6g space-air-ground-sea integrated fusion architecture based on software-defined cloud-edge collaboration

Abstract

The present invention relates to the technical field of communications, and provides a 6G space-air-ground-sea integrated fusion architecture based on software-defined cloud-edge collaboration, comprising: three tiers of cloud nodes from low to high: an edge cloud, a space-based cloud, and a core cloud; the edge cloud comprises 6G-enabled ships based on software-defined networking and mobile edge computing technologies; the space-based cloud comprises low earth orbit satellites based on software-defined satellite technology and low earth orbit satellite constellations connected by means of an inter-satellite link; the core cloud comprises a space-based 6G core network; the edge cloud, the space-based cloud, and the core cloud follow a task offloading mechanism and an information feedback mechanism; the task offloading mechanism is configured to select, on the basis of characteristics of a task, a cloud node of a target tier for task processing; and the information feedback mechanism is configured such that the cloud node of the upper tier sends feedback information to a cloud node of the lower tier, so as to optimize task processing of the lower tier. The present invention achieves fast and flexible networking for a 6G space-air-ground-sea integrated fusion network, thereby realizing efficient utilization and collaborative management and control of resources.

Description

6G sky-ground-sea integrated fusion architecture based on software-defined cloud-edge collaboration TECHNICAL FIELD

[0001] The present application relates to the technical field of communication, in particular to a 6G sky-ground-sea integrated fusion architecture based on software-defined cloud-edge collaboration. BACKGROUND

[0002] With the increasing demand and diversity of maritime business, in order to support various digital applications related to maritime vessels, especially to meet the 6G communication services of ocean-going vessels, including computationally intensive and latency-sensitive 6G emerging services, it is necessary to update the existing Internet mobile communication technology. Therefore, it is of great significance to use 6G technology combined with low-orbit satellites to empower maritime communication and meet the 6G Internet business needs of maritime personnel.

[0003] However, due to the large-scale and topology time-varying nature of low-orbit satellite constellations, it is difficult for ground networks to directly cover the open sea, and there are still many challenges in network management and low resource utilization in 6G sky-ground-sea integrated networking. These problems can be solved by cloud-edge collaboration technology combining software-defined network technology, cloud computing and edge computing.

[0004] The prior art only studies the application of a single software-defined network technology or cloud-edge collaboration technology to satellite communication networks, and does not fully utilize the advantages of both to combine them in sky-ground-sea integrated networks. In addition, current research and application of 6G communication systems combined with low-orbit satellites mainly focuses on land, and there is still a lack of application research in maritime communication.

[0005] SUMMARY

[0006] The present application provides a 6G sky-ground-sea integrated fusion architecture based on software-defined cloud-edge collaboration to solve the defects in the prior art.

[0007] The present application provides a 6G sky-ground-sea integrated fusion architecture based on software-defined cloud-edge collaboration, including three levels of cloud nodes from low to high: edge cloud, sky-based cloud and core cloud; the edge cloud includes a shipborne 6G ship based on software-defined network and mobile edge computing technology; the sky-based cloud includes low-orbit satellites based on software-defined satellite technology and a constellation of low-orbit satellites connected through a star chain; the core cloud includes a land-based 6G core network; the edge cloud, the sky-based cloud and the core cloud follow a task uploading mechanism and an information feedback mechanism; the task uploading mechanism is configured to select a target level of cloud node for task processing according to the characteristics of the task; the information feedback mechanism is configured to send feedback information from the previous level of cloud node to the next level of cloud node to optimize the next level of task processing.

[0008] The application provides a 6G space-ground-sea integrated fusion architecture based on software-defined cloud-edge cooperation, and the task uploading mechanism further comprises the following steps: in the case that the cloud node at the current level cannot meet the processing requirement of the task, uploading the task to a cloud node at a level above the current level for processing.

[0009] The application provides a 6G space-ground-sea integrated fusion architecture based on software-defined cloud-edge cooperation, and the method for selecting the cloud node at the target level for processing the task according to the characteristics of the task comprises the following steps: in the case that the task is determined to be a local task with low computing amount or time delay sensitivity, allocating the local task to the edge cloud for processing; the method for determining the local task with low computing amount comprises the following steps: determining the local task with low computing amount according to a preset computing amount measurement index of the task; the method for determining the local task with time delay sensitivity comprises the following steps: determining the local task with time delay sensitivity according to a preset time delay measurement index of the task.

[0010] The application provides a 6G space-ground-sea integrated fusion architecture based on software-defined cloud-edge cooperation, and the method for selecting the cloud node at the target level for processing the task according to the characteristics of the task comprises the following steps: in the case that the task is determined to be a global task involving multi-device or resource scheduling, allocating the global task to the space-based cloud for processing.

[0011] The application provides a 6G space-ground-sea integrated fusion architecture based on software-defined cloud-edge cooperation, and the method for selecting the cloud node at the target level for processing the task according to the characteristics of the task comprises the following steps: in the case that the task is determined to be a complex task with high computing amount, allocating the complex task to the core cloud for processing; the method for determining the local task with high computing amount comprises the following steps: determining the complex task with high computing amount according to a preset computing amount measurement index of the task.

[0012] The application provides a 6G space-ground-sea integrated fusion architecture based on software-defined cloud-edge cooperation, and the method for uploading the task to a cloud node at a level above the current level for processing in the case that the cloud node at the current level cannot meet the processing requirement of the task comprises the following steps: uploading the task to the edge cloud, and in the case that the edge cloud determines that the task is a local task, processing the task by the edge cloud; in the case that the edge cloud determines that the task is a task that cannot be processed by the edge cloud, uploading the task to the space-based cloud; in the case that the space-based cloud determines that the task is a global task, processing the task by the space-based cloud; in the case that the space-based cloud determines that the task is a task that cannot be processed by the space-based cloud, uploading the task to the core cloud, and processing the task by the core cloud.

[0013] According to the 6G space-ground-sea integrated fusion architecture based on software-defined cloud edge collaboration provided by the application, the cloud node of the upper level sends feedback information to the cloud node of the lower level to optimize the task processing of the lower level, comprising: after the core cloud processes complex tasks, the feedback information is sent to the space-based cloud to optimize the software configuration of the space-based cloud by using the feedback information.

[0014] According to the 6G space-ground-sea integrated fusion architecture based on software-defined cloud edge collaboration provided by the application, the cloud node of the upper level sends feedback information to the cloud node of the lower level to optimize the task processing of the lower level, comprising: after the core cloud processes complex tasks, the feedback information is sent to the space-based cloud to optimize the software configuration of the space-based cloud by using the feedback information.

[0015] The 6G space-ground-sea integrated fusion architecture based on software-defined cloud edge collaboration provided by the application comprises an edge cloud, a space-based cloud and a core cloud, which constitutes a shipborne 6G and low-orbit satellite fusion network based on software-defined cloud edge collaboration, and realizes flexible networking of shipborne 6G and low-orbit satellites; It is especially suitable for scenarios that require high-speed and reliable communication across regions, environments (land, sea and air); The emphasized software-defined capability means that the network is more flexible and programmable, and can quickly adapt to future technology development and diversified business demands; Through the design of space-ground-sea integration, the communication accessibility and service quality in the global range are improved.

[0016] The 6G space-ground-sea integrated fusion architecture based on software-defined cloud edge collaboration provided by the application comprises a task uploading mechanism and an information feedback mechanism, the lower cloud can upload tasks to the upper cloud, and the upper cloud feeds back information to the lower cloud, so as to improve resource utilization and optimize related configurations through cloud edge collaboration and software definition, so that the system resource utilization is further improved.

DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the application or prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are some embodiments of the application, and those skilled in the art can also obtain other drawings according to these drawings without creative labor.

[0018] Fig. 1 is a schematic diagram of the 6G space-ground-sea integrated fusion architecture based on software-defined cloud edge collaboration provided by the application;

[0019] Fig. 2 is a flowchart of task uploading and information feedback provided by the application;

[0020] Fig. 3 is a flowchart of task uploading and information feedback provided by the application.

Specific embodiments

[0021] In order to make the objects, technical solutions and advantages of the present application clearer, the following will clearly and completely describe the technical solutions in the present application with reference to the drawings in the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0022] It should be noted that, in the description of the embodiments of the present application, the terms "comprising", "containing" or any other variants thereof are intended to cover the non-exclusive containing, so that the process, method, article or equipment including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or equipment. The specific meaning of the above terms in the present application can be understood according to the specific circumstances by a person of ordinary skill in the art.

[0023] The following describes the 6G space-ground-sea integrated fusion architecture based on software-defined cloud-edge collaboration provided by the embodiments of the present application with reference to Figures 1-3.

[0024] Figure 1 is a schematic diagram of the 6G space-ground-sea integrated fusion architecture based on software-defined cloud-edge collaboration provided by the present application, as shown in Figure 1, the architecture includes three levels of cloud nodes from low to high: edge cloud, space-based cloud and core cloud; the edge cloud includes a shipborne 6G ship based on software-defined network (Software-Defined Networking, SDN) and mobile edge computing (Mobile Edge Computing, MED) technology; the space-based cloud includes a low-orbit satellite based on software-defined satellite technology and a constellation of low-orbit satellites connected through a star chain; the core cloud includes a land-based 6G core network; the edge cloud, the space-based cloud and the core cloud comply with a task uploading mechanism and an information feedback mechanism; the task uploading mechanism is configured to select a target level cloud node for task processing according to the characteristics of the task; the information feedback mechanism is configured to send feedback information from the cloud node at the previous level to the cloud node at the next level to optimize the task processing at the next level.

[0025] The 6G space-ground-sea integrated fusion architecture based on software-defined cloud-edge collaboration provided by the present application represents the forefront of future communication technology development, aiming to achieve seamless, efficient and flexible communication services worldwide through a highly integrated multi-level cloud architecture. The following is a further description of several core features of the architecture.

[0026] Edge Cloud: By combining software-defined networking and mobile edge computing technology (SDN-MEC), it can provide ultra-low latency services, accelerate data processing, and reduce backhaul network burden. This layer is particularly important for special environments such as the sea and remote areas, effectively improving the service quality and response speed of local areas. The shipborne 6G ship based on software-defined networking and mobile edge computing technology can be understood as a ship equipped with mobile edge computing equipment based on SDN-MEC.

[0027] Space-based Cloud: Using Low Earth Orbit (LEO) and Inter-Satellite Link (ISL) technology, it forms a global communication network layer. Software-defined satellite (SDS) technology enables dynamic configuration of satellite resources according to demand, providing flexible bandwidth allocation and quality of service guarantees. This layer not only solves the problem of remote areas and ocean coverage, but also provides the possibility of continuous communication and data transmission worldwide.

[0028] Core Cloud: As the center of the entire architecture, the land-based 6G core network is responsible for global network management and data processing, ensuring efficient data exchange and routing. The core cloud supports large-scale data processing and complex business logic, providing powerful computing and storage resources for upper-layer applications.

[0029] Task uploading mechanism: According to the characteristics of the task (such as delay requirements, data volume, computational complexity, etc.), the most suitable cloud node level for executing the task is intelligently selected. This not only optimizes resource allocation, but also ensures service quality and user experience.

[0030] Information feedback mechanism: A closed-loop control between upper and lower levels is formed, enabling the system (i.e., the fusion architecture) to continuously optimize according to actual running conditions. After the upper cloud node processes the task, the results or optimization instructions are fed back to the lower level, which helps to adjust strategies in real time, optimize resource use efficiency, and quickly respond to network changes or abnormal situations.

[0031] Therefore, the architecture provided by the present application is particularly suitable for scenarios that require high-speed, reliable communication across regions, environments (land, sea, air), such as remote medical treatment, emergency rescue, ocean monitoring, and autonomous driving; through the design of space-ground-sea integration, the communication accessibility and service quality worldwide are improved, which is of great significance for building global digital economic infrastructure and promoting digital transformation; the emphasis on software-defined capabilities means that the network is more flexible and programmable, and can quickly adapt to future technological developments and diverse business needs, which is a key technical support for moving towards the 6G and beyond era.

[0032] Based on the content of the above embodiment, as an optional embodiment, the cloud node of the last level sends feedback information to the cloud node of the next level to optimize the task processing of the next level, including: after the core cloud processes the complex task, the feedback information is sent to the space-based cloud to optimize the soft configuration of the space-based cloud using the feedback information; and after the space-based cloud processes the global task, the feedback information is sent to the edge cloud to adjust the network configuration and computing resource allocation of the edge cloud.

[0033] The SDN-MEC in the edge cloud can measure the current task, existing channel resources and communication environment, integrate the obtained information under the current environment based on the SDN technology to reconfigure and optimize the MEC function, so that the function configuration can be dynamically adjusted according to different situations. In addition, the SDN-MEC can also receive feedback information from the upper cloud, i.e. the space-based cloud, to store relevant task information and optimize the resource configuration and mode setting related thereto.

[0034] The SD-S in the space-based cloud can use software-defined radio technology to flexibly control and dynamically adjust the modulation mode, bandwidth, waveform, frequency, and beam and antenna gain of satellite radio signals, realize software definition of satellite hardware, and further realize reconfiguration of satellite payload function and flexible configuration of on-orbit tasks. In addition, the SD-S can also receive feedback information from the 6G core cloud and cooperative information from other SD-S through inter-satellite links to realize reasonable scheduling of resources and optimized arrangement of related configurations, thereby improving the collaborative ability and overall performance of the system.

[0035] The core cloud based on the 6G core network is used to implement complex tasks with large computing amount, and is also responsible for using cloud computing technology to realize resource scheduling, integration, management optimization and cooperation within the cloud computing range of various resources distributed on the network. The management and scheduling of all resources are defined by software, and the SDN controller is used to realize flexible management and dynamic configuration of software and hardware resources, so as to dynamically modify the network configuration to support different computing task requirements from the space-based satellite cloud.

[0036] Based on the content of the above embodiment, as an optional embodiment, the present application provides a 6G space-earth-sea integrated fusion architecture based on software-defined cloud-edge cooperation, which selects a target level of cloud node for task processing according to the characteristics of the task, including: in the case that the task is determined to be a local task with low computing amount or time delay sensitivity, the local task is allocated to the edge cloud for processing; wherein the method for determining that the task is a local task with low computing amount includes: determining that the task is a local task with low computing amount according to a preset computing amount measurement index of the task; the method for determining that the task is a local task with time delay sensitivity includes: determining that the task is a local task with time delay sensitivity according to a preset time delay measurement index of the task.

[0037] Specifically, the low-computational task allocation method includes but is not limited to the following main points.

[0038] Pre-design computational load measurement indicators: The present application can set a set of standards or models to measure the computational demand of tasks. These indicators may include CPU cycle count, memory usage, expected processing time, etc. These standards help the present application quantify the computational intensity of each task.

[0039] Task characteristic evaluation: When a new task is generated, the present application will automatically evaluate the computational demand of the task according to the above indicators. If the evaluation result shows that the computational resources required by the task are lower than a certain preset threshold, the task is marked as "low computational load".

[0040] Task allocation decision: Once the task is determined to be low computational load, the system will immediately allocate it to edge cloud processing. Since the edge cloud is close to the data source, it can respond quickly, even if the computational demand is not large, it can efficiently complete the task.

[0041] Further, the time-sensitive local task allocation method includes but is not limited to the following points.

[0042] Pre-set latency measurement indicators: The system also needs an evaluation system for latency sensitivity, such as the maximum delay time allowed for task execution, the level of real-time interaction demand, and the freshness requirement of data.

[0043] Latency demand analysis: For each new task, the system will analyze its sensitivity to latency according to the latency measurement indicators. If the type of the task requires extremely short response time to ensure immediate interaction or decision accuracy, such as remote surgery guidance, automatic driving control command, etc., the task is classified as "time-sensitive".

[0044] Quick response deployment: After identifying the time-sensitive task, the system will prioritize deploying it on the edge cloud for execution. The proximity deployment characteristics of the edge cloud can significantly reduce data transmission latency, ensuring that the task can be processed within the specified time and meet strict latency requirements.

[0045] Optionally, the 6G space-ground-sea integrated fusion architecture based on software-defined cloud-edge collaboration provided by the present application allocates global tasks to space-based cloud processing in the case of global tasks involving multi-device or resource scheduling.

[0046] Space-based cloud, especially the network composed of low-orbit satellites and Starlink technology, has unique coverage advantages and global perspectives, and can efficiently coordinate various resources and devices without geographical restrictions, realizing wide-area connection and management across space, land and sea. The following are several key points to illustrate the effectiveness of this strategy:

[0047] Global view and resource scheduling: Through its global network coverage, the space-based cloud can obtain the state information and resource distribution of all participating devices, which is crucial for tasks that require unified scheduling of cross-regional resources. Whether it is ocean monitoring, cross-border logistics tracking, or large-scale environmental monitoring projects, the space-based cloud can provide non-blind area monitoring and scheduling capabilities.

[0048] Multi-device collaboration: In global tasks, multiple devices or sensors often need to work together. The space-based cloud's high-bandwidth and low-latency communication capabilities ensure timely and accurate information exchange between these devices, enabling efficient collaboration. The software-defined capability allows it to dynamically configure network resources, optimize data flow according to task requirements, and support the smooth execution of complex multi-device tasks.

[0049] In summary, the present invention allocates global tasks involving multiple devices or resource scheduling to the space-based cloud for processing, fully utilizing its global coverage, unified resource scheduling, and efficient collaborative work advantages. This lays a solid foundation for the efficient operation and widespread application of the 6G era's space-earth-sea integrated fusion architecture.

[0050] Optionally, the 6G space-earth-sea integrated fusion architecture based on software-defined cloud-edge collaboration provided by the present invention allocates complex tasks to core cloud processing when it is determined that the task is a computationally intensive complex task. The method for determining that the task is a computationally intensive local task includes: determining that the task is a computationally intensive complex task according to a pre-set task computational quantity measurement index.

[0051] In the present invention, for computationally intensive and complex tasks, allocating them to core cloud processing is an efficient and reasonable resource allocation method. Core cloud usually has powerful computing capability and rich storage resources, and can handle tasks that edge cloud or space-based cloud cannot effectively handle due to resource limitations. The following are the specific implementation details of this strategy:

[0052] The present invention will use a series of pre-set measurement indexes to evaluate the computational complexity of the task. These indexes may include the number of expected computation cycles, the amount of data to be processed, algorithm complexity, memory usage, and other parameters. Through these indexes, the present invention can quantitatively analyze the resource requirements of each task. Once a task is evaluated as computationally intensive (i.e., its computational requirements exceed the processing capacity of the space-based cloud (or edge cloud) or the set high computation threshold), the present invention will automatically mark it as a "computationally intensive complex task". Core cloud, with its high-performance computing clusters, large-scale parallel processing capabilities, and rich storage resources, can efficiently execute these tasks while ensuring data security and integrity.

[0053] As an optional embodiment, based on the content of the above embodiments, the task uploading mechanism further comprises: in the case that the cloud node at the current level cannot meet the processing requirements of the task, uploading the task to the previous level at the current level for processing.

[0054] Specifically, the task is uploaded to the edge cloud, in the case that the edge cloud determines that the task is a local task, the edge cloud processes the task; in the case that the edge cloud determines that the task is a task that the edge cloud cannot process, the task is uploaded to the space-based cloud; in the case that the space-based cloud determines that the task is a global task, the space-based cloud processes the task; in the case that the space-based cloud determines that the task is a task that the space-based cloud cannot process, the task is uploaded to the core cloud for processing.

[0055] As an optional embodiment, Fig. 2 is one of the flow diagrams of task uploading and information feedback provided by the present application, as shown in Fig. 2, including but not limited to the following steps:

[0056] Firstly, the task is uploaded to the edge cloud of the shipborne 6G, and the current task, existing channel resources and communication environment are measured by SDN-EMC;

[0057] Secondly, the edge cloud solves the local task with low computing power or time delay sensitivity, and uploads to the space-based cloud node, i.e. low-orbit satellite, if it is a global task that cannot be processed, and obtains feedback from the space-based cloud to optimize configuration and task processing.

[0058] Thirdly, the space-based cloud integrates the computing power resources and communication resources of the space-based cloud low-orbit satellite constellation through SD-S and ISL, and schedules and arranges them to fully utilize network resources to complete global tasks.

[0059] Fourthly, if the space-based computing platform cannot process the complex task with large amount of calculation, the task is uploaded to the core cloud for processing, and information feedback is obtained from the core cloud to redefine and optimize the software related task configuration of the space-based node.

[0060] As an optional embodiment, Fig. 3 is another flow diagram of task uploading and information feedback provided by the present application, as shown in Fig. 3, after the task is uploaded, it is firstly judged whether it is a local task with low amount of calculation or time delay sensitivity, if so, it is uploaded to the edge cloud SDN-MEC which can process it for calculation. If not or it is a computing task that cannot be processed locally, it is further uploaded to the space-based satellite cloud, and it is judged whether it is a global task involving multi-device or resource scheduling, if so, it is processed by the SD-S low-orbit satellite constellation connected through ISL. If not or it is a computing task that cannot be processed by the space-based cloud, it is a complex task with large amount of calculation or high complexity, which needs to be uploaded to the 6G core network core cloud for processing.

[0061] Meanwhile, based on the information feedback mechanism provided in the invention, information can be fed back to the next level after the previous level is processed. Specifically, the core cloud processes complex tasks with large computational load or high complexity, and then feeds back the relevant task information to the space-based cloud, which optimizes the software configuration of the relevant computing tasks with the help of software-defined technology. Similarly, after the space-based cloud processes global tasks, it transmits feedback information of the global tasks to the edge cloud based on SDN-MEC, so that it obtains useful information related to the global tasks and performs resource rearrangement and optimization reconstruction through software-defined architecture.

[0062] The information feedback and resource optimization process from the core cloud to the space-based cloud and then to the edge cloud highlights the important role of cross-level collaborative optimization mechanism in processing complex tasks and global tasks. The specific steps and advantages are as follows:

[0063] Core cloud processing and feedback: In the face of tasks with large computational load or high complexity, the core cloud, with its powerful computing capacity and rich resource reserves, undertakes the heavy task of processing these tasks. Once the task is completed, the core cloud not only returns the processing result, but also feeds back the key information, lessons learned or optimization suggestions in the task execution process to the space-based cloud. This feedback mechanism helps the space-based cloud understand which computing strategies, algorithms or resource configurations are most effective, so as to pre-optimize the software configuration in future similar tasks and improve processing efficiency and accuracy.

[0064] Optimization and re-feedback of space-based cloud: The space-based satellite cloud with software-defined technology can dynamically adjust the soft configuration of its computing tasks, such as algorithm parameters, task scheduling strategies or resource allocation schemes, using feedback information from the core cloud. This process enhances the intelligence and adaptability of the space-based cloud, ensuring that it more efficiently manages resources globally to meet the needs of different regions and scenarios. After processing global tasks, the space-based cloud continues to transmit feedback information of task execution and global perspective insights to the edge cloud, promoting the downward dissemination of knowledge and optimization strategies.

[0065] Dynamic optimization of edge cloud: The ship-borne 6G edge cloud, through SDN (Software Defined Network) and MEC (Mobile Edge Computing) technology, can perform more accurate resource rearrangement and configuration optimization according to the feedback from the space-based cloud. SDN enables the edge cloud to dynamically adjust network structure and data flow path, reducing latency; MEC makes computing closer to data sources, speeding up response. Such feedback loop enables the edge cloud to better support local, latency-sensitive applications while maintaining consistency and synergy with global tasks.

[0066] The 6G space-sea-air integrated fusion architecture based on software-defined cloud-edge collaboration provided by the application realizes reasonable hierarchical allocation and control of computing resources existing in the network by means of software-defined flexible cloud-edge collaboration of sea base, space base and land base, realizes rapid response and reasonable access of computing tasks, optimization scheduling of computing resources and real-time feedback of computing results, constructs an open capability interface of the software-defined cloud-edge collaboration network facing the business, and meets the differentiated needs of 6G business in a complex marine environment.

[0067] Finally, it should be noted that: the above examples are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing examples, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing examples, or make equivalent replacement for part of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A 6G integrated architecture for space, air, and sea based on software-defined cloud-edge collaboration, characterized in that, It includes three levels of cloud nodes from low to high: edge cloud, space-based cloud, and core cloud; The edge cloud includes a shipborne 6G vessel based on software-defined networking and mobile edge computing technologies; the space-based cloud includes low-Earth orbit satellites based on software-defined satellite technology and a constellation of low-Earth orbit satellites connected by Starlink; the core cloud includes a land-based 6G core network. The edge cloud, the space-based cloud, and the core cloud follow a task upload mechanism and an information feedback mechanism; the task upload mechanism is configured to select cloud nodes at the target level for task processing based on the characteristics of the task. The information feedback mechanism is configured such that the upper-level cloud node sends feedback information to the lower-level cloud node to optimize the task processing of the lower level.

2. The 6G integrated architecture for space, air, and sea based on software-defined cloud-edge collaboration as described in claim 1, characterized in that, The task upload mechanism also includes: If the current cloud node cannot meet the processing requirements of the task, the task will be uploaded to the next higher level for processing.

3. The 6G integrated architecture for space, air, and sea based on software-defined cloud-edge collaboration as described in claim 1, characterized in that, Based on the characteristics of the task, select the target-level cloud node for task processing, including: If a task is determined to be a local task with low computational load or latency sensitivity, the local task is assigned to edge cloud processing. The method for identifying a task as a local task with low computational load includes: identifying a task as a local task with low computational load based on a preset computational load measurement index. Methods for identifying a task as a latency-sensitive local task include: determining the task as a latency-sensitive local task based on preset latency measurement indicators.

4. The 6G integrated architecture for space, air, and sea based on software-defined cloud-edge collaboration as described in claim 3, characterized in that, Based on the characteristics of the task, select the target-level cloud node for task processing, including: If a task is determined to be a global task involving multiple devices or resource scheduling, the global task is assigned to the space-based cloud for processing.

5. The 6G integrated architecture for space, air, and sea based on software-defined cloud-edge collaboration as described in claim 3, characterized in that, Based on the characteristics of the task, select the target-level cloud node for task processing, including: If a task is determined to be a complex task with a large computational load, the complex task should be assigned to the core cloud processing. One method for identifying a task as a computationally intensive local task is to determine that the task is a complex task with high computational complexity based on a preset computational complexity metric.

6. The 6G integrated architecture for space, air, and sea based on software-defined cloud-edge collaboration as described in claim 5, characterized in that, If the current cloud node cannot meet the processing requirements of the task, the task will be uploaded to the next higher level for processing, including: The task is uploaded to the edge cloud. If the edge cloud determines that the task is a local task, it will process the task. If the edge cloud determines that the task is one that it cannot process, the task will be uploaded to the space-based cloud. If the space-based cloud determines that the task is a global task, then the space-based cloud will handle the task; if the space-based cloud determines that the task is one that it cannot handle, then the task will be uploaded to the core cloud for processing.

7. The 6G integrated architecture for space, air, and sea based on software-defined cloud-edge collaboration as described in claim 5, characterized in that, The upper-level cloud node sends feedback information to the lower-level cloud node to optimize the task processing at the lower level, including: After the core cloud processes a complex task, it sends feedback information to the space-based cloud to optimize the soft configuration of the space-based cloud.

8. The 6G integrated architecture for space, air, and sea based on software-defined cloud-edge collaboration as described in claim 5, characterized in that, The upper-level cloud node sends feedback information to the lower-level cloud node to optimize the task processing at the lower level, including: After the space-based cloud processes the global task, it sends feedback information to the edge cloud to adjust the network configuration and computing resource allocation of the edge cloud.

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