A low-orbit satellite Internet of Things communication method and system based on dynamic blockchain

Abstract

The present invention discloses a low-orbit satellite Internet of Things communication method and system based on dynamic blockchain, the method specifically includes: taking at least one ground station as a consensus node in each network partition to form a consensus network, and using the RBFT algorithm to select a master node from a number of consensus nodes in each consensus network; using a satellite transit algorithm to predict the transit information of each low-orbit satellite, and setting the low-orbit satellite passing through any consensus network as the accounting node of the consensus network according to the transit information; obtaining the service request of the satellite communication terminal, forwarding the service request to the master node of the consensus network through the low-orbit satellite of the transit satellite communication terminal, verifying and prioritizing the service request according to the master node, and if the verification is passed, broadcasting and consensus verification are performed to all nodes of the current consensus network. The present invention improves the efficiency and security of low-orbit satellite Internet of Things communication, and provides reliable technical support for satellite Internet applications.

Description

Technical Field

[0001] The present invention relates to the field of satellite Internet of Things technology, and in particular to a low-orbit satellite Internet of Things communication method and system based on dynamic blockchain. Background Art

[0002] With the rapid development of satellite technology, low-orbit satellite IoT has become an important infrastructure for connecting various IoT devices on the earth's surface. At present, the number of low-orbit satellites in orbit has exceeded tens of thousands, and they are widely used in communications, remote sensing, environmental monitoring and other fields. However, with the large-scale application of low-orbit satellites, their communication security issues have become increasingly prominent, especially in the security of the measurement and control domain, access domain and network domain.

[0003] The TT&C domain involves the communication link between the satellite TT&C station and the satellite platform, and it is necessary to ensure the authentication and data protection of the communication link to prevent unauthorized access and data leakage. The access domain involves satellite communication terminals, satellite payloads, etc., and it is necessary to implement authentication and signaling protection between satellite communication terminals and satellite payloads to ensure the integrity and reliability of data transmission.

[0004] As a distributed ledger technology, blockchain technology ensures that data cannot be tampered with through encryption algorithms, realizes a decentralized trust mechanism, and provides a new security guarantee for communication between IoT devices. In the IoT market, blockchain technology has been widely used in device identity authentication, data security storage, and service directory processing, effectively improving the transparency and security of communication between devices.

[0005] However, there are many challenges in applying blockchain technology to low-orbit satellite IoT communications. First, low-orbit satellite payloads are expensive and have limited computing resources, making it difficult to support the high computing power requirements of traditional blockchain consensus algorithms. Second, the communication link between low-orbit satellites and ground stations is dynamic and unstable, requiring efficient identity authentication and key negotiation mechanisms to ensure the security and reliability of the communication link. In addition, there are many types of satellite communication terminal devices in the low-orbit satellite IoT, with different computing capabilities. How to achieve effective access and efficient communication of satellite communication terminal devices is also an urgent problem to be solved.

[0006] In response to the above problems, some existing technologies have proposed solutions. For example, Chinese patent CN202311147696.6 proposes a method to reduce the scale of the consensus network by grouping satellite communication terminals, but this method requires dynamic networking between satellite communication terminals, and has high requirements for interconnection between different manufacturers and different satellite communication terminal systems, and low operability. At the same time, since there is only one consensus node in each orbit, when there is no consensus node above the area where the satellite communication terminal is located, the delay of data transmission will increase.

[0007] Chinese patent CN202410283017.6 proposes a method to reduce the size of blockchain by sharding, dividing satellites, marine equipment, and ground equipment into multiple independent sharded blockchains. However, this method does not provide a method for sharing data between sharded blockchains, and cannot guarantee end-to-end data security from satellite communication terminals to ground data centers.

[0008] Therefore, how to ensure the security of low-orbit satellite Internet of Things communications while reducing the consensus algorithm's requirements for computing power, realizing efficient identity authentication and key negotiation mechanisms, and supporting effective access and efficient communication of different types of satellite communication terminal devices has become a technical problem that needs to be urgently solved in the current low-orbit satellite Internet of Things communications field. Summary of the invention

[0009] The purpose of the present invention is to provide a low-orbit satellite Internet of Things communication method and system based on dynamic blockchain, which improves the efficiency and security of low-orbit satellite Internet of Things communications, provides reliable technical support for satellite Internet applications, and solves at least one of the above-mentioned prior art problems.

[0010] In a first aspect, the present invention provides a low-orbit satellite Internet of Things communication method based on a dynamic blockchain, the method specifically comprising:

[0011] The low-orbit satellite communication network is divided into multiple network partitions. In each network partition, at least one ground station is used as a consensus node to form a consensus network. The RBFT algorithm is used to select the master node from several consensus nodes in each consensus network.

[0012] A satellite transit algorithm is used to predict the transit information of each low-orbit satellite, and based on the transit information, a low-orbit satellite passing through any consensus network is set as a bookkeeping node of the consensus network;

[0013] Obtain the service request of the satellite communication terminal, forward the service request to the master node of the corresponding consensus network through the low-orbit satellite passing through the satellite communication terminal, verify and prioritize the service request according to the master node, and broadcast and verify the consensus to all nodes of the current consensus network if the verification is successful;

[0014] After the consensus verification is passed, the communication data signed by the service private key sent by the satellite communication terminal is obtained in real time according to the low-orbit satellite of the transiting satellite communication terminal. After the service public key verification is performed on the communication data, it is forwarded to any ground station of the current consensus network, and then forwarded to another designated satellite communication terminal or data center through the ground station.

[0015] In a second aspect, the present invention provides a low-orbit satellite Internet of Things communication system based on a dynamic blockchain, the system specifically comprising:

[0016] The first communication module is used to divide the low-orbit satellite communication network into multiple network partitions, use at least one ground station as a consensus node in each network partition to form a consensus network, and use the RBFT algorithm to select a master node from a number of consensus nodes in each consensus network;

[0017] The second communication module is used to predict the transit information of each low-orbit satellite using a satellite transit algorithm, and set the low-orbit satellite passing through any consensus network as a bookkeeping node of the consensus network according to the transit information;

[0018] The third communication module is used to obtain the service request of the satellite communication terminal, forward the service request to the master node of the corresponding consensus network through the low-orbit satellite passing the satellite communication terminal, verify and prioritize the service request according to the master node, and broadcast and verify the consensus to all nodes of the current consensus network if the verification is successful;

[0019] The fourth communication module is used to obtain the communication data signed by the service private key sent by the satellite communication terminal in real time according to the low-orbit satellite of the transiting satellite communication terminal after the consensus verification is passed, and after verifying the service public key of the communication data, forward it to any ground station of the current consensus network, and forward it to another designated satellite communication terminal or data center through the ground station.

[0020] In a third aspect, the present invention provides a computer device comprising: a memory and a processor and a computer program stored in the memory. When the computer program is executed on the processor, a low-orbit satellite Internet of Things communication method based on dynamic blockchain as described in any one of the above methods is implemented.

[0021] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the low-orbit satellite Internet of Things communication method based on dynamic blockchain as described in any one of the above methods is implemented.

[0022] Compared with the prior art, the present invention has at least one of the following technical effects:

[0023] 1. The present invention improves the efficiency and security of low-orbit satellite Internet of Things communications and provides reliable technical support for satellite Internet applications.

[0024] 2. The present invention improves the scalability and fault tolerance of the system by dividing the low-orbit satellite communication network into multiple network partitions, establishing consensus nodes in each partition and selecting the master node using the RBFT algorithm.

[0025] 3. The present invention uses a satellite transit algorithm to predict the transit information of low-orbit satellites and sets accounting nodes to achieve effective recording and verification of communication data.

[0026] 4. The present invention verifies and prioritizes service requests through the master node, thereby ensuring the rationality and efficient processing of service requests.

[0027] 5. The present invention obtains the real-time orbital position information of low-orbit satellites, calculates the position change trend, and combines the ground station distribution data to establish a correspondence model between ground stations and satellite coverage areas. It can accurately calculate the consensus network to which the low-orbit satellite belongs at the current moment and mark it as a serviceable satellite, providing a basis for subsequent communication and data forwarding.

[0028] 6. The present invention constructs a terminal feature vector by acquiring device characteristic information of the satellite communication terminal, and assigns weights according to the importance of the feature vector, thereby achieving a reasonable evaluation of the priority of the satellite communication terminal.

[0029] 7. After the present invention verifies the service public key of the communication data, it determines the distribution strategy of the communication data according to the priority score of the satellite communication terminal and the processing performance of the ground station, thereby realizing the reasonable distribution and efficient processing of the data.

[0030] 8. The present invention improves the system's ability to predict and adapt to future communication data processing capabilities by acquiring the actual processing time of communication data and using a reinforcement learning algorithm to dynamically optimize the allocation strategy.

[0031] 9. The present invention compares the communication window time with a preset threshold to determine whether the communication window time meets the time requirements for identity authentication and key negotiation, thereby ensuring the security and reliability of the communication process.

[0032] 10. The present invention adopts the Kalman filter algorithm to filter the communication link state information, obtains a smooth communication link state estimation value, and improves the prediction accuracy of the communication link state.

[0033] 11. The present invention uses a hidden Markov model to predict the dynamic topological change trend between low-orbit satellites and ground stations, providing a basis for the best time for key negotiation.

[0034] 12. The present invention adopts the Mamdani reasoning method to make fuzzy decisions, determines the best time for key negotiation, and improves the efficiency and security of key negotiation.

[0035] 13. The present invention divides the operation cycle of the low-orbit satellite communication network into multiple time windows through a time window division method, calculates the distance and line of sight angle according to the position information of the low-orbit satellite and the ground station, and determines the existence of a valid link, and further determines the duration and transmission delay of the valid link by calculating the relative movement speed and direction, thereby providing a guarantee for the integrity of the communication link status information.

[0036] 14. The present invention takes maximizing network throughput and transmission efficiency as the optimization goal, adopts genetic algorithm to dynamically adjust the link allocation strategy, and redetermines the communication link status information based on the adjusted link allocation strategy, thereby improving the utilization rate and transmission efficiency of the communication link between the low-orbit satellite and the ground station. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0038] Figure 1 It is a flowchart of a low-orbit satellite Internet of Things communication method based on dynamic blockchain provided by one embodiment of the present invention;

[0039] Figure 2 This is a structural diagram of a low-orbit satellite Internet of Things communication system based on a dynamic blockchain provided by an embodiment of the present invention;

[0040] Figure 3 It is a structural schematic diagram of a computer device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0041] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0042] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0043] It should also be understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0044] As used in the specification and appended claims of this application, the term "if" can be interpreted as "when" or "uponce" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "uponce it is determined" or "in response to determining" or "uponce [described condition or event] is detected" or "in response to detecting [described condition or event]", depending on the context.

[0045] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0046] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0047] In the embodiment of the present application, the execution subject of the process includes a terminal device, which includes but is not limited to: a server, a computer, a smart phone, a tablet computer, and other devices capable of executing the method disclosed in the present application. Figure 1 A schematic diagram of the process of a low-orbit satellite Internet of Things communication method based on a dynamic blockchain disclosed in an embodiment of the present invention is shown, and the details are as follows:

[0048] S101, divide the low-orbit satellite communication network into multiple network partitions, use at least one ground station as a consensus node in each network partition to form a consensus network, and use the RBFT algorithm to select a master node from a number of consensus nodes in each consensus network.

[0049] In this embodiment, the ground station is a ground device installed on the earth for satellite communication. The main functions of the ground station include monitoring satellite operation, orbit measurement, telemetry and remote control, receiving remote sensing and telemetry data, and processing and storing information. The ground station includes a ground measurement and control center, a ground receiving center, a ground data processing center, an image analysis center, and a comprehensive database.

[0050] The consensus nodes have the authority to initiate new block proposals and vote on proposals. They are responsible for sorting, packaging, and verifying blocks in the blockchain network. After receiving a service request from a terminal, the consensus node will broadcast to other consensus nodes to maintain a complete service directory and participate in the subsequent PrePrepare, Prepare, and Commit stages to reach a consensus.

[0051] The ground station elects the master node of the consensus network in the service area through the polling mechanism in the RBFT algorithm. For example, a master node can also be specified by a preset method. The master node will generate system keys, global authentication parameters and root certificates. The root certificate contains the system's authentication public key, the master node signature and global authentication parameters. The master node will also create a genesis block, which records the satellite ID that can provide services.

[0052] In the RBFT algorithm, consensus nodes can be further divided into primary nodes and backup nodes. The primary node can be elected according to the consensus algorithm. For example, a primary node and a backup node can be preset. The primary node is responsible for making decisions and communicating them to other nodes; the backup node is used for fault tolerance to ensure that the system can still operate normally even if the primary node has errors or malicious behavior.

[0053] In the RBFT (Robust Byzantine Fault Tolerance) network, the election of the primary node is implemented through a polling mechanism. Specifically, the concept of "view" is introduced in the RBFT algorithm. Each election of the primary node is accompanied by a change in the view. The change of the view is monotonically increasing, starting from zero, and the view number increases each time the primary node is elected. The current view and the total number of nodes N jointly determine the ID of the primary node. The calculation formula is:

[0054] PrimaryId=(view+1)mod NPrimaryId=(view+1)modN

[0055] This means that the master node is dynamically elected through polling, and each node has the opportunity to become the master node. When a node becomes the master node, it will be responsible for sorting and packaging transactions from the client. If the master node fails or exhibits Byzantine behavior (such as stopping sending messages or sending error messages), the backup node (Replica) will detect these abnormal behaviors and trigger the view change (ViewChange) process to elect a new master node.

[0056] S102, using a satellite transit algorithm to predict the transit information of each low-orbit satellite, and setting the low-orbit satellite passing through any consensus network as a bookkeeping node of the consensus network according to the transit information.

[0057] In this embodiment, the low-orbit satellite is generally a satellite device with an orbital altitude of 500 to 2000 kilometers. A low-orbit satellite (LEO) is composed of a platform structure, a power system (solar panels and batteries), an attitude control system, a propulsion system, a communication system (transmitter, receiver, antenna), a payload (equipment for performing missions) and a thermal control system.

[0058] The master node ground station can predict the time when a serviceable satellite passes through the ground station based on the satellite transit algorithm. When a serviceable satellite passes, the master node ground station sends the consensus node configuration file to the satellite. The node configuration file specifies the satellite as the accounting node in the consensus network. After receiving the configuration file sent by the master node ground station, the satellite joins the consensus network according to the RBFT algorithm and becomes a new node in the blockchain. After joining the blockchain network, the new node will enter recovery mode and actively request the views, latest blocks and other information of all nodes in the existing consensus network to update its own storage status, and finally synchronize to the latest status of the entire system. When the satellite leaves the master node ground station, it leaves the entire consensus network according to the RBFT algorithm.

[0059] The accounting node saves and updates the ledger of each network slice. The ledger records the service directory data and application data in each slice network. These data are mainly used for satellite communication identity storage and satellite resource management services.

[0060] Satellite transit refers to the process of a satellite passing over a certain point on the Earth (usually a ground station or other observation point). This concept involves the orbital characteristics of the satellite and the change in its position relative to the Earth.

[0061] The process of nodes joining and leaving in the RBFT algorithm is as follows:

[0062] 1. Node joining process:

[0063] (1) The newly added node actively initiates a connection to the existing nodes by reading the configuration file information. After confirming that all nodes are connected successfully, it updates its own routing table and initiates recovery.

[0064] (2) After receiving the connection request from the new node, the existing node confirms that it agrees to the node joining, and then broadcasts the AddNode message to the entire network, indicating that it agrees to the new node joining the entire consensus network.

[0065] (3) When an existing node receives N (N is the total number of nodes in the existing blockchain consensus network) AddNode messages, it updates its own routing table and then begins to respond to the consensus message requests from the newly added nodes (before this, all consensus messages from the newly added nodes are not processed).

[0066] (4) After the newly added node completes recovery, it broadcasts a ReadyForN request to all existing nodes in the network.

[0067] (5) After receiving the ReadyForN request, the existing node recalculates the N,view and other information after the new node joins, and then encapsulates it and the PQC message into the AgreeUpdateN message and broadcasts it to the entire network.

[0068] (6) After the new node joins the consensus network, a new master node will be generated. After receiving Nf AgreeUpdateN messages, the master node will send an UpdateN message as the new master node.

[0069] (7) After receiving the UpdateN message, all nodes in the network confirm the correctness of the message and perform VCReset.

[0070] (8) After each node completes VCReset, the entire network broadcasts the FinishUpdate message.

[0071] (9) After receiving Nf FinishUpdate messages, the node processes subsequent requests and completes the process of adding new nodes.

[0072] 2. Node leaving process:

[0073] The dynamic deletion process of RBFT nodes is similar to the process of adding new nodes. The specific steps are as follows:

[0074] (1) First, the node to be deleted sends a request to all nodes in the alliance.

[0075] (2) After each node confirms its agreement, it will broadcast the agreement to other nodes in the alliance. When a node receives 2f+1 responses agreeing to join, it will establish a link with the new node.

[0076] (3) Subsequently, when the node to be deleted establishes a connection with Nf (N is the total number of blockchain alliance nodes) nodes, the active recovery algorithm can be executed to synchronize the latest status of blockchain alliance members.

[0077] (4) After completing the above steps, the node can safely leave the network.

[0078] The above steps describe how nodes dynamically join and leave the consensus network in the RBFT algorithm.

[0079] S103, obtaining a service request from a satellite communication terminal, forwarding the service request to a master node of the corresponding consensus network via a low-orbit satellite passing through the satellite communication terminal, verifying and prioritizing the service request according to the master node, and broadcasting and consensus verification to all nodes of the current consensus network if the verification is successful.

[0080] In this embodiment, the satellite communication terminal is a ground device set on the earth responsible for connecting satellites and sensors. It is a bridge between the satellite communication network and the ground network. Its main functions include signal conversion, protocol conversion and data processing. The terminal consists of a radio frequency subsystem and a baseband subsystem. The radio frequency subsystem includes an antenna, radio frequency components and intermediate frequency components, which are responsible for receiving and sending signals; the baseband subsystem includes a satellite modem, an access service network, a network routing and security system, etc., which are responsible for the management and control of data traffic.

[0081] Before the satellite communication terminal transmits data through the low-orbit communication network for the first time, it needs to pass the transaction verification of the consensus network to ensure the security of satellite communication terminal access and data transmission. The satellite communication terminal does not participate in the consensus process. The satellite communication terminal is preset with a serviceable satellite catalog when it leaves the factory, and the time when the serviceable satellite passes the ground station can be predicted based on the satellite transit algorithm. When the satellite communication terminal first accesses the low-orbit satellite communication network, it sends a service request to the satellite of the transiting satellite communication terminal. The service request contains the device identification number (device ID) and the service identification number (service ID).

[0082] After receiving the service request, the satellite (which has joined the sharded blockchain in this region) sends it to the master node in this region according to the node configuration file. The master node verifies and prioritizes the service request. If the verification is passed, the service request, service key pair and priority ranking are broadcast to all nodes of the consensus network according to the three-phase commit protocol (Pre-Prepare, Prepare, Commit) of the RBFT algorithm for consensus verification.

[0083] After receiving the consensus verification result, all nodes write the verification result into the blockchain. The verification result includes the device identification number, service identification number, service key pair and sorted service priority. The service key pair includes the service public key and service private key. After receiving the consensus verification result, the master node sends the service request response to the satellite of the transit satellite communication terminal, and the satellite sends the service request response to the satellite communication terminal. This service request response includes the request result and the service private key. If the request is passed, the satellite communication terminal can enter the communication transmission stage.

[0084] S104, after the consensus verification is passed, the communication data signed by the service private key sent by the satellite communication terminal is obtained in real time according to the low-orbit satellite of the transiting satellite communication terminal. After the service public key verification is performed on the communication data, it is forwarded to any ground station of the current consensus network, and then forwarded to another designated satellite communication terminal or data center through the ground station.

[0085] In this embodiment, after the satellite communication terminal enters the communication transmission stage, the satellite communication terminal sends the data signed by the service private key to the satellite of the transit satellite communication terminal. After receiving the data transmitted by the satellite communication terminal, the satellite of the transit satellite communication terminal verifies the signature of the satellite communication terminal with the device ID of the satellite communication terminal and the corresponding service public key according to the accounting record of this node, and caches the data in the forwarding queue if the verification is successful. When the transit satellite communication terminal satellite passes through the ground station in the transit communication network, it forwards the cached data to the ground station, and the ground station then sends the data to the designated data center or satellite communication terminal, thereby completing the data transmission.

[0086] In some embodiments, in the above step S102, the use of a satellite transit algorithm to predict the transit information of each low-orbit satellite specifically includes:

[0087] Acquire the real-time orbital position information of each low-orbit satellite, and calculate the position change trend of each low-orbit satellite in a future preset time period according to the real-time orbital position information;

[0088] Acquire ground station distribution data, and establish a corresponding relationship model between ground station locations and satellite coverage areas according to the ground station distribution data and the location change trend;

[0089] Based on the corresponding relationship model, the consensus network to which any low-orbit satellite belongs at the current moment is calculated, and the low-orbit satellite is marked as a serviceable satellite of the consensus network to which it currently belongs, thereby forming the transit information of the low-orbit satellite.

[0090] In this embodiment, the real-time orbital position information of each low-orbit satellite is obtained, and the position change trend of the satellite in the future preset time period is predicted by the orbital mechanics model. The distribution data of the ground station is obtained, including the latitude and longitude coordinates, altitude, antenna parameters and other information of the ground station. According to the position change trend of the satellite and the distribution data of the ground station, the link budget model is used to calculate the visible time window and link quality between the satellite and the ground station, and a corresponding relationship model between the ground station position and the satellite coverage area is established. Based on the corresponding relationship model, the ground station that each satellite can connect to at the current moment is determined, and the consensus network to which the satellite belongs is determined according to the network topology relationship between the ground stations. The satellite is marked as a serviceable satellite of the current consensus network, and the satellite number, the consensus network to which it belongs, the time to enter the coverage area, the time to leave the coverage area and other information are used to generate the transit information of the satellite. According to the transit information of the satellite, the communication scheduling between the ground station and the satellite is optimized. When the satellite enters the coverage area, the communication link is established in advance to improve the utilization rate of the communication time. Taking into account the satellite's position change, ground station distribution, link quality and other factors, the consensus network to which the satellite belongs is dynamically adjusted to ensure the global coverage and service continuity of the low-orbit satellite communication network.

[0091] For example, the satellite position can be accurately located through ground tracking stations or satellite-borne GPS receivers. For example, the position of a low-orbit communication satellite at a specific moment may be 115.3 degrees longitude, 39.9 degrees latitude, and 550 kilometers altitude. Based on the six elements of the Kepler orbit, the future trajectory of the satellite can be predicted. Assuming that the satellite orbit has an inclination of 53 degrees and a period of 95 minutes, it will rotate around the earth about 15 times in the next 24 hours, and the coverage area will change over time.

[0092] The ground station distribution data contains the geographical location and communication capabilities of each ground station. For example, the Beijing ground station is located at 40 degrees north latitude and 116 degrees east longitude, with Ku and Ka band antennas. Combined with satellite orbit prediction, a correspondence model between ground stations and satellite coverage areas can be established. This model takes into account factors such as the curvature of the earth and atmospheric refraction, and can accurately calculate the satellite visibility time window. For example, a satellite is visible above the Beijing ground station 4 times a day, each time for about 8 minutes. Based on the correspondence model, the consensus network to which each satellite belongs at any time can be determined. A consensus network refers to a group of satellites that can communicate and work together. For example, at a certain moment, five satellites in the same orbital plane may form a consensus network that can exchange data through intersatellite links. Marking a satellite as a serviceable satellite means that it can provide communication services to specific ground users. Transit information contains parameters such as the visible time, elevation angle, and azimuth angle of the satellite to the ground station. This information is crucial for planning communication tasks. For example, if a mobile user needs to transmit a large amount of data within a specific time period, the system can select the best satellite and time window to complete the task based on transit information. This dynamic management method can optimize the utilization of satellite network resources and improve communication efficiency and reliability. By adjusting satellite grouping and task allocation in real time, the system can adapt to changes in communication needs in different geographical locations and times. For example, during peak communication demand periods, the number of serviceable satellites in a certain area can be increased; in emergencies, the network topology can be quickly reconfigured to ensure smooth communication in key areas. In addition, this method also helps with load balancing and fault recovery in satellite networks. When a satellite fails, the system can quickly adjust the consensus network and transfer tasks to other available satellites to maintain service continuity. This not only improves the robustness of the system, but also extends the service life of the satellite and reduces operating costs.

[0093] In some embodiments, in the above step S103, the verifying and prioritizing the service request according to the master node specifically includes:

[0094] Acquire device characteristic information of the satellite communication terminal, and construct a terminal feature vector according to the device characteristic information, wherein the device characteristic information includes device type, communication capability, and service requirements;

[0095] According to the importance of each feature vector in the terminal feature vector, a weight is assigned to each feature vector to determine the priority score of each satellite communication terminal;

[0096] Extracting the digital signature information carried in the service request according to the master node, and verifying the digital signature information using the RSA verification algorithm;

[0097] If the digital signature information is verified, each service request is prioritized according to the priority score of the satellite communication terminal corresponding to each service request.

[0098] In this embodiment, the device characteristic information of the satellite communication terminal, including the device type, communication capability and service requirements, etc., is obtained to construct a multi-dimensional terminal feature vector. The principal component analysis method is used to reduce the dimension of the terminal feature vector, and the main feature components that best characterize the terminal characteristics are extracted. According to the variance contribution rate of each feature component, its importance weight is calculated to obtain a weighted terminal feature vector. The weighted terminal feature vector is grouped by a clustering algorithm, and terminals with similar characteristics are divided into the same category. For each terminal category, differentiated service strategies and resource allocation plans are formulated based on its business requirements and communication capabilities. In each terminal category, the similarity between terminals is calculated based on the Euclidean distance of the weighted feature vector to obtain the priority ranking of the terminals.

[0099] After receiving the service request from the satellite communication terminal, the master node extracts the digital signature information from the request, verifies the digital signature using the preset RSA public key, and determines whether the digital signature is legal and valid. If the digital signature verification is successful, the satellite communication terminal priority score table is obtained according to the satellite communication terminal identifier carried in the service request, and the priority score corresponding to the request is determined. The priority score of the current service request is compared with the priority scores of other existing service requests, and all service requests are prioritized in order from high to low according to the priority scores. For the sorted service request list, each request is processed from top to bottom. If the priority score of a request is lower than the preset threshold, it is judged as a low priority request, which is not processed temporarily, and the next request is processed. For the service request that needs to be processed, the master node calls the corresponding service module to process the request according to the business type and request parameters in the request, and obtains the service response result data. The master node digitally signs the service response result data, generates signature information, packages the signature information and the response result data together, and sends it to the requesting satellite communication terminal through the satellite communication link. After receiving the response data packet, the satellite communication terminal extracts the digital signature information and verifies it using the preset master node public key. If the signature verification passes, the response result data is submitted to the upper-level application for processing to complete the service request process.

[0100] Exemplarily, device types may include handheld terminals, vehicle-mounted terminals, or fixed stations, each of which has its own unique communication capabilities and service requirements. For example, a handheld terminal may require low-latency, low-power voice communication services, while a fixed station may require high-bandwidth data transmission capabilities. By analyzing these characteristics, a multi-dimensional feature vector can be constructed to accurately describe the attributes of each terminal. The weight distribution of the feature vector reflects the importance of different characteristics in the priority assessment. For example, in an emergency communication scenario, the terminal's anti-interference ability may be more important than the transmission rate.

[0101] Suppose there is a vector containing five features: device type, communication frequency band, data transmission rate, anti-interference ability, and battery life. Under normal circumstances, these features may be given similar weights. However, in special cases, such as disaster relief, anti-interference ability and battery life may be given higher weights to ensure the reliability and durability of communication. The calculation of the priority score takes into account both the feature vector and the weight. Suppose there are two terminals, one is a handheld device for daily communication, and the other is a vehicle-mounted device for emergency rescue. Although the handheld device may perform better in some aspects, such as a higher data transmission rate, the vehicle-mounted device may receive a higher priority score considering the special needs of emergency rescue. This dynamic priority evaluation mechanism ensures that resources are reasonably allocated to the users who need them most. Digital signature verification is a key step in ensuring communication security. As an asymmetric encryption algorithm, the RSA algorithm is widely used in digital signatures. In actual applications, the terminal device uses a private key to sign the service request, and the master node uses the corresponding public key to verify it. This not only confirms the authenticity of the request, but also prevents the request from being tampered with. For example, when a high-priority user sends a service request, digital signature verification can ensure that the request is indeed from an authorized user and not forged by a malicious third party. Prioritization of service requests is the last step in resource allocation. In actual operation, the system dynamically adjusts the service order based on the previously calculated priority scores and the current network resource conditions. For example, when the network load is light, even lower-priority requests may be processed quickly. However, when the network is congested, the system will prioritize high-priority requests to ensure that critical communication needs are met. This flexible scheduling strategy not only improves the efficiency of network resource utilization, but also responds quickly to the needs of important users in emergency situations. Through this series of steps, the satellite communication system can intelligently manage and allocate limited communication resources, while ensuring communication security, while maximizing the satisfaction of the diverse needs of different users. The advantage of this approach lies in its flexibility and adaptability, and the ability to make optimal decisions based on real-time conditions, thereby improving the efficiency and reliability of the entire satellite communication network.

[0102] In some embodiments, in the above step S104, after verifying the service public key of the communication data, the communication data is forwarded to any ground station of the current consensus network, specifically including:

[0103] After performing service public key verification on at least one of the communication data, determining an allocation strategy for each communication data according to a priority score of a satellite communication terminal corresponding to each communication data and a processing performance of each ground station in the current consensus network, wherein the allocation strategy includes a processing order of the communication data and a ground station to which the communication data is allocated;

[0104] The actual processing time of each communication data at the assigned ground station is obtained, and the allocation strategy of each communication data sent next time by at least one satellite communication terminal is dynamically optimized using a reinforcement learning algorithm according to the priority score and actual processing time of the satellite communication terminal corresponding to each communication data.

[0105] In this embodiment, communication data from multiple satellite communication terminals is received, the source of each communication data is authenticated, and the data signature is verified by a preset service public key to ensure the authenticity and integrity of the data source and prevent the data from being tampered with or forged. The priority score of the satellite communication terminal corresponding to each communication data is obtained. The priority score is determined by multiple dimensions such as the importance of the satellite terminal, the data type, and the business requirements. It is quantitatively calculated through a pre-established scoring system to obtain a priority score between 0 and 100. The processing performance parameters of each ground station node in the current consensus network are obtained, including computing power, storage capacity, network bandwidth, etc. The data processing upper limit and load of each ground station are determined based on these parameters to form a dynamic evaluation mechanism for the processing capacity of the ground station. According to the priority score of each communication data and the processing performance of the ground station, an intelligent scheduling algorithm, such as a weighted polling algorithm or a priority queue algorithm, is used to determine the processing order of each communication data. Data with high priority is processed first, and data with the same priority is scheduled according to the principle of first come first served. While determining the processing order, according to the processing capacity and load of the ground station, a load balancing algorithm, such as a consistent hashing algorithm or a minimum number of connections algorithm, is used to dynamically allocate each communication data to a ground station with a lower load and that can meet the processing requirements, so as to achieve balanced utilization of the ground station group and maximize processing efficiency. Generate a data allocation strategy, including the processing order of each communication data and the target ground station to which it is allocated, and send the allocation strategy to the corresponding ground station node. The ground station processes the communication data according to the allocation strategy and returns the results to the data allocation and dispatching center after processing. Monitor and manage the entire process of data processing, and grasp the processing progress and load of each ground station in real time through log analysis and performance monitoring. Dynamically adjust the data allocation strategy according to the actual situation. If a ground station fails or its processing capacity decreases, the data it is responsible for will be transferred to other ground stations in a timely manner to ensure the continuity and reliability of data processing.

[0106] The actual processing time of each communication data at the assigned ground station is obtained; the average processing time and variance of each communication data are calculated based on the obtained actual processing time; the priority score of the satellite communication terminal corresponding to each communication data is obtained; the average processing time, variance and priority score are used as the state space of the reinforcement learning algorithm; the allocation strategy of each communication data is used as the action space of the reinforcement learning algorithm; through the reinforcement learning algorithm, the optimal action, that is, the optimal allocation strategy, is selected according to the current state space; the optimized allocation strategy is applied to the satellite communication terminal, and the allocation strategy of each communication data sent next time is dynamically adjusted.

[0107] Exemplarily, by performing public key verification on communication data, the system can confirm the authenticity and integrity of the data and prevent malicious attacks and data tampering. For example, when a high-priority user sends an emergency communication request, the system uses the user's public key to verify the signature of the request to ensure that the request is indeed from an authorized user. After the verification is completed, the system will formulate a communication data allocation strategy based on the priority score of the satellite communication terminal and the processing performance of the ground station. The priority score may be based on multiple factors, such as user type, importance of communication content, etc. Suppose there are three communication requests: one from the military command center (priority score 95), one from the meteorological monitoring station (priority score 80), and one from an ordinary user (priority score 60). The system will prioritize the request from the military command center, followed by the meteorological monitoring station, and finally the ordinary user. The processing performance of the ground station is also an important factor in determining the allocation strategy. For example, there are three ground stations A, B, and C, and their processing capabilities are 100, 80, and 60 packets per second, respectively. The system will prioritize high-priority communication data to the ground station A with the strongest processing capability to ensure a quick response. The acquisition of actual processing time is crucial for system optimization. The system records the actual processing time of each communication data at the assigned ground station. For example, the actual processing time of the communication data of the military command center at ground station A is 0.5 seconds, while the expected time should be 0.3 seconds. This difference provides room for optimization for the system. The application of reinforcement learning algorithms enables the system to dynamically optimize the allocation strategy. By continuously learning the difference between the actual processing time and the expected time, as well as the system performance under different allocation strategies, the algorithm can gradually improve the decision-making process. For example, if a ground station is found to be particularly efficient in processing a specific type of communication data, the system will be more inclined to allocate similar data to this ground station in the future. This dynamic optimization mechanism can adapt to changes in the network environment. Suppose that at a certain time period, the processing capacity of ground station B is increased to 120 packets per second due to equipment upgrades. The reinforcement learning algorithm will quickly capture this change and make more use of the new capacity of ground station B in subsequent allocations. In this way, the system can not only ensure the timely processing of high-priority communications, but also maximize the utilization efficiency of overall network resources. This is of great significance for satellite communication systems to cope with complex and changing communication needs, especially in emergency situations or resource-constrained situations. At the same time, this intelligent resource allocation and optimization mechanism also lays the foundation for more complex satellite communication network management in the future.

[0108] In some embodiments, in the above steps S101 to S104, the method further includes:

[0109] Obtain the communication window time between each low-orbit satellite and the ground station of the current consensus network, and determine whether the communication window time meets the time requirements for identity authentication and key negotiation by comparing the communication window time with a preset communication window time threshold;

[0110] If the communication window time is greater than or equal to a preset communication window time threshold, cross-domain identity authentication is performed according to the respective identity information of the low-orbit satellite and the ground station;

[0111] Acquire communication link state information between the low-orbit satellite and the ground station, and according to the communication link state information, use a Kalman filter algorithm to recursively calculate a state estimate and an estimate error covariance matrix, filter the communication link state information, and obtain a smoothed communication link state estimate;

[0112] According to the communication link state estimation value, a hidden Markov model is used to define a state transition probability matrix and an observation probability matrix, and a forward algorithm is used to calculate the probability of the observation sequence, so as to predict the dynamic topology change trend between the low-orbit satellite and the ground station, and obtain the topology change probability within a preset time in the future;

[0113] According to the communication link state estimation value and the topology change probability, the Mamdani reasoning method is used to make a fuzzy decision to determine the best time for key negotiation between the low-orbit satellite and the ground station.

[0114] In this embodiment, the orbital parameters of the low-orbit satellite and the position coordinates of the ground station are obtained, and the communication window time between the low-orbit satellite and the ground station is calculated. The calculated communication window time is compared with the preset communication window time threshold to determine whether the communication window time meets the time requirements for identity authentication and key negotiation. If the communication window time is greater than or equal to the preset communication window time threshold, the respective identity information is obtained from the databases of the low-orbit satellite and the ground station. The identity information of the low-orbit satellite is sent to the ground station, and the identity information of the ground station is sent to the low-orbit satellite at the same time to realize the exchange of identity information. At the low-orbit satellite end, the preset cross-domain identity authentication algorithm is used to verify the received ground station identity information to determine the authenticity and legitimacy of the ground station identity. At the ground station end, the preset cross-domain identity authentication algorithm is also used to verify the received low-orbit satellite identity information to determine the authenticity and legitimacy of the low-orbit satellite identity. If the identity authentication of both the low-orbit satellite and the ground station is passed, it is determined that the two can conduct subsequent key negotiation and secure communication, otherwise the communication is terminated and the identity authentication failure information is recorded.

[0115] The communication link state information between the low-orbit satellite and the ground station is obtained, and the Kalman filter algorithm is used to filter the obtained communication link state information; according to the Kalman filter algorithm, the communication link state information is filtered by recursively calculating the state estimation value and the estimation error covariance matrix; if the estimation error of the communication link state information is greater than a preset threshold, it is judged that the smoothness of the current communication link state estimation value does not meet the requirement, and the Kalman filter processing is continued; if the estimation error of the communication link state information is less than or equal to the preset threshold, it is judged that the smoothness of the current communication link state estimation value meets the requirement, and the communication link state estimation value is determined to be a smoothed estimation result.

[0116] The estimated value of the communication link state is used as the observation sequence of the hidden Markov model. The hidden Markov model is used to define the state transition probability matrix to represent the transition probability of the topological connection state between the low-orbit satellite and the ground station. The observation probability matrix is ​​constructed to represent the probability of observing a specific link state estimate under a given topological state. The probability of the observation sequence under the hidden Markov model is calculated through the forward algorithm to obtain the probability distribution of the dynamic topological change trend. According to the probability distribution, the topological changes between the low-orbit satellite and the ground station in a specific time period in the future are predicted to obtain the probability of topological change.

[0117] According to the estimated value of the communication link state and the probability data of topology change, the Mamdani reasoning method is used to establish a fuzzy decision rule base for determining the optimal time for key negotiation. Through the fuzzy decision process of the Mamdani reasoning method, the communication link state and topology change factors are comprehensively considered to obtain the fuzzy evaluation result of the optimal time for key negotiation. The fuzzy evaluation result output by the Mamdani reasoning method is defuzzified and converted into the determined optimal time for key negotiation. If the estimated value of the communication link state and the probability of topology change change, the relevant data is re-acquired, iterated, and the determination result of the optimal time for key negotiation is dynamically adjusted. According to the determined optimal time for key negotiation, the key negotiation process between the low-orbit satellite and the ground station is controlled to start, and the secure distribution and update of the key is completed. During the key negotiation process, the communication link state and topology changes are continuously monitored. If an abnormal change is detected, the current key negotiation process is interrupted and the optimal time for key negotiation is returned to be re-determined.

[0118] Exemplarily, first, the system needs to obtain the communication window time between each low-orbit satellite and the ground station of the consensus network to which it belongs. This time window represents the time period in which the satellite and the ground station can communicate directly. For example, a low-orbit satellite may have a 15-minute communication window with the ground station during a specific period of time every day. The system will compare this time with the preset threshold. Assuming that the threshold is set to 10 minutes, the 15-minute window time meets the requirements for identity authentication and key negotiation. After meeting the time requirements, the system will perform cross-domain identity authentication. This process involves verifying the identity information of the low-orbit satellite and the ground station. For example, the satellite may use its unique identifier and digital signature, while the ground station may use its geographic location information and encryption certificate. This two-way authentication ensures the authenticity of both communicating parties and prevents potential spoofing attacks.

[0119] Next, the system obtains communication link status information, such as signal strength, delay time, etc. In order to process these data that may be noisy, the system uses the Kalman filter algorithm. Assume that the initial signal strength measurement is -70dBm, but there is a fluctuation of ±5dBm. The Kalman filter can smooth these fluctuations through recursive calculation and obtain a more accurate estimate, such as -68dBm. This filtering process improves the accuracy of subsequent decisions. Based on the processed link status information, the system uses a hidden Markov model to predict future topology changes. For example, the model may predict that in the next 30 minutes, the probability of the satellite disconnecting from the current ground station is 20%, and the probability of establishing a connection with a new ground station is 30%. This prediction helps the system make adaptive adjustments in advance to ensure the continuity of communication.

[0120] Finally, the system comprehensively considers the estimated link status and the probability of topology change, and uses the Mamdani fuzzy reasoning method to determine the best time for key negotiation. For example, if the current link status is good (signal strength is higher than -65dBm) and the probability of topology change in the short term is low (less than 10%), the system may determine that this is the best time to negotiate keys. This intelligent decision-making mechanism can maximize the success rate of secure communications in a dynamically changing network environment. Through this series of steps, the low-orbit satellite communication system can establish secure and reliable communication links in a complex and changing space environment. This not only improves the overall security of the system, but also optimizes resource utilization efficiency, laying the foundation for more complex space communication networks in the future.

[0121] Further, the obtaining of the communication link status information between the low-orbit satellite and the ground station specifically includes:

[0122] According to the topological structure and dynamic change characteristics of the low-orbit satellite communication network, the time window division method is adopted to divide the operation cycle of the low-orbit satellite communication network into multiple time windows;

[0123] For each time window, the distance and line of sight angle between the low-orbit satellite and the ground station are calculated based on the position information of the low-orbit satellite and the ground station;

[0124] If the distance between the low-orbit satellite and the ground station is less than the preset distance threshold and the line of sight angle meets the communication requirements, it is determined that there is a valid link between the low-orbit satellite and the ground station within the time window;

[0125] If it is determined that there is a valid link between the low-orbit satellite and the ground station within the time window, the relative motion speed and direction between the low-orbit satellite and the ground station within each time window are calculated based on the orbital parameters of the low-orbit satellite and the position coordinates of the ground station;

[0126] The duration and transmission delay of the effective link are determined according to the relative movement speed and the direction, so as to form the communication link status information between the low-orbit satellite and the ground station.

[0127] In this embodiment, the topological structure and dynamic change characteristic data of the low-orbit satellite communication network are obtained, and the operation cycle is divided into multiple time windows by using a time window division method according to the network operation cycle. For each time window, the position information data of all low-orbit satellites and ground stations in the time window is obtained. According to the acquired position information data, a distance calculation algorithm is used to calculate the distance between each low-orbit satellite and each ground station in each time window. According to the acquired position information data, a line of sight angle calculation algorithm is used to calculate the line of sight angle between each low-orbit satellite and each ground station in each time window. A preset distance threshold and a line of sight angle threshold are obtained, and the calculated distance is compared with the preset distance threshold, and the calculated line of sight angle is compared with the preset line of sight angle threshold. If the distance between the low-orbit satellite and the ground station is less than the preset distance threshold, and the line of sight angle meets the preset line of sight angle threshold, it is determined that there is a valid link between the low-orbit satellite and the ground station in the time window, otherwise it is determined that there is no valid link. According to the judgment result, it is determined whether there is a valid link between all low-orbit satellites and all ground stations in each time window, and the distribution of valid links in each time window of the low-orbit satellite communication network in the operation cycle is obtained.

[0128] If it is determined that there is a valid link, the relative motion speed and direction between the low-orbit satellite and the ground station in the time window are calculated using the relative kinematic model according to the orbital parameters of the low-orbit satellite and the position coordinates of the ground station. According to the calculated relative motion speed and direction, combined with the change in the distance between the low-orbit satellite and the ground station, the duration of the valid link in the time window is determined through the link prediction algorithm. According to the distance between the low-orbit satellite and the ground station and the propagation speed of the communication signal, the transmission delay between the low-orbit satellite and the ground station in the time window is calculated through the signal propagation model. The determined effective link duration and transmission delay are used as communication link status information, associated with the corresponding time window, and a communication link status table between the low-orbit satellite and the ground station is formed. The generated communication link status table is stored in the database, and is queried and updated as needed to provide data support for subsequent communication task scheduling and link optimization between the low-orbit satellite and the ground station.

[0129] Exemplarily, the satellite operation cycle is divided into multiple discrete time periods to facilitate accurate analysis and prediction of network status. For example, for a low-orbit satellite with an orbital period of 100 minutes, it can be divided into 10 time windows, each lasting 10 minutes. This division method enables the system to perform link status evaluation and resource allocation on a finer-grained time scale. In each time window, the system needs to calculate the distance and line of sight angle between the low-orbit satellite and the ground station. These two parameters directly determine the possibility of establishing a communication link. Assume that a low-orbit satellite is 800 kilometers away from the ground station in a certain time window, and the line of sight angle is 60 degrees. If the preset distance threshold is 1,000 kilometers and the line of sight angle is required to be greater than 45 degrees, then there is a valid link between the satellite and the ground station in this time window. This judgment mechanism ensures the quality of communication and avoids signal attenuation caused by excessive distance or obstructions. Once it is determined that there is a valid link, the next step is to calculate the relative speed and direction of movement between the satellite and the ground station. These parameters are crucial for evaluating the Doppler effect and predicting link duration. For example, if the satellite is calculated to be moving at a speed of 7.5 kilometers per second relative to the ground station and in a direction from northeast to southwest, the system can estimate the signal frequency offset and link availability time. This dynamic information helps the communication system make real-time adjustments, such as automatic frequency correction and data transmission rate optimization. Based on the relative motion parameters, the system can further determine the duration and transmission delay of the effective link. For example, for the satellite in the above example, if the length of its trajectory passing over the ground station is 3,000 kilometers, the duration of the effective link is about 400 seconds. At the same time, considering the propagation speed of electromagnetic waves and the influence of the atmosphere, the system may estimate the average transmission delay to be 5 milliseconds. This information constitutes the core content of the communication link status and provides an important basis for subsequent route selection and resource scheduling. Through this systematic analysis method, the low-orbit satellite communication network can achieve efficient and reliable communication in a complex and changing space environment. The division of time windows allows the system to manage resources predictably, the calculation of distance and angle ensures the availability of the link, and the relative motion analysis provides a dynamic perspective for link quality assessment. This comprehensive link status information not only improves the success rate of communications, but also lays the foundation for adaptive adjustment and optimization of the network, thereby maximizing the overall performance of the communication system under limited orbital resources and ground facilities.

[0130] Furthermore, the method further comprises:

[0131] With the optimization goal of maximizing network throughput and transmission efficiency, and with link capacity and node resources as constraints, a genetic algorithm is used to dynamically adjust the link allocation strategy of the effective link between the low-orbit satellite and the ground station.

[0132] Based on the adjusted link allocation strategy, the communication link status information between the low-orbit satellite and the ground station is re-determined.

[0133] In this embodiment, the link capacity and node resource information between the low-orbit satellite and the ground station are obtained as constraints of the genetic algorithm. According to the current link allocation strategy, the network throughput and transmission efficiency are evaluated and used as the fitness function of the genetic algorithm. Through the selection, crossover and mutation operations of the genetic algorithm, a new link allocation strategy population is generated, and the fitness value of each individual is calculated. It is judged whether the termination condition of the genetic algorithm is met. If it is met, the optimal link allocation strategy is output, otherwise it returns to continue iterative optimization. According to the optimal link allocation strategy obtained by the genetic algorithm, the communication link status information between the low-orbit satellite and the ground station is updated. Using the updated communication link status information, the data transmission path and resource allocation are dynamically adjusted to adapt to changes in the link allocation strategy. The changes in network throughput and transmission efficiency are continuously monitored. When the performance drops to a preset threshold, a new round of link allocation optimization process is triggered and returned for re-execution.

[0134] For example, the weighted sum of network throughput and transmission efficiency can be used as a fitness function. For example, assuming that there are 10 low-orbit satellites and 20 ground stations in a certain time window, a 10×20 matrix can be used to represent the link allocation strategy, in which each element represents the link bandwidth allocation between the satellite and the ground station. By calculating the total network throughput and average transmission delay under this allocation method, a comprehensive score can be obtained as the fitness value. In the iterative process of the genetic algorithm, it is necessary to design appropriate crossover and mutation operations. For the crossover operation, a single-point crossover or multi-point crossover method can be used. For example, two parent solutions are selected and exchanged in a row or column of the matrix to generate a new child solution. The mutation operation can randomly select certain elements in the matrix and make small adjustments to them under the premise of satisfying the constraints. These operations can gradually improve the quality of the solution while maintaining the diversity of the population. The handling of constraints is another key point. The link capacity constraint can be achieved by limiting the total bandwidth allocation of each satellite to not exceed its maximum capacity. For example, if the maximum bandwidth of a satellite is 1Gbps, the sum of the bandwidth allocated to all ground stations connected to it must not exceed this value. Node resource constraints may include satellite energy limitations, processing power, etc. These constraints can be converted into penalty terms and added to the fitness function, so as to automatically avoid infeasible solutions during the optimization process. Through multiple iterations, the genetic algorithm can gradually converge to a better link allocation strategy. This strategy not only takes into account the overall performance of the network, but also adapts to the dynamic characteristics of the low-orbit satellite network. For example, within a certain time window, the algorithm may allocate more bandwidth resources to a high-speed moving satellite to make full use of its short visible time. Based on the optimized link allocation strategy, the communication link status information needs to be re-evaluated and updated. This includes parameters such as the available bandwidth, expected transmission delay, and signal-to-noise ratio of each link. For example, if a link between a satellite-ground station pair is allocated a bandwidth of 200Mbps, the actual achievable data transmission rate and signal quality need to be recalculated based on factors such as the distance between them and the relative motion state. These updated link status information will provide a more accurate basis for subsequent routing decisions and resource scheduling, thereby further improving the overall performance of the network. This dynamic optimization method enables the low-orbit satellite communication network to better adapt to changes in the space environment and fluctuations in user needs, achieving efficient resource utilization and continuous optimization of network performance. By continuously adjusting the link allocation strategy and updating link status information, the system can maintain efficient and stable communication services in a complex and changing environment.

[0135] Reference Figure 2 An embodiment of the present invention provides a low-orbit satellite Internet of Things communication system 2 based on a dynamic blockchain, and the system 2 specifically includes:

[0136] The first communication module 201 is used to divide the low-orbit satellite communication network into multiple network partitions, use at least one ground station as a consensus node in each network partition to form a consensus network, and use the RBFT algorithm to select a master node from a plurality of consensus nodes in each consensus network;

[0137] The second communication module 202 is used to predict the transit information of each low-orbit satellite using a satellite transit algorithm, and set the low-orbit satellite passing through any consensus network as a bookkeeping node of the consensus network according to the transit information;

[0138] The third communication module 203 is used to obtain the service request of the satellite communication terminal, forward the service request to the master node of the corresponding consensus network through the low-orbit satellite passing the satellite communication terminal, verify and prioritize the service request according to the master node, and broadcast and verify the consensus to all nodes of the current consensus network if the verification is successful;

[0139] The fourth communication module 204 is used to obtain the communication data signed by the service private key sent by the satellite communication terminal in real time according to the low-orbit satellite of the transiting satellite communication terminal after the consensus verification is passed, and after verifying the communication data with the service public key, forward it to any ground station of the current consensus network, and forward it to another designated satellite communication terminal or data center through the ground station.

[0140] It is understandable that if Figure 1 The contents of the low-orbit satellite Internet of Things communication method embodiment based on dynamic blockchain shown in the embodiment are all applicable to the low-orbit satellite Internet of Things communication system embodiment based on dynamic blockchain. The functions specifically implemented by the low-orbit satellite Internet of Things communication system embodiment based on dynamic blockchain are the same as those in the embodiment shown in the embodiment. Figure 1 The embodiment of the low-orbit satellite Internet of Things communication method based on dynamic blockchain shown in FIG. 1 is the same as that shown in FIG. 1 , and the beneficial effects achieved are the same as those of FIG. Figure 1 The beneficial effects achieved by the embodiment of the low-orbit satellite Internet of Things communication method based on dynamic blockchain shown are also the same.

[0141] It should be noted that the information interaction, execution process and other contents between the above-mentioned systems are based on the same concept as the embodiment of the method of the present invention. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0142] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0143] Reference Figure 3 The embodiment of the present invention further provides a computer device 3, comprising: a memory 302 and a processor 301 and a computer program 303 stored in the memory 302. When the computer program 303 is executed on the processor 301, a low-orbit satellite Internet of Things communication method based on dynamic blockchain as described in any one of the above methods is implemented.

[0144] The computer device 3 may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The computer device 3 may include, but is not limited to, a processor 301 and a memory 302. Those skilled in the art will appreciate that Figure 3 It is only an example of computer device 3 and does not constitute a limitation on computer device 3. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components, for example, it may also include input and output devices, network access devices, etc.

[0145] The processor 301 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0146] In some embodiments, the memory 302 may be an internal storage unit of the computer device 3, such as a hard disk or memory of the computer device 3. In other embodiments, the memory 302 may also be an external storage device of the computer device 3, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the computer device 3. Further, the memory 302 may also include both an internal storage unit and an external storage device of the computer device 3. The memory 302 is used to store an operating system, an application program, a boot loader, data, and other programs, such as the program code of the computer program. The memory 302 may also be used to temporarily store data that has been output or is to be output.

[0147] An embodiment of the present invention also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the low-orbit satellite Internet of Things communication method based on dynamic blockchain as described in any of the above methods is implemented.

[0148] In this embodiment, if the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the above-mentioned various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium can at least include: any entity or device that can carry the computer program code to the camera / terminal device, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. For example, USB flash drive, mobile hard disk, disk or optical disk. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electric carrier signals and telecommunication signals.

[0149] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0150] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0151] In the embodiments disclosed in the present application, it should be understood that the disclosed devices / terminal equipment and methods can be implemented in other ways. For example, the device / terminal equipment embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0152] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

Claims

1. A low-orbit satellite Internet of Things communication method based on dynamic blockchain, characterized in that: The method specifically comprises: The low-orbit satellite communication network is divided into multiple network partitions. In each network partition, at least one ground station is used as a consensus node to form a consensus network. The RBFT algorithm is used to select the master node from several consensus nodes in each consensus network. A satellite transit algorithm is used to predict the transit information of each low-orbit satellite, and based on the transit information, a low-orbit satellite passing through any consensus network is set as a bookkeeping node of the consensus network; The method of using a satellite transit algorithm to predict the transit information of each low-orbit satellite specifically includes: Acquire the real-time orbital position information of each low-orbit satellite, and calculate the position change trend of each low-orbit satellite in a future preset time period according to the real-time orbital position information; Acquire ground station distribution data, and establish a corresponding relationship model between ground station locations and satellite coverage areas according to the ground station distribution data and the location change trend; Based on the corresponding relationship model, the consensus network to which any low-orbit satellite belongs at the current moment is calculated, and the low-orbit satellite is marked as a serviceable satellite of the consensus network to which it currently belongs, thereby forming transit information of the low-orbit satellite; Obtain the service request of the satellite communication terminal, forward the service request to the master node of the corresponding consensus network through the low-orbit satellite passing through the satellite communication terminal, verify and prioritize the service request according to the master node, and broadcast and verify the consensus to all nodes of the current consensus network if the verification is successful; After the consensus verification is passed, the communication data signed by the service private key sent by the satellite communication terminal is obtained in real time according to the low-orbit satellite of the transiting satellite communication terminal. After the service public key verification is performed on the communication data, it is forwarded to any ground station of the current consensus network, and then forwarded to another designated satellite communication terminal or data center through the ground station.

2. The method according to claim 1, characterized in that The verifying and prioritizing the service request according to the master node specifically includes: Acquire device characteristic information of the satellite communication terminal, and construct a terminal feature vector according to the device characteristic information, wherein the device characteristic information includes device type, communication capability, and service requirements; According to the importance of each feature vector in the terminal feature vector, a weight is assigned to each feature vector to determine the priority score of each satellite communication terminal; Extracting the digital signature information carried in the service request according to the master node, and verifying the digital signature information using the RSA verification algorithm; If the digital signature information is verified, each service request is prioritized according to the priority score of the satellite communication terminal corresponding to each service request.

3. The method according to claim 2, characterized in that After the service public key verification is performed on the communication data, it is forwarded to any ground station of the current consensus network, specifically including: After performing service public key verification on at least one of the communication data, determining an allocation strategy for each communication data according to a priority score of a satellite communication terminal corresponding to each communication data and a processing performance of each ground station in the current consensus network, wherein the allocation strategy includes a processing order of the communication data and a ground station to which the communication data is allocated; The actual processing time of each communication data at the assigned ground station is obtained, and the allocation strategy of each communication data sent next time by at least one satellite communication terminal is dynamically optimized using a reinforcement learning algorithm according to the priority score and actual processing time of the satellite communication terminal corresponding to each communication data.

4. The method according to any one of claims 1 to 3, characterized in that The method further comprises: Obtain the communication window time between each low-orbit satellite and the ground station of the current consensus network, and determine whether the communication window time meets the time requirements for identity authentication and key negotiation by comparing the communication window time with a preset communication window time threshold; If the communication window time is greater than or equal to a preset communication window time threshold, cross-domain identity authentication is performed according to the respective identity information of the low-orbit satellite and the ground station; Acquire communication link state information between the low-orbit satellite and the ground station, and according to the communication link state information, use a Kalman filter algorithm to recursively calculate a state estimate and an estimate error covariance matrix, filter the communication link state information, and obtain a smoothed communication link state estimate; According to the communication link state estimation value, a hidden Markov model is used to define a state transition probability matrix and an observation probability matrix, and a forward algorithm is used to calculate the probability of the observation sequence, so as to predict the dynamic topology change trend between the low-orbit satellite and the ground station, and obtain the topology change probability within a preset time in the future; According to the communication link state estimation value and the topology change probability, the Mamdani reasoning method is used to make a fuzzy decision to determine the best time for key negotiation between the low-orbit satellite and the ground station.

5. The method according to claim 4, characterized in that The obtaining of the communication link status information between the low-orbit satellite and the ground station specifically includes: According to the topological structure and dynamic change characteristics of the low-orbit satellite communication network, the time window division method is adopted to divide the operation cycle of the low-orbit satellite communication network into multiple time windows; For each time window, the distance and line of sight angle between the low-orbit satellite and the ground station are calculated based on the position information of the low-orbit satellite and the ground station; If the distance between the low-orbit satellite and the ground station is less than the preset distance threshold and the line of sight angle meets the communication requirements, it is determined that there is a valid link between the low-orbit satellite and the ground station within the time window; If it is determined that there is a valid link between the low-orbit satellite and the ground station within the time window, the relative motion speed and direction between the low-orbit satellite and the ground station within each time window are calculated based on the orbital parameters of the low-orbit satellite and the position coordinates of the ground station; The duration and transmission delay of the effective link are determined according to the relative movement speed and the direction, so as to form the communication link status information between the low-orbit satellite and the ground station.

6. The method according to claim 5, characterized in that The method further comprises: With the optimization goal of maximizing network throughput and transmission efficiency, and with link capacity and node resources as constraints, a genetic algorithm is used to dynamically adjust the link allocation strategy of the effective link between the low-orbit satellite and the ground station. Based on the adjusted link allocation strategy, the communication link status information between the low-orbit satellite and the ground station is re-determined.

7. A low-orbit satellite Internet of Things communication system based on dynamic blockchain, characterized in that: The system specifically comprises: The first communication module is used to divide the low-orbit satellite communication network into multiple network partitions, use at least one ground station as a consensus node in each network partition to form a consensus network, and use the RBFT algorithm to select a master node from a number of consensus nodes in each consensus network; The second communication module is used to predict the transit information of each low-orbit satellite using a satellite transit algorithm, and set the low-orbit satellite passing through any consensus network as a bookkeeping node of the consensus network according to the transit information; The method of using a satellite transit algorithm to predict the transit information of each low-orbit satellite specifically includes: Acquire the real-time orbital position information of each low-orbit satellite, and calculate the position change trend of each low-orbit satellite in a future preset time period according to the real-time orbital position information; Acquire ground station distribution data, and establish a corresponding relationship model between ground station locations and satellite coverage areas according to the ground station distribution data and the location change trend; Based on the corresponding relationship model, the consensus network to which any low-orbit satellite belongs at the current moment is calculated, and the low-orbit satellite is marked as a serviceable satellite of the consensus network to which it currently belongs, thereby forming transit information of the low-orbit satellite; The third communication module is used to obtain the service request of the satellite communication terminal, forward the service request to the master node of the corresponding consensus network through the low-orbit satellite passing the satellite communication terminal, verify and prioritize the service request according to the master node, and broadcast and verify the consensus to all nodes of the current consensus network if the verification is successful; The fourth communication module is used to obtain the communication data signed by the service private key sent by the satellite communication terminal in real time according to the low-orbit satellite of the transiting satellite communication terminal after the consensus verification is passed, and after verifying the service public key of the communication data, forward it to any ground station of the current consensus network, and forward it to another designated satellite communication terminal or data center through the ground station.

8. A computer device, characterized in that: include: A memory and a processor and a computer program stored in the memory, when the computer program is executed on the processor, implements the low-orbit satellite Internet of Things communication method based on dynamic blockchain as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed by a processor, the low-orbit satellite Internet of Things communication method based on dynamic blockchain as described in any one of claims 1 to 6 is implemented.

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