In this invention, Kubernetes container orchestration technology is preferably used to implement resource scheduling and management. Given the isolation of container resources, the simulation system becomes more robust, effectively solving the limitations of system resources (hardware resources and ports, etc.) in scenarios with massive numbers of models. If a user's simulation resources fail, the resource scheduling platform supports dynamic system scaling to quickly restore the user's simulation environment (recording user information and scenario requirements before destruction to protect the container). As scenarios become richer and computational load increases, when physical resource alarms occur, compute nodes or Pods can be dynamically added and run without affecting the operation of the current simulation service.

[0027] The massive terminal simulation system associated with the integrated air-space-ground network involves the simulation of access network clusters (i.e., user terminal clusters and base stations), core network clusters, and database platforms. To ensure massive simulation, all modules support distributed deployment and expansion, and both the access network cluster and the core network cluster are containerized. For the core network cluster, an integrated core network module approach is adopted, integrating multiple network elements to achieve load balancing for base station links and UE access, meeting the needs of massive user access. The simulated access network consists of virtual terminals and virtual base stations, supporting major L2 and L3 functions. One terminal process can simulate 1,000 concurrent terminals or 10,000 online users, and multiple servers can start many virtual terminal processes to achieve 100,000 terminal simulations. Specifically, this invention is based on container virtualization technology. It deploys user terminal simulation models (for simulating user UE), base station simulation models (for simulating base station GNB), core network simulation models (for simulating CN), simulation operation and maintenance management units (for simulating operation and maintenance management units OAM), and simulation database platforms (a cluster of database nodes) in containers as services to model the simulation system. It achieves the simulation of massive terminals by distributing multiple containers. When simulation is needed, resource management scheduling is used to schedule the corresponding server resources to create the required containers. The container size can be dynamically adjusted according to demand without affecting the simulation that is already running.

[0028] According to an embodiment of the present invention, the clustered deployment principle of the integrated air-space-ground special protocol simulation architecture based on the above embodiments is as follows: Figure 3As shown, this architecture includes several parts: front-end display, probe reporting middleware, access network cluster, integrated core network, and data management platform. The front-end display includes page display (for page presentation) and a JAVA backend (for backend control), used to implement the simulation display function. This is a technology known to those skilled in the art and will not be elaborated here. The probe reporting middleware is used to acquire simulation data in real time and report it to the front-end for display. A RocketMQ cluster is preferably configured to process the simulation data. The probe reporting middleware acquires data generated by each node based on test probes and reports it to the backend control to achieve simulation data analysis and display. High-concurrency access is used to simulate high-concurrency access scenarios for user terminals (simulating concurrent services of 1000 users), and massive online access is used to simulate user control... In a massive access scenario (simulating control plane access services for 10,000 users), virtual terminals (each virtual terminal is a user terminal simulated by a user simulation model deployed in a container) communicate with virtual base stations (base stations simulated by a base station simulation model deployed in a container) via UDP to generate simulation data; the integrated core network includes a virtual core network cluster, which communicates with the digital network (DN) via a gateway to generate simulation data; a data management platform is used to manage a database cluster that stores the simulation data. According to one embodiment of the present invention, the database cluster uses a Redis cluster, a MySQL cluster, and a MongoDB cluster to store the simulation data.

[0029] According to one embodiment of the present invention, such as Figure 4As shown, during the simulation, the test probe acquires all simulation data generated in the created and running container in real time and reports and pushes it to the RocketMQ cluster. The RocketMQ cluster includes multiple RocketMQ nodes, each of which adopts a producer / consumer pattern to acquire and process messages. Producers report messages, and consumers generate message queues based on the results of message processing. RocketMQ supports clustered deployment and can process simulation data reported by multiple producers simultaneously, handling up to millions of messages and reporting the processing results to the page for display. The message queue consumers in RocketMQ push all real-time messages sequentially to the backend middleware, ensuring both performance and real-time performance. The backend middleware sends the data processing results to the page for display. The RocketMQ cluster includes a Nameserver cluster and a Broker cluster. Since the Nameserver cluster, Broker cluster, and producer / consumer pattern are technologies known to those skilled in the art, this invention will not elaborate further. After the test probe acquires the simulation data generated by the container in real time, it reports the message and simultaneously stores the message in the memory database, and synchronizes it to the disk database (MySQL, Redis or Mongo) to support historical data queries.

[0030] Furthermore, to achieve better and faster simulation of massive terminals, an embodiment of the present invention also includes a protocol simplification scheme. This scheme focuses on the protocol parts related to processes and key indicators during simulation, abstracts the physical layer, and simplifies other protocols to improve simulation efficiency and reduce hardware costs. Based on the concept of protocol simplification, when simulating massive terminal scenarios or verifying key technologies, the physical layer's role includes providing bit error rate, spectral efficiency, and measurement information. It uses signal-to-noise ratio (SNR) forwarding and presents the correspondence between bit error rate and SNR to the upper-layer protocol using link budget or a graph. During upper-layer simulation, different SNR values ​​can convert the bit error rate into packet loss rate, serving as an important input for evaluating upper-layer protocol performance and key algorithms. Simultaneously, the upper-layer protocol is simplified by removing some transmission protocols, such as broadcast messages and paging procedures, without affecting the protocol flow. For example, Figure 5 shows a comparison of the protocol flow before and after the user plane protocol of a 5G protocol (5G NR) user is trimmed (Figure 5(a) shows the user plane protocol flow of a 5G protocol user, and Figure 5(b) shows the simplified protocol flow after the user plane protocol of a 5G protocol simulated user is trimmed), and Figure 6 shows a comparison of the control plane protocol flow before and after the 5G protocol (5G NR) user protocol is trimmed (Figure 6(a) shows the control plane protocol flow of a 5G protocol user, and Figure 6(b) shows the simplified protocol flow after the control plane protocol of a 5G protocol simulated user is trimmed). In this comparison, NAS-SM is the user plane protocol, ..., RRC is the radio resource control protocol, PDCP is the packet data aggregation protocol, ..., MAC is the physical layer access protocol, PHY is the media access control protocol, ... Since these protocols are known to those skilled in the art of communication, they are only briefly illustrated here without detailed explanation. As can be seen, based on the protocol trimming scheme proposed by the inventors, in the simulation system, the user plane and control panel of the terminal and base station have trimmed the physical layer (PHY) and radio frequency antenna (RF). During the simulation process, information such as the bit error rate calculated by the simulation system is integrated into the simulated media access control layer (SimulateMAC), and relevant parameters are obtained through simulation functions. Data is transmitted through the port in the form of IP packets at the radio link control module layer (RLC). In the base station simulation part, the centralized unit and the distributed unit are combined into one, simplifying the F1AP and E1AP protocols, reducing most of the internal signaling interactions, greatly improving the simulation rate, and without affecting the simulation effect.

[0031] Through the above embodiments, the concurrent access and call power of massive users can be verified using specialized protocol simulation. (Still referring to...) Figure 3In a clustered modular deployment, different models can be built according to different scenario simulation requirements, and corresponding protocols can be loaded for simulation verification. For example, to evaluate indicators such as access rate and handover frequency of satellite internet, it is only necessary to build an access model or handover model for a large number of terminals, and control the signaling messages initiated by the simulated terminals. For example, the access model controls the simulated terminals to send access messages, and calculates the access rate by counting the number of access requests and successful accesses; the handover model controls the simulated terminals to send handover messages, and calculates the handover success rate by counting the number of handover requests and successful handovers. For example, if only the control panel service of satellite internet is considered, and there is no need for data plane services, a large number of online terminal service models with only control plane protocols loaded can be built. If data service-related indicators, such as network bandwidth, bit error rate, and packet loss rate, are required, a high-concurrency terminal service model supporting both the control panel and user plane can be built. The model controls terminal behavior and simulates a large number of terminals performing services such as pinging, packet flooding, and audio / video transmission. It tests the capacity to handle high-concurrency services, loads corresponding data services, and obtains wireless environment data and user plane data transmission status through physical layer simulation and channel simulation calculations, calculating bandwidth, bit error rate, and packet loss rate. The high-concurrency terminal model and the massive online terminal model can simulate 1000 concurrent terminals or 10000 online users. Combined with containerization methods for hardware and software resources, multiple servers can simultaneously start and run dozens of virtual terminal processes, enabling the simulation of service scenarios involving 100,000 terminals without requiring a large number of servers, significantly reducing costs.

[0032] like Figure 7As shown, based on the modeling of the above embodiments, the system is further equipped with a resource management service module (used to schedule resources in the server node for simulation tasks corresponding to simulation requirements, create containers for simulation based on the called resources, and destroy the containers to release resources after the simulation ends), a human-computer interaction module (used to provide a human-computer interaction interface for users to configure simulation or trigger the simulation to stop), a scenario service module (used to obtain simulation configuration to generate simulation tasks and system configuration or generate instructions to stop simulation based on the trigger to stop simulation; wherein, the system configuration includes at least simulation protocol configuration and user terminal type configuration), a message queue module (used to store simulation task and system configuration message queues and instructions to stop simulation), and an operation management service module (used to perform system operations based on simulation tasks and system configuration). The system includes operation management, which includes requesting simulation resources, issuing simulation tasks to containers related to the simulation tasks, starting simulation tasks, collecting simulation results generated by container operation, and issuing push requests to push simulation results to the human-computer interaction module; a model algorithm service module (used to provide algorithm analysis services corresponding to simulation tasks to analyze simulation data generated during container operation to obtain simulation results, including object and motion model services and environment and channel model services, used to obtain physical layer simulation results, user terminal motion trajectories, etc. based on simulation data); and a data analysis and processing service module (used to push simulation results to the human-computer interaction module based on push requests from the operation management service module). It can realize the testing and verification of processes and key indicators of massive user terminals in various scenarios in the integrated air-space-ground network.

[0033] by Figure 7 Taking the simulation system shown as an example, a complete simulation process includes the following steps:

[0034] Step 1: Users configure the simulation through the interactive interface provided by the human-computer interaction module, including configuring the network composition, attributes and quantity of each network element, etc.

[0035] Step 2: The scenario service module obtains the simulation configuration, generates simulation tasks and system configuration, and distributes the simulation tasks and system configuration through the message queue module;

[0036] Step 3: The operation management service module receives the simulation task and configuration;

[0037] Step 4: The operation service management module generates a list of required resources based on the simulation scenario and requests simulation resources from the resource management service module.

[0038] Step 5: The resource management service module parses the resource list corresponding to the simulation configuration and calls server resources to create the containers required by each module in the simulation modeling. Specifically, the server resource nodes related to the database are referred to as public resource server nodes, used to create the containers corresponding to the database nodes. Other server resource nodes are referred to as user resource server nodes, used to create user simulation models, base station simulation models, core networks, etc. The runtime protocol architecture of the created containers is as follows: Figure 3 As shown, it will not be repeated here;

[0039] Step 6: The operation and maintenance management unit in each container reports the status of its own container to the operation and maintenance service module to determine whether the container is ready;

[0040] Step 7: After ensuring all containers are ready, the operation and maintenance service module issues simulation tasks to the containers.

[0041] Step 8: The operation and maintenance service module starts the simulation task and schedules various events according to the business scenario corresponding to the simulation task;

[0042] Step 9: During the simulation process, each simulation module / model running in the container calls the model algorithm service module to perform algorithm analysis according to the business process corresponding to the simulation task, so as to obtain physical layer simulation results, motion trajectory, etc.

[0043] Step 10: The operation and maintenance management unit of each container reports simulation data in real time, including key signaling messages (such as access request, access completion, handover execution, handover completion, etc.) and wireless environment data (such as bit error rate, packet loss rate, latency, etc. calculated based on channel simulation and physical layer simulation).

[0044] Step 11: After receiving the reported simulation data, the operation and management service module sends a push request to the data analysis and processing module.

[0045] Step 12: The data analysis and processing module pushes simulation data to the front-end human-computer interaction module based on the push request from the operation and management service module, so as to display it on the front-end interactive interface;

[0046] Step 13: Users observe simulation data through the interactive interface. When a simulation task needs to be customized, users send a request to stop the simulation to the scene service module through the interactive interface.

[0047] Step 14: After receiving the user's request to stop the simulation, the scenario service module issues a stop simulation command through the message queue module;

[0048] Step 15: The operation management service module receives the stop simulation command;

[0049] Step 16: The operation management service module sends a stop simulation message to the corresponding container according to the stop simulation command, and the process in the container is stopped.

[0050] Step 17: The operation service management module requests the resource control service module to release the previously fragmented container resources based on the stop simulation command;

[0051] Step 18: The resource management service module, upon request from the operation service management module, destroys all containers previously created based on the simulation task to release the corresponding resources.

[0052] In summary, this invention, based on resource virtualization, models, runs, and tests massive terminal scenarios. It can achieve 1:1 terminal modeling with relatively few hardware resources, and enables clustered deployment, operation, and management of various modules. It can also perform real-time analysis and processing of massive simulation data, realize large-scale scenario simulation and effective verification of key indicators for integrated space-air-ground satellite internet, and provide favorable support for the construction of integrated space-air-ground satellite internet.

[0053] It should be noted that although the steps are described in a specific order above, it does not mean that the steps must be executed in the above specific order. In fact, some of these steps can be executed concurrently or even in a different order, as long as the required function can be achieved.

[0054] This invention can be a system, method, and / or computer program product. A computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for causing a processor to implement various aspects of the invention.

[0055] Computer-readable storage media can be tangible devices that hold and store instructions for use by an instruction execution device. Computer-readable storage media can include, for example, but not limited to, electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination thereof.

[0056] The various embodiments of the present invention have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical application, or technical improvements to the embodiments in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. A space-ground integrated network terminal simulation system, the system comprising multiple server nodes, each server node being configured with multiple container units, and each container unit running multiple containers, wherein, The system also includes: Multiple user terminal simulation models are used to simulate user terminals in different scenarios in the integrated space-ground network, and each user terminal simulation model is deployed in a container created by a container unit on a server node. Multiple base station simulation models are used to simulate base stations in an integrated space-ground network, and each base station simulation model is deployed in a container created by a container unit on a server node; Multiple core network simulation models are used to simulate the core network in the integrated space-ground network, and each core network simulation model is deployed in a container created by a container unit on a server node; Multiple operation and maintenance management units are used to report the status of each container, and one operation and maintenance management unit is configured in each container; The simulation database cluster is used to store the simulation data generated by each container running in the user resource server node. It includes multiple database nodes, and each database node is deployed in a container unit in the server node.

2. The system according to claim 1, characterized in that, The user terminal simulation model is one of the following: user terminal high concurrency model, user terminal access model, user terminal switching model, and user terminal massive online model.

3. The system according to claim 1, characterized in that, The simulation database cluster includes: A MySQL cluster consists of multiple MySQL nodes, each of which is deployed as a container within a container unit on a server node. A Redis cluster consists of multiple Redis nodes, each of which is deployed as a container within a container unit on a server node. A Mongo cluster consists of multiple Mongo nodes, each of which is deployed as a container within a container unit on a server node.

4. The system according to claim 1, characterized in that, The system also includes: The message probe middleware is used to acquire all simulation data generated by all running server nodes in real time, and to process the simulation data.

5. The system according to claim 4, characterized in that, The message probe middleware includes: The test probe module is used to acquire all simulation data generated by all running containers corresponding to the simulation task in real time. The RocketMQ cluster is used to process simulation data obtained by the test probe module. It consists of multiple RocketMQ nodes and uses a producer / consumer pattern to process the data. Each RocketMQ node is deployed as a container in a container unit of the server node.

6. The system according to claim 1, characterized in that, The system also includes: The resource management service module is used to schedule resources in the server node for the simulation task corresponding to the simulation requirement based on the simulation requirements, create containers for simulation based on the called resources, and destroy the containers to release resources after the simulation ends.

7. The system according to claim 6, characterized in that, The system also includes: The human-computer interaction module provides a human-computer interaction interface for users to configure simulation or trigger the simulation to stop. The scenario service module is used to obtain simulation configuration to generate simulation tasks and system configuration, or to generate instructions to stop simulation based on a stop simulation trigger; wherein, the system configuration includes at least simulation protocol configuration and user terminal type configuration; The message queue module is used to store simulation task and system configuration message queues, as well as instructions to stop the simulation; The operation management service module is used to generate a list of resources required for simulation based on simulation tasks and system configuration, as well as to request simulation resources, issue simulation tasks to containers related to simulation tasks, start simulation tasks, collect simulation results generated by container operation, and issue push requests to push simulation results to the human-computer interaction module. The model algorithm service module is used to provide algorithm analysis services corresponding to simulation tasks to analyze the simulation data generated during container operation and obtain simulation results. The data analysis and processing service module is used to push simulation results to the human-computer interaction module based on push requests from the operation management service module.

8. A simulation method based on the system described in any one of claims 1-7, characterized in that, The method includes: S1. Obtain simulation tasks and system configuration; S2. Based on the simulation task and system configuration, call the resources required; S3. In the resources called, create multiple containers required for the simulation task, and deploy the user terminal simulation model, base station simulation model, core network simulation model, simulation operation and maintenance management unit, and simulation database node required for the simulation task in the created containers; S4. Run the container created in step S3 to simulate an integrated air-space-ground network and generate simulation data.

9. The method according to claim 8, characterized in that, In step S4, during the simulation process, the physical layer is trimmed according to preset rules before the simulation is executed.

10. A computer-readable storage medium, characterized in that, It stores a computer program that can be executed by a processor to implement the steps of the method of any one of claims 8-9.

11. An electronic device, characterized in that, include: One or more processors; A storage device for storing one or more programs, which, when executed by one or more processors, cause the electronic device to perform the steps of the method as described in any one of claims 8-9.

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