Data transmission method for differentiated service quality assurance of satellite network and related equipment

Abstract

The invention provides a satellite network-oriented differential service quality guarantee data transmission method and related equipment. The method comprises the following steps: acquiring data to be transmitted in a time slot, and a source node and a target node of the data to be transmitted; obtaining a candidate link from the source node to the target node and a link attribute of the candidate link based on an undirected time-space diagram of the satellite network; determining a link utility value of the candidate link about a service quality index based on the link attribute and the service type of the data to be transmitted; determining the candidate link corresponding to the maximum value of the link utility value as a target link; and transmitting the to-be-transmitted data based on the target link.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the field of satellite communication, and in particular to a data transmission method and device for differentiated quality of service guarantee in a satellite network, and a storage medium. BACKGROUND

[0002] Current research on satellite network quality of service (QoS) routing has formed multiple technical paths, but each method has limitations in adapting to the characteristics of satellite networks. Centralized routing can achieve fine resource allocation with global vision, but it faces the core pain point: the SDN architecture is limited by the single-point failure risk of the controller and the satellite-ground communication delay, making it difficult to adapt to the high dynamics of satellite networks, and the complex deployment increases the difficulty of implementation. The hierarchical architecture optimizes planning using the stability of high-level satellites, but when the topology changes significantly, the time-consuming cross-layer resource redistribution and route adjustment lead to temporary QoS failure of services. Distributed routing improves reliability through decentralization, but the complexity of mobile agent design, traffic prediction, and other aspects increases the implementation and maintenance costs of satellite nodes, and the consideration of QoS indicators is often one-sided. In addition, multi-path routing methods based on genetic algorithms, storage time aggregation graphs, and multi-agent deep reinforcement learning have optimized specific QoS dimensions (such as delay jitter and traffic maximization), but are limited by slow convergence, high path update overhead when the topology changes, complex training, and high computational resource requirements, making it difficult to meet the dual requirements of real-time performance and deployment feasibility of satellite networks. SUMMARY

[0003] Therefore, the purpose of the present disclosure is to provide a data transmission method, system, device, and storage medium for differentiated quality of service guarantee in a satellite network.

[0004] In a first aspect, the present disclosure provides a data transmission method for differentiated quality of service guarantee in a satellite network, comprising: obtaining to-be-transmitted data within a time slot, a source node, and a target node of the to-be-transmitted data; obtaining candidate links from the source node to the target node and link attributes of the candidate links based on an undirected space-time graph of the satellite network; determining link utility values of the candidate links with respect to quality of service indicators based on the link attributes and a service type of the to-be-transmitted data; determining a target link corresponding to a maximum value of the link utility values as the target link; transmitting the to-be-transmitted data based on the target link.

[0005] In a second aspect, the present disclosure provides a data transmission device for differentiated quality of service guarantee in a satellite network, comprising: The data acquisition module is configured to acquire data to be transmitted in a time slot, a source node and a target node of the data to be transmitted. The candidate link module is configured to obtain candidate links from the source node to the target node and link attributes of the candidate links based on a directed space-time graph of the satellite network. The utility calculation module is configured to determine a link utility value of the candidate links with respect to a quality of service indicator based on the link attributes and a service type of the data to be transmitted. The target link module is configured to determine the candidate link corresponding to a maximum value of the link utility values as a target link. The data transmission module is configured to transmit the data to be transmitted based on the target link.

[0006] In a third aspect, the present disclosure provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, wherein the processor implements the method of the first aspect when executing the program.

[0007] In a fourth aspect, the present disclosure provides a non-transitory computer-readable storage medium storing computer instructions for causing a computer to execute the method of the first aspect.

[0008] In a fifth aspect, the present disclosure provides a computer program product comprising computer program instructions for causing a computer to execute the method of the first aspect when the computer program instructions are executed on the computer.

[0009] As can be seen from the above, the present disclosure provides a data transmission method, system, device and storage medium for differentiated quality of service guarantee of a satellite network. The data to be transmitted in a time slot and its source and target nodes are acquired, candidate links from the source to the target and link attributes are obtained based on a directed space-time graph of a satellite network, link utility values of the candidate links are determined in combination with the link attributes and a data service type, and a candidate link with the maximum utility value is selected as a target link to transmit data. The target link that best meets the quality of service requirements can be accurately selected from a large number of candidate links according to different service types, differentiated data transmission in a satellite network is realized, and the quality of service of various services is guaranteed. The quality of service requirements of different services are distinguished from the source, and traffic management is used to ensure that data is transmitted along an optimal path that meets specific quality of service requirements, which includes comprehensive consideration of key indicators such as delay, bandwidth and reliability. The data packet forwarding mechanism based on source routing realizes efficient and accurate forwarding of data packets by fusing constellation labels and IP information, and realizes optimal performance guarantee for routing and forwarding of data streams of the same source with different quality of service. BRIEF DESCRIPTION OF DRAWINGS

[0010] In order to more clearly illustrate the technical solutions in the present disclosure or the related art, the drawings needed to be used in the embodiments or the related art description will be briefly introduced. Obviously, the drawings in the following description are only embodiments of the present disclosure, and other drawings can be obtained by those skilled in the art without any creative effort based on these drawings.

[0011] Figure 1 A schematic diagram of a data transmission architecture for differentiated quality of service guarantee of a satellite network according to an embodiment of the present disclosure.

[0012] Figure 2 A structural schematic diagram of an exemplary electronic device according to an embodiment of the present disclosure.

[0013] Figure 3 A schematic flowchart of a data transmission method for differentiated quality of service guarantee of a satellite network according to an embodiment of the present disclosure.

[0014] Figure 4 A schematic diagram of differentiated transmission of service flows under different service type identifications according to an embodiment of the present disclosure.

[0015] Figure 5 A schematic diagram of a constellation source routing and forwarding working principle according to an embodiment of the present disclosure.

[0016] Figure 6 A schematic diagram of a data transmission apparatus for differentiated quality of service guarantee of a satellite network according to an embodiment of the present disclosure.

[0017] Figure 7 A schematic diagram of a data transmission apparatus for differentiated quality of service guarantee of a satellite network according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0018] In order to make the purposes, technical solutions and advantages of the present disclosure clearer, the present disclosure will be further described in detail below with reference to specific embodiments and drawings.

[0019] It should be noted that, unless otherwise defined, technical terms or scientific terms used in the embodiments of the present disclosure shall be understood as their common meanings to those skilled in the art to which the embodiments of the present disclosure belong. The terms "first", "second", and similar terms used in the embodiments of the present disclosure do not denote any order, quantity, or importance, but are used to distinguish different components. The terms "include", "contain", and similar terms mean that the elements or objects before the terms encompass the elements or objects listed after the terms and their equivalents, and do not exclude other elements or objects. The terms "connect" or "connected" and similar terms are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. The terms "upper", "lower", "left", "right", and the like are only used to represent relative positional relationships, and when the absolute positions of the described objects change, the relative positional relationships can also change accordingly.

[0020] It can be understood that, before using the technical solutions disclosed in the embodiments of the present disclosure, the type, scope of use, and scenario of use of personal information involved in the present disclosure should be informed to the user and the authorization of the user should be obtained in a proper manner according to relevant laws and regulations.

[0021] For example, in response to receiving a user's active request, a prompt message is sent to the user to explicitly prompt the user that the operation requested to be performed will require obtaining and using the user's personal information. Thus, the user can voluntarily choose whether to provide personal information to the electronic device, application program, server, or storage medium, etc. software or hardware that performs the operation of the technical solutions of the present disclosure according to the prompt message.

[0022] It can be understood that the above notification and user authorization process is only illustrative and does not limit the implementation of the present disclosure, and other ways that meet the relevant laws and regulations can also be applied to the implementation of the present disclosure.

[0023] Figure 1 A schematic diagram of a data transmission architecture for differentiated quality of service guarantee of satellite network-oriented of the embodiments of the present disclosure is shown. Referring to Figure 1 The data transmission architecture 100 for differentiated quality of service guarantee of satellite network-oriented can include a server 110, a terminal 120, and a network 130 providing a communication link. The server 110 and the terminal 120 can be connected through the wired or wireless network 130. The server 110 can be a stand-alone physical server, a server cluster or a distributed system composed of multiple physical servers, or a cloud server providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, security services, CDN, and other basic cloud computing services.

[0024] The terminal 120 can be implemented in hardware or software. For example, when the terminal 120 is implemented in hardware, the terminal 120 can be various electronic devices with a display screen and supporting page display, including but not limited to a smart phone, a tablet computer, an electronic book reader, a laptop computer, a desktop computer, and the like. When the terminal 120 is implemented in software, the terminal 120 can be installed in the above-listed electronic devices; the terminal 120 can be implemented as a plurality of software or software modules (for example, software or software modules for providing a distributed service) or as a single software or software module, which is not specifically limited herein.

[0025] It should be noted that the data transmission method for differentiated quality of service guarantee of a satellite network provided by the embodiments of the present disclosure can be executed by the terminal 120 or the server 110. It should be understood that, Figure 1 The number of terminals, networks, and servers in the above embodiments is only illustrative and is not intended to limit the same. According to the implementation needs, there can be any number of terminals, networks, and servers.

[0026] Figure 2 A hardware structure schematic diagram of an exemplary electronic device 200 provided by the embodiments of the present disclosure is shown. As Figure 2 shown, the electronic device 200 can include a processor 202, a memory 204, a network module 206, a peripheral interface 208, and a bus 210. The processor 202, the memory 204, the network module 206, and the peripheral interface 208 are communicatively connected to each other inside the electronic device 200 through the bus 210.

[0027] The processor 202 can be a central processing unit (CPU), a neural network processor (NPU), a microcontroller unit (MCU), a programmable logic device, a digital signal processor (DSP), an application specific integrated circuit (ASIC), or one or more integrated circuits. The processor 202 can be used to perform functions related to the technologies described in the present disclosure. In some embodiments, the processor 202 can also include multiple processors integrated as a single logical component. For example, as Figure 2 shown, the processor 202 can include multiple processors 202a, 202b, and 202c.

[0028] The memory 204 can be configured to store data (for example, instructions, computer code, and the like). As Figure 2As shown, the data stored by the memory 204 can include program instructions (e.g., program instructions for implementing the data transmission method for differentiated quality of service guarantee of satellite network-oriented services of embodiments of the present disclosure) and data to be processed (e.g., the memory can store configuration files of other modules, etc.). The processor 202 can also access the program instructions and data stored by the memory 204, and execute the program instructions to operate on the data to be processed. The memory 204 can include volatile storage or non-volatile storage. In some embodiments, the memory 204 can include random access memory (RAM), read-only memory (ROM), optical disk, magnetic disk, hard disk, solid state disk (SSD), flash memory, memory stick, etc.

[0029] The network module 206 can be configured to provide communication with other external devices to the electronic device 200 via a network. The network can be any wired or wireless network capable of transmitting and receiving data. For example, the network can be a wired network, a local wireless network (e.g., Bluetooth, WiFi, near field communication (NFC), etc.), a cellular network, the Internet, or a combination thereof. It can be understood that the type of network is not limited to the specific examples described above. In some embodiments, the network module 206 can include any combination of any number of network interface controllers (NICs), radio frequency modules, transceivers, modems, routers, gateways, adapters, cellular network chips, etc.

[0030] The peripheral interface 208 can be configured to connect the electronic device 200 with one or more peripheral devices to enable information input and output. For example, the peripheral devices can include input devices such as keyboards, mice, touchpads, touchscreens, microphones, various sensors, etc., and output devices such as displays, speakers, vibrators, indicator lights, etc.

[0031] The bus 210 can be configured to transmit information between various components (e.g., the processor 202, the memory 204, the network module 206, and the peripheral interface 208) of the electronic device 200, such as internal buses (e.g., processor-memory buses), external buses (USB ports, PCI-E buses), etc.

[0032] It should be noted that although the architecture of the electronic device 200 described above only shows the processor 202, the memory 204, the network module 206, the peripheral interface 208, and the bus 210, in the specific implementation process, the architecture of the electronic device 200 can also include other components necessary for normal execution. In addition, those skilled in the art can understand that the architecture of the electronic device 200 described above can also only include components necessary for implementing the embodiments of the present disclosure, and does not necessarily include all the components shown in the figure.

[0033] In the related technology of global communication network, low-orbit satellite network becomes an important supplement to ground network due to its wide coverage, flexible deployment, strong anti-destruction and other advantages. However, it faces many challenges in practical application: 1. Strong network dynamics: the mobility of low-orbit satellite nodes leads to frequent changes in network topology, and the routing path needs to be adjusted frequently, which increases the computing overhead and affects real-time service transmission; 2. Resource limited: the processing and storage capacity of satellite nodes are limited, and traditional traffic scheduling strategies are difficult to adapt to dynamic load, which easily leads to the decline of service quality; 3. Diversified service demand: the development of multimedia services makes the types of services in the network more diversified, including real-time video (delay sensitive), file download (bandwidth sensitive), background application (best effort) and other types of services, and a single routing algorithm cannot meet the differentiated QoS requirements. For the Quality of Service (QoS) routing problem of Low Earth Orbit Satellite Network (LEO), the existing research has the following aspects: 1. Centralized routing method: the central node calculates the routing table and then distributes it to the satellite nodes. The central node makes fine adjustment of network resources from the global perspective to meet the QoS requirements of different services. Most of this kind of method adopts Software-Defined Networking (SDN) controller to collect global information of the network, so as to calculate the routing path. However, the SDN architecture itself has the risk of single-point failure of centralized controller, and the communication delay between controller and satellite node affects the timeliness and accuracy of routing decision, which limits the reliability in dynamic satellite network environment and affects the QoS guarantee. At the same time, the algorithm based on SDN needs to deploy complex controller in the network, which involves more device configuration and software management work, and the deployment is difficult.

[0034] 2. Centralized method based on hierarchical architecture of satellite network: the relatively stable characteristics and wider view of high-level nodes are used to make global routing planning to ensure the QoS requirements of different services. The Medium Earth Orbit (MEO) layer satellite nodes or Geosynchronous Orbit (GEO) layer satellite nodes play a leading role in routing decision, and the LEO layer satellite nodes report local information (such as link state, traffic load, etc.) to high-level nodes. The high-level nodes make global routing planning according to these information and distribute guidance information to low-level nodes. In fact, when dealing with large-scale topology changes, hierarchical architecture may need complex resource reallocation and routing adjustment between different levels, which may take a long time to complete, and the QoS of services may be affected during this period.

[0035] 3. In the distributed routing mechanism, each node in the network exchanges routing information to calculate its own routing decision. It does not rely on a central control node, avoiding the impact of central control node failure, and improving the reliability and robustness of the network. However, the existing distributed routing mechanism is relatively complex, involving the design of multiple mobile agents, traffic prediction algorithms, and multiple links of processing and calculation. It may be difficult to implement and maintain in satellite networks. Secondly, the existing method does not fully consider the QoS conditions.

[0036] 4. The multi-path QoS routing method based on genetic algorithm reduces the computational overhead and guarantees QoS in terms of delay jitter under bandwidth and end-to-end delay constraints. However, genetic algorithm itself has the problems of slow convergence speed and easy to fall into local optimal solution. In the environment of satellite network which requires high real-time performance, it may not be able to provide stable and optimal multi-path selection for services in time.

[0037] 5. The QoS multi-path routing scheme based on storage time aggregation graph finds multiple paths for each task that maximize traffic and have acceptable delivery delay to achieve QoS routing. However, when the network state changes, the overhead of updating the aggregation graph and recalculating the path may cause high delay, affecting the transmission efficiency of the service.

[0038] 6. The method based on multi-agent deep reinforcement learning uses hybrid knowledge to define network architecture, providing more complex multi-path routing strategies and QoS guarantees. However, the training process of the method based on multi-agent deep reinforcement learning is complex and requires high computing resources, which may cause deployment difficulties in actual satellite networks.

[0039] In summary, current research on QoS routing for LEO satellite networks has formed multiple technical paths, but each method has limitations in adapting to the characteristics of satellite networks. Centralized routing, although it can rely on global vision to achieve fine resource allocation, faces the core pain point: the SDN architecture is limited by the single-point failure risk of the controller and the satellite-ground communication delay, making it difficult to adapt to the high dynamics of satellite networks, and the complex deployment increases the difficulty of implementation. The hierarchical architecture, although it optimizes planning using the stability of high-level satellites, causes long resource reallocation and routing adjustment times across layers when the topology changes, leading to temporary QoS failure of services. Distributed routing, although it improves reliability through decentralization, increases the implementation and maintenance costs of satellite nodes due to the complexity of mobile agent design and traffic prediction, and the consideration of QoS indicators is often one-sided. In addition, multi-path routing methods based on genetic algorithms, storage time aggregation graphs, and multi-agent deep reinforcement learning, although they have optimizations in specific QoS dimensions (such as delay jitter and traffic maximization), are limited by slow convergence, high path update overhead when the topology changes, complex training, and large computational resource requirements, making it difficult to meet the dual requirements of real-time performance and deployment feasibility for LEO satellite networks. Therefore, there is an urgent need for an efficient routing technology that can balance the characteristics of low-orbit satellite networks and differentiated QoS requirements.

[0040] In view of this, the present disclosure proposes a satellite network dynamic source routing forwarding technology for differentiated QoS guarantee, which realizes efficient forwarding of different QoS requirement services in low-orbit satellite networks through traffic classification and management, path selection based on QoS preference value, source routing label encapsulation and forwarding mechanism, and the advantages of Segment Routing (SR) technology. This technology can adapt to the dynamic changes in satellite network topology and the limited resources, providing customized routing strategies for delay-sensitive, bandwidth-sensitive, and best-effort services, and improving network resource utilization and service transmission reliability.

[0041] Referring to Figure 3 , Figure 3 A schematic flowchart of a data transmission method for differentiated QoS guarantee in a satellite network according to an embodiment of the present disclosure is shown. The data transmission method for differentiated QoS guarantee in a satellite network according to an embodiment of the present disclosure can be deployed on a server side. Figure 3 In the data transmission method for differentiated QoS guarantee in a satellite network, the method 300 can further include the following steps.

[0042] In step S310, the data to be transmitted within a time slot, the source node and the target node of the data to be transmitted are obtained.

[0043] In a communication system, in order to realize the reasonable sharing and orderly utilization of communication resources by multiple users or multiple services, the time axis is divided into a plurality of continuous small time periods, each of which can be referred to as a time slot. Different time slots can be allocated to different data transmission tasks to avoid conflicts in data transmission and ensure the orderliness of communication. For example, in a time division multiple access (TDMA) communication mode, multiple users occupy the channel in turn according to a predetermined time slot order for data transmission. The data to be transmitted can refer to the information content that the source node is ready to send to the target node at the current time. These data can be of various types, such as text, image, video, audio, etc., which carry different service requirements, such as video stream and audio stream data in video calls, document data in file transmission, etc. The source node can be the starting point of data transmission, i.e. the device or node that generates or initially holds the data to be transmitted and is ready to send it out. In a satellite network, the source node can be a ground station, a user terminal (such as a mobile phone, a satellite phone, etc.) or a satellite itself (when data is exchanged between satellites). The target node can be the destination of data transmission, i.e. the device or node that receives the data to be transmitted. Similarly in a satellite network, the target node can be a ground station, a user terminal or another satellite.

[0044] Specifically, in the pre-divided time period (i.e. time slot), the data to be transmitted is obtained. At the same time, the starting position of the data, i.e. the source node, and the position where the data finally arrives, i.e. the target node, can be determined. This provides key information for subsequent selection of appropriate transmission paths. For example, in a complex satellite communication scenario, there can be simultaneous data transmission requirements between multiple ground stations and satellites. By determining the data to be transmitted in the time slot and its source node and target node, the specific situation of each data transmission task can be clearly defined. By accurately obtaining the data to be transmitted in the time slot, the source node and the target node, accurate input can be provided for subsequent link selection operations based on the undirected space-time graph of the satellite network. This makes the data transmission process more orderly and efficient, avoiding transmission chaos and resource waste caused by unclear information. For example, conflicts in time and space between different data transmission tasks can be avoided, ensuring that each data can be accurately transmitted from the source node to the target node through the optimal path in the appropriate time slot, thereby improving the data transmission efficiency and reliability of the satellite network and ensuring the normal operation of various services in the satellite network.

[0045] In step S320, based on the undirected space-time graph of the satellite network, candidate links from the source node to the target node and link attributes of the candidate links are obtained.

[0046] In this context, a satellite network refers to a complex network system comprised of multiple satellites connected to ground stations, user terminals, and other entities via wireless communication links. These satellites are distributed across different orbits, enabling data transmission and interaction between themselves and with ground facilities to achieve various functions such as global communication, navigation, and remote sensing. An undirected spatiotemporal graph is a graph that dynamically describes the topology and link status of a satellite network at different times, with edges that are not directional. In this graph, nodes can represent entities such as satellites, ground stations, or user terminals, and edges represent communication links between these entities. These links are not directional; that is, if there is a link connecting satellite A and satellite B, data can be transmitted from A to B or vice versa. A candidate link refers to a communication link among all possible transmission paths from the source node to the target node that meets certain basic conditions (such as the link being currently available or the signal strength reaching a certain threshold). Link attributes refer to a series of parameters used to describe the characteristics and performance of the link. Link attributes can include link bandwidth (representing the amount of data that can be transmitted per unit time), transmission latency (the time required for data to be transmitted from one end of the link to the other), bit error rate (the proportion of erroneous bits during data transmission to the total number of bits), link reliability (the probability that the link will complete its intended function within a specified time and under specified conditions), and packet loss rate (the proportion of lost data packets during data transmission to the total number of data packets; a high packet loss rate will affect the integrity and accuracy of data, and has a significant impact on services such as file transfer).

[0047] This method utilizes an undirected spatiotemporal graph of a satellite network to obtain candidate links and their attributes from the source node to the target node. First, it leverages the satellite network topology and temporal dynamics information contained within the undirected spatiotemporal graph. Then, using specific algorithms (such as breadth-first search, depth-first search, or more complex graph search algorithms), and considering the impact of time on link status, it explores all possible paths to the target node from the source node, selecting links that meet basic communication conditions as candidate links. Simultaneously, for each candidate link, its various attributes, such as bandwidth and latency, are calculated or obtained based on the link-related information recorded in the undirected spatiotemporal graph. For example, in a low-Earth orbit satellite network where satellites are constantly moving, the undirected spatiotemporal graph reveals which other satellites can act as relays between the source and target satellites at a specific moment, forming candidate links. Furthermore, it allows for the calculation of attributes such as transmission latency and packet loss rate for these candidate links based on information such as the distance between satellites and signal power.

[0048] This approach enables comprehensive and accurate acquisition of candidate links and their attributes from the source node to the target node. Comprehensiveness is reflected in its consideration of the spatial topology and dynamic temporal changes of the satellite network, ensuring no potentially viable transmission paths are overlooked and accurately reflecting the performance of each link. This provides a rich and reliable information foundation for subsequent data transmission decisions. For example, when selecting data transmission links, the most suitable link can be chosen from the candidate links based on different service requirements (e.g., selecting links with low transmission latency for services with high real-time requirements, and selecting links with high bandwidth for services with large data volumes). This improves the data transmission efficiency and quality of the satellite network, ensuring the stable operation of various services within the satellite network.

[0049] In some embodiments, method 300 further includes: By slicing the satellite orbital periods according to time, an undirected spatiotemporal graph of the satellite network is constructed. Among them, time slot sequence , For the i-th time slot; The set of nodes in the satellite network; This is the set of candidate links between the source node S and the target node D. P represents time slot The set of link attributes between node i and node j, including latency, bandwidth, inter-satellite distance, and packet loss rate; for The set of data to be transmitted within a time slot.

[0050] This involves meticulously slicing the satellite's orbital period according to the time dimension, dividing the entire period into a series of continuous time slots. Based on these time slots, an undirected spatiotemporal graph of the satellite network can be constructed. G ={ T , V , E , P , B The set of nodes in the graph. V It covers all nodes in the satellite network; a set of candidate links. E This includes the source node in each time slot. S ( S ∈ V ) to target node D ( D ∈ V All links between () that meet the basic communication conditions; for each time slot, the set of link attributes. P Detailed records of any node within this time slot i To the node j Key information such as latency, bandwidth, inter-satellite distance, and packet loss rate of the inter-satellite links; and the set of data to be transmitted within the time slot.B This clarifies the data to be transmitted in the corresponding time slot. Through the undirected spatiotemporal diagram of the satellite network, the topology and link status of the satellite network at different times are comprehensively and dynamically depicted. On the one hand, it can accurately capture the changing characteristics of the satellite network over time. Because satellites are constantly moving in orbit, their relative positions and communication link status are constantly changing. By time slicing and recording detailed information for each time slot, these dynamic changes can be reflected in real time, providing an accurate basis for subsequent data transmission decisions. On the other hand, it comprehensively records the set of link attributes. P and the set of data to be transmitted B This allows for the comprehensive consideration of multiple factors when selecting links and allocating resources, such as the latency and bandwidth requirements of services, combined with the actual attributes of the links, to select the optimal transmission path. This effectively improves the data transmission efficiency of the satellite network, ensures the service quality of various services, and enhances the overall performance and reliability of the satellite network.

[0051] Specifically, the satellite's orbital period is sliced ​​according to time, and then the network is modeled as an undirected spatiotemporal graph. . It is a time series vector, where the length of each time slot is... express. This represents the set of all nodes in a satellite network topology. Inter-satellite links use sets. Indicate. Assume. and These represent the source node and the destination node, respectively. The QoS metric parameters for each link in the current time slice can be obtained dynamically and stored in the link attributes. Within the set. For any link Define its time slot The following latency ,bandwidth Interstellar distance Packet loss rate Attributes such as. Any path from the source node. to the destination node path The delay is the sum of the propagation delay and transmission delay of all links on the path: Any path from the source node to the destination node path The bandwidth is the remaining bandwidth of all links on the path. The minimum value, the remaining bandwidth of the link is expressed as the total bandwidth of the link minus the used bandwidth: , Any path from the source node to the destination node path Packet loss rate: ,in For link The packet loss rate. (Set) for A collection of traffic generated within a time slot, each traffic item containing traffic type, source and destination address attributes.

[0052] In step S330, based on the link attributes and the service type of the data to be transmitted, the link utility value of the candidate link with respect to the quality of service index is determined.

[0053] Different data transmission needs correspond to different business types. Common examples include real-time services (such as voice calls, video conferencing, and online games, which have extremely high real-time requirements and need to transmit data to the destination in a very short time to ensure business continuity and smoothness), non-real-time services (such as file downloads and email sending, which have relatively lower real-time requirements and focus more on data integrity and accuracy), and large-volume data services (such as high-definition video streaming and large-scale data backup, which require large bandwidth and stable transmission channels to support the rapid transmission of large amounts of data). Service quality indicators (SMIs) are a series of standards for measuring the quality of data transmission services. Common SMIs include latency, bandwidth, packet loss rate, reliability (the probability that a link completes its intended function within a specified time and under specified conditions), and availability (the probability that a link can function normally when needed). Different business types have different requirements for SMIs. For example, real-time services focus more on latency and packet loss rate, while large-volume data services prioritize bandwidth and reliability. Link utility value can be a comprehensive indicator that measures the degree to which a candidate link meets the service quality requirements for a specific business. It is obtained through comprehensive analysis and calculation of link attributes and the service quality indicators required by the type of data service to be transmitted. The higher the link utility value, the better the candidate link performs in meeting the service quality requirements of the current service, and the more suitable it is for transmitting the data of that service.

[0054] To determine the link utility value of candidate links in terms of service quality indicators (SMIs) based on link attributes and the service type of the data to be transmitted, it is first necessary to clarify the service type of the data to be transmitted, and then determine the specific requirements of this service for various SMIs (such as latency, bandwidth, packet loss rate, etc.). Then, for each candidate link, its corresponding link attribute values ​​(such as actual transmission latency, available bandwidth, packet loss rate, etc.) are obtained. Next, a specific algorithm or model is used (e.g., a weighted scoring method, which assigns different weights to each SMI based on its importance to the service, and calculates and combines the link attribute values ​​with the weights; or a fuzzy comprehensive evaluation method, which considers the fuzziness of the indicators for a more comprehensive assessment) to match and calculate the link attributes with the service quality indicators required by the service, ultimately yielding the link utility value for each candidate link. For example, for real-time video call services, latency and packet loss rate are key indicators. When calculating the link utility value, the latency and packet loss rate attributes of candidate links are given priority; the shorter the latency and the lower the packet loss rate, the higher the link utility value is likely to be.

[0055] This approach allows for precise evaluation of each candidate link's performance in meeting quality of service (QoS) requirements, based on the characteristics and needs of different services. By calculating link utility values, the merits of each candidate link can be intuitively compared, providing a scientific basis for selecting the optimal transmission link. In practical applications, this avoids blindly selecting links, improves data transmission efficiency and reliability, and ensures that different services can obtain QoS commensurate with their needs within the satellite network. For example, for online gaming services with extremely high real-time requirements, this solution allows for the selection of links with high utility values, effectively reducing lag and latency during gameplay and enhancing the player's gaming experience. For large-scale data backup services with large data volumes, high-bandwidth, high-reliability links can be selected to ensure fast and complete data transmission, improving the efficiency and security of data backup.

[0056] In some embodiments, determining the link utility value of the candidate link with respect to the quality of service metric based on the link attributes and the service type of the data to be transmitted includes: Based on the link attributes, determine the utility function of the candidate link with respect to the service quality index; The utility weight of the utility function is determined based on the service type of the data to be transmitted; The link utility value is obtained by weighting the utility function and the utility weight.

[0057] First, a utility function for service quality indicators is constructed based on link attributes. This function converts various link attributes (such as latency, bandwidth, and packet loss rate) into quantifiable values ​​that affect service quality, accurately reflecting the link's potential performance in terms of service quality. Next, considering the significant differences in service quality requirements among different service types, utility weights are assigned to the utility function based on the service type of the data to be transmitted. For example, real-time voice services are sensitive to latency, so latency-related utility functions are given higher weights. Finally, the link utility value is obtained by calculating the weighted sum of the utility function and utility weights. This value comprehensively considers both the link's own attributes and service requirements, providing a comprehensive assessment of the candidate link's service quality satisfaction for a specific service.

[0058] On the one hand, it can accurately quantify the service quality performance of candidate links under different business scenarios, avoiding the limitations of selecting links based on a single factor or subjective judgment. On the other hand, by reflecting the differentiated needs of different business types through utility weights, it makes link selection more aligned with actual business requirements, improving the relevance and effectiveness of data transmission. For example, when selecting links for real-time video transmission services in satellite networks, it can prioritize links that perform well in terms of bandwidth and latency and have matching weights, thereby effectively reducing video stuttering and latency, improving user experience, and ensuring the stable and efficient operation of various services in satellite networks.

[0059] In some embodiments, the quality of service metrics include latency, remaining bandwidth, and packet loss rate; The utility function of the candidate link with respect to the service quality metric is determined based on the link attributes, including: Based on the link delay and adjustment coefficient in the link attributes, a utility function for the delay is obtained; wherein, the utility function for the delay... , For adjustment coefficients, The link delay is mentioned above. Based on the remaining bandwidth and maximum bandwidth of the link in the link attributes, a utility function for the remaining bandwidth is obtained; wherein, the utility function for the remaining bandwidth... , This is the maximum bandwidth of the link. The remaining bandwidth of the link; Based on the link packet loss rate and attenuation coefficient in the link attributes, a utility function for the packet loss rate is obtained; wherein, the utility function for the packet loss rate... , is the attenuation coefficient. The packet loss rate of the link.

[0060] Specifically, utility functions can be constructed for latency, remaining bandwidth, and packet loss rate, which are key service quality metrics. For latency, a utility function is constructed using an inverse proportional function based on link latency and an adjustment coefficient. Higher latency results in lower utility values, and the rate of decrease is influenced by the adjustment coefficient. For remaining bandwidth, the utility function is determined by the ratio of remaining bandwidth to the maximum bandwidth. When remaining bandwidth exceeds the maximum bandwidth, the value is 1, reflecting the contribution of remaining bandwidth to service quality. For packet loss rate, a utility function is constructed using the link packet loss rate and attenuation coefficient, employing an exponential function. Higher packet loss rates result in lower utility values, and the degree of attenuation is determined by the attenuation coefficient. These three utility functions quantify the performance of a link across different service quality metrics. This allows for a scientific and detailed evaluation of the utility of candidate links across these three key service quality metrics: latency, remaining bandwidth, and packet loss rate. The latency utility function can intuitively reflect the real-time performance of link transmission, accurately selecting high-quality links with low latency for services with high real-time requirements. The remaining bandwidth utility function clearly reflects the transmission capacity of the link, ensuring sufficient bandwidth support for large data volume services. The packet loss rate utility function can effectively measure the reliability of link transmission, ensuring complete data transmission. Combining these three utility functions, the service quality of candidate links can be comprehensively and accurately evaluated, providing a reliable basis for selecting the most suitable link for business needs and improving the efficiency and stability of satellite network data transmission.

[0061] Specifically, to eliminate the dimensional differences between different QoS indicators, a utility function is used to map the original indicator values ​​to the [0,1] interval, achieving quantization unification. Latency (lower is better): a reverse mapping function is used. , The adjustment coefficient is used so that the mapping value approaches 0 when the delay is close to the threshold; the remaining bandwidth (the larger the better): a forward mapping function is used. , Maximum link bandwidth; Packet loss rate (lower is better): using an exponential decay function. , This is used as an attenuation coefficient to enhance the advantage of low packet loss rate. After normalizing the original indicators, indicator weights are assigned to different service types (e.g., Class A has the highest latency weight, and Class B has the highest bandwidth weight).

[0062] The link utility value is calculated by weighted summation, using the following formula: .

[0063] in, , , These are the weighting coefficients. , , This is a utility function. A higher weight indicates a higher degree of match between the path and the QoS requirements of the current service.

[0064] In some embodiments, the link delay includes the sum of the link propagation delay and the transmission delay on the candidate link; The remaining bandwidth of the link includes the minimum remaining bandwidth of the sub-links on the candidate link, and the remaining bandwidth of the sub-links includes the total bandwidth of the sub-links minus the used bandwidth. The link packet loss rate includes: ,in, For link packet loss rate, These are candidate links from source node S to target node D. Sub-links between node i and node j in the candidate links The packet loss rate.

[0065] Link latency comprehensively considers the sum of propagation latency and transmission latency on the candidate link, fully reflecting the time consumed by data transmission on that link. Remaining link bandwidth is the minimum remaining bandwidth of each sub-link on the candidate link, and the remaining bandwidth of a sub-link is obtained by subtracting the used bandwidth from the total bandwidth of the sub-links. This ensures the link has sufficient transmission capacity and avoids affecting overall transmission due to insufficient bandwidth in some sub-links. Link packet loss rate is obtained by calculating the complement of the product of the packet loss rates of all sub-links in the candidate link from the source node to the target node, accurately reflecting the probability of data loss during the entire link transmission process. This allows for precise measurement of the key performance indicators of the candidate links. Accurate link latency calculation helps select low-latency links for services with high real-time requirements (such as video conferencing and online games), ensuring smooth service operation. A reasonable method for determining remaining link bandwidth can avoid impacting the transmission efficiency of large-volume services due to local bandwidth bottlenecks, ensuring stable and fast data transmission. Accurate link packet loss rate calculation provides a reliable basis for services with strict data integrity requirements (such as file transfer and financial transactions), allowing for the selection of links with low packet loss rates, reducing the risk of data retransmission and loss, and thus comprehensively improving the service quality and transmission reliability of different services in the satellite network.

[0066] In some embodiments, the service type includes latency-sensitive services, bandwidth-sensitive services, or best-effort services; The utility weight of the utility function is determined based on the service type of the data to be transmitted, including: For latency-sensitive services, the utility weight of the link latency > the utility weight of the link packet loss rate > the utility weight of the remaining bandwidth of the link; For bandwidth-sensitive services, the utility weight of the remaining bandwidth of the link > the utility weight of the link latency > the utility weight of the link packet loss rate; For best-effort services, the utility weights of the remaining link bandwidth, the link delay, and the link packet loss rate are the same.

[0067] Among them, the scheme assigns utility weights to the utility functions corresponding to link delay, remaining bandwidth, and packet loss rate according to the characteristics of different service types (delay-sensitive, bandwidth-sensitive, best-effort). For delay-sensitive services, the utility weight of link delay is set to the highest to highlight their strict requirements for real-time performance. For bandwidth-sensitive services, the utility weight of the remaining link bandwidth is set to the highest to meet the dependence on bandwidth for large-data-volume transmission. For best-effort services, the requirements for various indicators are relatively balanced, so the three utility weights are set to be the same. This scheme can accurately meet different service requirements, ensure that when selecting a link, the most critical quality-of-service indicators of the service are prioritized, effectively improve the adaptability and efficiency of satellite network data transmission, and ensure the stable and efficient operation of various services.

[0068] Specifically, satellite network services are divided into three categories, each with different characteristics and QoS requirements, so there are also differences in routing strategies. For different service types, the path that best meets the QoS requirements needs to be selected from numerous paths. For example, for a delay-sensitive service request, a low-delay link will be preferentially considered in routing selection to ensure the smooth progress of the service and minimize the impact of delay on the user experience. Similarly, for a bandwidth-sensitive service, the path with a large bandwidth and capable of stably providing a high data transmission rate is the focus when selecting a route. For best-effort services, there are no strict requirements for delay and bandwidth, and the remaining resources in the network are used for data transmission without affecting high-priority services.

[0069] Traffic steering is implemented based on SR Policy. SR Policy is identified by a triple <Headend (source node), Color (service type), Endpoint (destination node)>. The Color attribute is used to associate the policy with the intention. Different quality-of-service requirements, such as low delay and high bandwidth, can be represented through the Color attribute. This traffic classification and management mechanism maps traffic flows with different Colors to preset paths to achieve differential forwarding, as Figure 4 [[ID=:12]]shown.

[0070] For three typical types of services in satellite networks (latency-sensitive, bandwidth-sensitive, and best-effort), the priorities of core QoS indicators are clearly defined: For latency-sensitive services (such as real-time interaction): prioritize low latency, with secondary focus on packet loss rate; for bandwidth-sensitive services (such as large file transfers): prioritize high remaining bandwidth, with secondary focus on latency; for best-effort services: balance latency, bandwidth, and packet loss rate, with resource utilization as the core. For each candidate path, latency, remaining bandwidth, and packet loss rate are collected as core indicators.

[0071] For different types of services, a utility function is determined for the core QoS metrics (latency, remaining bandwidth, packet loss rate) to normalize the original QoS metric values ​​of different dimensions and ranges to the [0,1] interval: Delay uses a reverse mapping function , The smaller the time delay, the higher the mapping value.

[0072] The remaining bandwidth uses a forward mapping function. , This represents the maximum bandwidth of the link; the larger the remaining bandwidth, the higher the mapping value.

[0073] Packet loss rate uses an exponential decay function , (where is the attenuation coefficient). The lower the packet loss rate, the higher the mapping value.

[0074] After normalizing the original metrics, weights are assigned to different business types, and the link utility value is calculated by weighted summation: ,in, , , These are the weighting coefficients. , , This is a utility function. A higher weight indicates a higher degree of match between the path and the QoS requirements of the current service.

[0075] In step S340, the candidate link corresponding to the maximum value of the link utility value is determined as the target link.

[0076] This approach calculates the link utility value of each candidate link based on different service quality indicators and service type weights. By comparing these utility values, the candidate link with the highest value is selected as the target link. This method is highly effective, accurately selecting the link with the best overall service quality from numerous candidate links. It ensures that the selected link meets the needs of the data services to be transmitted to the greatest extent possible. Whether it's reducing latency for latency-sensitive services, ensuring transmission rates for bandwidth-sensitive services, or balancing various indicators for best-effort services, it effectively improves the efficiency and reliability of data transmission, optimizes the resource utilization of the satellite network, and provides a stable, high-quality transmission channel for various services.

[0077] Specifically, in the candidate path set from the source node to the destination node generated in the control plane, a subset of paths that meet the segmentation condition are selected, and then the link utility value of all paths is calculated using the aforementioned weighted summation formula. The path with the highest overall weight is selected as the optimal segmentation path, and the key nodes in the path are included in the segment list.

[0078] In step S350, the data to be transmitted is transmitted based on the target link.

[0079] After identifying the target link with the best overall performance from the candidate links, this target link is directly used to transmit the data to be transmitted. Since the target link is the optimal solution selected based on a comprehensive consideration of factors such as link attributes, service type, and service quality indicators, it can best adapt to the service requirements of the data to be transmitted, effectively ensuring the real-time performance (such as meeting the requirements of latency-sensitive services), efficiency (such as meeting the requirements of bandwidth-sensitive services), and stability of data transmission (avoiding significant transmission problems in best-effort services), thereby improving the overall data transmission quality, reducing the risk of transmission failure, and optimizing the utilization efficiency of satellite network resources.

[0080] In some embodiments, transmitting the data to be transmitted based on the target link includes: A segment list is generated based on the target link, the segment list including key node labels arranged in forwarding order; The data to be transmitted is transmitted based on nodes in the target link, wherein, At the source node, the segment list is encapsulated into the segment routing header of the data packet to be transmitted, and the segment list pointer is set to the number of critical nodes in the critical node label; the next transmission node of the data packet is the next critical node of the source node in the segment list; When the data packet is transmitted to the critical node indicated by the critical node label, the segment list pointer is decremented by 1, and the next transmission node of the data packet is updated to the next critical node based on the segment list, so as to transmit the data packet. When the data packet is transmitted to a non-critical node, it is transmitted to the next critical node based on the local routing list; The data packet is transmitted to the target node when the segment list pointer is 0.

[0081] The process involves first generating a segment list containing labels of critical nodes arranged in forwarding order based on the determined target link. At the source node, this segment list is encapsulated in the segment routing header of the data packet to be transmitted, and an initial segment list pointer is set. Subsequently, the data packet is transmitted between critical and non-critical nodes according to rules. Critical nodes update their pointers and the next transmission node, while non-critical nodes forward the packet to the next critical node based on their local routing lists, until the pointer reaches 0 and the packet reaches the target node. This scheme is highly effective. The segment list clarifies the data transmission path, reduces routing overhead in intermediate stages, and improves transmission efficiency and reliability. Simultaneously, the division of labor and cooperation between critical and non-critical nodes ensures accurate and rapid data transmission along the target link, effectively enhancing the performance and stability of data transmission in satellite networks.

[0082] Specifically, the source node encapsulates the generated Segment List into the Segment Routing Header (SRH) of the data packet, sets the initial Segments Left (SL) pointer (the value of which is equal to the number of intermediate nodes in the Segment List), and sets the initial destination address of the data packet to the first intermediate node in the Segment List. When the data packet arrives at an SR node (a node in the Segment List), the SR node updates the SL pointer (SL=SL-1), modifies the destination address of the data packet to the next Segment node, and queries the local routing table to complete the forwarding. When the data packet passes through a non-SR node, the non-SR node only looks up the table based on the current destination address and forwards the packet without modifying the SRH information. The data packet is forwarded to the final destination node when the SL pointer is 0, completing a source routing forwarding with differentiated QoS guarantee.

[0083] For example, in the set of all candidate paths from the source node to the destination node, the path with the highest comprehensive weight is selected as the optimal segmentation path, and the key nodes in the path are added to the Segment List. After the source node calculates the optimal path, it generates a Segment List composed of constellation labels (SID, Segment Identifier), which is encapsulated in the Segment Routing Header (SRH) of the data packet and contains key fields: Segments Left (SL): indicating the location (pointer) of the intermediate node to be visited; Segment List: satellite node labels arranged in forwarding order (the bottom of the stack is the first traversed node).

[0084] In this system, the source node, as the initiator of service traffic, is responsible for calculating the Segment List, which includes intermediate nodes, and performing initial encapsulation of data packets based on the service type (including the Segment List and segment pointer information). Its core function is to elect intermediate nodes through an optimization algorithm, generating a sequence of forwarding paths that meet the constraints. SR nodes, which are intermediate nodes included in the Segment List, perform three operations during forwarding: first, update the segment pointer (decrementing the Segments Left field by 1) to indicate the current forwarding progress; second, modify the destination address of the data packet to the next node in the Segment List; and third, query the specific path of the next Segment node based on its own routing table to complete the data packet forwarding. Non-SR nodes, which are nodes not included in the Segment List, only perform basic forwarding functions, i.e., querying the local routing table based on the current destination address of the data packet and completing the forwarding, without participating in any modification of information related to the Segment List (such as segment pointers, destination addresses, etc.).

[0085] The complete packet forwarding process combines source routing path guidance with traditional routing table lookups. The specific steps are as follows: (1) Source node encapsulation: The source node generates a Segment List (e.g., [source node, intermediate node A, intermediate node B, destination node]) and writes it into the segment routing header (SRH) of the data packet. At the same time, it sets the initial segment pointer (Segments Left = number of intermediate nodes, e.g. 2) and sets the initial destination address of the data packet to the first intermediate node in the Segment List (e.g., A).

[0086] (2) SR Node Forwarding: When a data packet arrives at an SR node (such as A), the following operations are performed: a. Update the segment pointer (Segments Left=2-1=1); b. Modify the destination address of the data packet to the next node in the Segment List (e.g., B); c. Query the local routing table to obtain the forwarding path of node B, and forward the data packet to the next hop.

[0087] (3) Forwarding by non-SR nodes: If a data packet passes through a non-SR node (such as an intermediate forwarding node between SR nodes) during the forwarding process, the node only queries the routing table based on the current destination address of the data packet (such as B) and forwards it directly to the next hop without modifying any information in the SRH.

[0088] (4) Destination Node Reception: When the data packet arrives at the last SR node (e.g., B), the segment pointer is updated to 0, the destination address is modified to the final destination node, and after a routing table lookup, it is forwarded to the destination node, completing the entire transmission process. The complete process is as follows: Figure 5 As shown.

[0089] This disclosure enables precise assurance of differentiated QoS. Through a differentiated QoS weighting mechanism, QoS indicator weights are dynamically allocated for latency-sensitive, bandwidth-sensitive, and best-effort services. Combined with the comprehensive quantification of multi-dimensional indicators, it achieves precise matching between service requirements and path performance, providing more comprehensive service quality assurance for multiple types of services compared to existing methods. The introduction of source routing forwarding and segmentation constraints avoids the single-point failure risk and complex deployment costs of centralized architectures. Furthermore, it simplifies path calculation through optimized intermediate node election, reduces the processing overhead of satellite nodes, and adapts to the resource-constrained characteristics of low-Earth orbit satellites. Thirdly, the source routing mechanism eliminates the need for intermediate nodes to participate in path decision-making, effectively reducing the impact of dynamic topology changes, improving forwarding efficiency and network stability, while remaining compatible with existing satellite network protocols, demonstrating strong feasibility for implementation.

[0090] This disclosure addresses the challenge of ensuring differentiated QoS in low-Earth orbit (LEO) satellite networks and overcomes the limitations of existing technologies in achieving precise QoS assurance under the highly dynamic and resource-constrained conditions of LEO satellite networks. Existing research has not fully overcome the challenge of coordinating and adapting to the "highly dynamic topology + limited resources + multi-service differentiated QoS" of LEO satellite networks: either due to reliance on centralized control or complex algorithms, it leads to a contradiction between real-time performance, reliability, and deployment; or due to insufficient consideration of QoS indicators and inefficient response to topology changes, it is difficult to continuously and stably meet the QoS requirements of multiple service types in scenarios with limited satellite network resources. These limitations collectively point to a core gap: the failure to achieve an effective balance between "precise QoS assurance," "satellite characteristic adaptation," and "low-complexity deployment." This disclosure, through clear service type classification (latency-sensitive, bandwidth-sensitive, and best-effort), distinguishes the QoS requirements of different services from the source, and utilizes traffic management to ensure that data is transmitted along the optimal path that meets specific service quality requirements. This includes a comprehensive consideration of key indicators such as latency, bandwidth, and reliability. The source-routing-based packet forwarding mechanism achieves efficient and accurate packet forwarding by integrating constellation tags and IP information, thus ensuring optimal performance for routing and forwarding data flows with different QoS from the same source.

[0091] In summary, this disclosure constructs a source routing forwarding system for differentiated QoS assurance in low-Earth orbit (LEO) satellite networks to meet the need for designing efficient routing technologies and achieving multiple QoS guarantees in highly dynamic and resource-constrained LEO satellite networks. This system integrates the path guidance advantages of source routing with a differentiated QoS weighting mechanism, designs customized path selection strategies for different services, and combines intermediate node optimization election under finite segmentation constraints to achieve accurate matching of multi-dimensional QoS indicators. Its ultimate goal is to avoid the single-point risk and deployment complexity of centralized architectures, overcome the one-sidedness of existing distributed methods in scenarios where high-speed movement of LEO satellites leads to frequent topology changes and limited node resources, and solve the real-time performance and implementation challenges of intelligent algorithm-based solutions. This provides an efficient, reliable, and easily deployable routing technology to meet the differentiated QoS assurance needs of multiple service scenarios.

[0092] It should be noted that the method of this embodiment can be executed by a single device, such as a computer or server. The method of this embodiment can also be applied in a distributed scenario, where multiple devices cooperate to complete the task. In such a distributed scenario, one of these devices may execute only one or more steps of the method of this embodiment, and the multiple devices will perform table processing with each other to complete the method described.

[0093] It should be noted that the above description describes some embodiments of this disclosure. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in a different order than that shown in the above embodiments and still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0094] Based on the same technical concept, corresponding to any of the methods in the above embodiments, this disclosure also provides a data transmission device for differentiated quality of service assurance in satellite networks, see [link to relevant documentation]. Figure 6 The data transmission device for differentiated quality of service assurance for satellite networks includes: The data acquisition module is used to acquire the data to be transmitted within the time slot, the source node and the target node of the data to be transmitted; The candidate link module is used to obtain candidate links from the source node to the target node and the link attributes of the candidate links based on the undirected spatiotemporal graph of the satellite network. The utility calculation module is used to determine the link utility value of the candidate link with respect to the quality of service index based on the link attributes and the service type of the data to be transmitted; The target link module is used to determine the candidate link corresponding to the maximum value of the link utility value as the target link; The data transmission module is used to transmit the data to be transmitted based on the target link.

[0095] This satellite network-oriented data transmission device first uses a data acquisition module to obtain the data to be transmitted within a time slot, along with its source and target nodes. Next, a candidate link module identifies candidate links from the source to the target and acquires their link attributes based on the undirected spatiotemporal graph of the satellite network. Then, a utility calculation module combines link attributes with service type to calculate the link utility value of the candidate links relative to service quality indicators. Finally, a target link module selects the link with the highest utility value as the target link. Finally, the data transmission module uses the target link to transmit the data. The device comprehensively considers satellite network characteristics, link attributes, and service requirements, accurately selecting the optimal target link, effectively ensuring differentiated service quality for different service types, improving data transmission efficiency and reliability, and optimizing the utilization of satellite network resources.

[0096] Specifically, such as Figure 7 As shown, the data transmission device for satellite networks may include: The topology and traffic generation module comprises three sub-modules: traffic generation, topology information collection, and dynamic topology construction. The traffic generation module generates simulated service data to be transmitted into the system, and parameters such as the traffic ratio, traffic volume, and generation time interval for different service types can be set. The topology information collection module collects satellite parameters and inter-satellite link information, and the dynamic topology construction module builds a real-time satellite network topology model based on the collected topology information.

[0097] The routing algorithm module executes a segmented path selection algorithm with differentiated QoS weights. Based on the satellite network topology information and the QoS weights of services, it uses a multi-index comprehensive evaluation algorithm to calculate the QoS matching degree of each path.

[0098] The data forwarding module includes control plane functions such as constellation label configuration, label distribution, source routing policy generation, label list conversion, and data plane functions such as service type awareness and data routing forwarding. The constellation label configuration module generates label information for each satellite node. Label distribution uses control plane protocols to distribute the configured constellation label information to each satellite node. The type awareness module identifies the type of service traffic entering the system using protocol header information. The source routing policy generation module formulates source routing policies based on the path information calculated by the routing algorithm module. The label list conversion module converts the routing path information obtained by the source routing policy generation module into a label list format suitable for use by the data forwarding module. The data forwarding module forwards data packets according to the label list.

[0099] The performance analysis and visualization module is responsible for monitoring key performance indicators of the algorithm. For service flows with different QoS requirements, it analyzes performance metrics such as latency, jitter, and bandwidth utilization. It also visualizes the various system performance indicators monitored and statistically analyzed by the algorithm performance analysis module in intuitive charts. A system visualization interface is developed to intuitively and graphically display information such as the satellite network topology, service traffic distribution, node status, and link status.

[0100] By coordinating the various sub-modules, a fully functional, efficient, and reliable data transmission system for satellite networks with differentiated quality of service assurance is constructed, meeting the high-quality transmission requirements of satellite networks for various services in complex environments.

[0101] For ease of description, the above apparatus is described in terms of its functions, divided into various modules. Of course, in implementing this disclosure, the functions of each module can be implemented in one or more software and / or hardware.

[0102] The apparatus described above is used to implement the data transmission method for differentiated quality of service assurance for satellite networks in any of the foregoing embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0103] Based on the same technical concept, corresponding to the methods of any of the above embodiments, this disclosure also provides a non-transitory computer-readable storage medium storing computer instructions for causing the computer to execute the data transmission method for differentiated quality of service assurance for satellite networks as described in any of the above embodiments.

[0104] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information accessible by a computing device.

[0105] The computer instructions stored in the storage medium of the above embodiments are used to cause the computer to execute the data transmission method for differentiated quality of service assurance for satellite networks as described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0106] Those skilled in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of this disclosure (including the claims) is limited to these examples; within the framework of this disclosure, the technical features of the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other variations of different aspects of the embodiments of this disclosure as described above, which are not provided in detail for the sake of brevity.

[0107] Additionally, to simplify the description and discussion, and to avoid obscuring the embodiments of this disclosure, the provided drawings may or may not show well-known power / ground connections to integrated circuit (IC) chips and other components. Furthermore, the apparatus may be shown in block diagram form to avoid obscuring the embodiments of this disclosure, and this also takes into account the fact that the details of implementation of these block diagram apparatuses are highly dependent on the platform on which the embodiments of this disclosure will be implemented (i.e., these details should be fully understood by those skilled in the art). While specific details (e.g., circuits) have been set forth to describe exemplary embodiments of this disclosure, it will be apparent to those skilled in the art that the embodiments of this disclosure can be implemented without these specific details or with variations thereof. Therefore, these descriptions should be considered illustrative rather than restrictive.

[0108] Although this disclosure has been described in conjunction with specific embodiments thereof, many substitutions, modifications, and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may be used with the embodiments discussed.

[0109] This disclosure is intended to cover all such substitutions, modifications, and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A method for differentiated quality of service (QoS) guarantee in satellite network, comprising: obtaining to-be-transmitted data, a source node and a target node of the to-be-transmitted data in a time slot; obtaining candidate links from the source node to the target node and link attributes of the candidate links based on a directed time-space graph of the satellite network; determining a link utility value of the candidate links with respect to a QoS indicator based on the link attributes and a service type of the to-be-transmitted data; determining a target link corresponding to a maximum value of the link utility value as the target link; and transmitting the to-be-transmitted data based on the target link. The determining of the link utility value of the candidate links with respect to the QoS indicator based on the link attributes and the service type of the to-be-transmitted data comprises: determining a utility function of the candidate links with respect to the QoS indicator based on the link attributes; determining a utility weight of the utility function based on the service type of the to-be-transmitted data; and obtaining the link utility value based on a weighted sum of the utility function and the utility weight. The QoS indicator comprises a delay, a residual bandwidth and a packet loss rate. The determining of the utility function of the candidate links with respect to the QoS indicator based on the link attributes comprises: determining the utility function of the candidate links with respect to the delay based on the link delay; determining the utility function of the candidate links with respect to the residual bandwidth based on the link residual bandwidth; and determining the utility function of the candidate links with respect to the packet loss rate based on the link packet loss rate. 4.The method of claim 3, further comprising: the link delay comprises a sum of a link propagation delay and a transmission delay on the candidate link; the link residual bandwidth comprises a minimum value of a sub-link residual bandwidth of a sub-link on the candidate link, the sub-link residual bandwidth comprising a total bandwidth of the sub-link minus an already used bandwidth; and the service type comprises a delay-sensitive service, a bandwidth-sensitive service or a best-effort service. The determining of the utility weight of the utility function based on the service type of the to-be-transmitted data comprises: for the delay-sensitive service, the utility weight of the link delay > the utility weight of the link packet loss rate > the utility weight of the link residual bandwidth; for the bandwidth-sensitive service, the utility weight of the link residual bandwidth > the utility weight of the link delay > the utility weight of the link packet loss rate; and for the best-effort service, the utility weight of the link residual bandwidth, the utility weight of the link delay and the utility weight of the link packet loss rate are the same.

2. The method of claim 1, wherein, The transmitting of the to-be-transmitted data based on the target link comprises: generating a segment list based on the target link, the segment list comprising key node labels arranged in a forwarding order; and transmitting the to-be-transmitted data based on nodes in the target link, wherein: at the source node, encapsulating the segment list into a segment routing header of a data packet of the to-be-transmitted data and setting a segment list pointer to a key node number of the key node labels; and a next transmission node of the data packet is a next key node of the source node in the segment list. ​ ​ ​ 3. The method of claim 2, wherein, ​ ​ obtain a utility function about the link delay based on the link delay in the link attribute and an adjustment coefficient; wherein the utility function about the link delay , is the adjustment coefficient, is the link delay; obtaining a utility function about the residual bandwidth based on the link residual bandwidth and the link maximum bandwidth in the link attribute; wherein the utility function about the residual bandwidth , is the link maximum bandwidth, is the link residual bandwidth; obtain a utility function about the packet loss rate based on the link packet loss rate and the attenuation coefficient in the link attribute; wherein the utility function about the packet loss rate is the attenuation coefficient, is the link packet loss rate. ​ ​ ​ The link packet loss rate comprises: wherein, is a link packet loss rate, is a candidate link from a source node S to a destination node D, is a sub-link packet loss rate between a node i and a node j in the candidate link .

5. The method of claim 2, wherein, ​ ​ ​ ​ ​ 6. The method of claim 1, wherein, ​ ​ ​ ​ ​ when the data packet is transmitted to a non-critical node, transmitting the data packet to the next critical node based on a local routing list; until the segment list pointer is 0, the data packet is transmitted to the target node. 7.The method of claim 1, further comprising: Slice the satellite motion cycle according to time to construct a directed space-time graph of the satellite network ; wherein the time slot sequence , is the ith time slot; is a node set of the satellite network; is a candidate link set between a source node S and a target node D, ; P is a time slot link attribute set between a node i and a node j below, including a time delay, a bandwidth, an inter-satellite distance and a packet loss rate; is the set of the to-be-transmitted data in the time slot.​ 8.A data transmission device for differentiated quality of service guarantee in a satellite network, comprising: a data acquisition module configured to acquire data to be transmitted, a source node and a target node of the data to be transmitted in a time slot; a candidate link module configured to obtain candidate links from the source node to the target node and link attributes of the candidate links based on a directed space-time graph of the satellite network; a utility calculation module configured to determine link utility values of the candidate links with respect to a quality of service indicator based on the link attributes and a service type of the data to be transmitted; a target link module configured to determine a target link as the candidate link corresponding to a maximum value of the link utility values; a data transmission module configured to transmit the data to be transmitted based on the target link. 9.An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of any one of claims 1 to 7 when executing the program. 10.A non-transitory computer-readable storage medium storing computer instructions for causing a computer to execute the method of any one of claims 1 to 7.

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