Saturation prediction method and device for inter-satellite link load

Abstract

The application discloses a load saturation prediction method and device for an inter-satellite link, which is applied to a gateway station and comprises the following steps: acquiring first traffic information required by a first satellite for assisting in forwarding data of each second satellite in a same first period in each sampling period, constructing a first data set corresponding to each first period, and determining a first distribution curve; acquiring second traffic information required by the first satellite for assisting in forwarding data of each second satellite in a second period, constructing a second data set corresponding to the second period, and determining a second distribution curve; determining a channel capacity of the inter-satellite link, and broadcasting the channel capacity, the first distribution curve and the second distribution curve to the first satellite; determining a conversion parameter between the first distribution curve corresponding to the second period and the first distribution curve corresponding to a third period, predicting a third distribution curve corresponding to the third period; and selecting a prediction point in the third distribution curve, and determining a load saturation of the first satellite in the third period.

Description

Technical Field

[0001] This application relates to the field of satellite communication technology, and in particular to a method and apparatus for predicting load saturation of inter-satellite links. Background Technology

[0002] Low Earth orbit (LEO) satellites achieve continuous coverage and communication services by constructing satellite constellations. However, the high-speed movement of LEO satellites causes their coverage areas to switch dynamically, and the connections between LEO satellites and ground terminals, as well as inter-satellite links, change frequently, resulting in a constantly evolving network topology.

[0003] In actual operation, the communication capacity of low-Earth orbit (LEO) satellites is physically limited. The bandwidth and processing power of onboard relay equipment cannot be infinitely expanded, especially in areas with high data relay demand, which may exceed the processing capacity of the corresponding LEO satellite. In other words, the LEO satellite cannot independently handle all data relay tasks. This leads to localized congestion in the satellite network, causing data packet loss, increased transmission latency, and other problems, severely impacting the quality of communication services.

[0004] Therefore, it is necessary to increase the number of satellites to assist low-Earth orbit (LEO) satellites in relaying data, thereby alleviating the data relay tasks that exceed the processing capacity of the LEO satellites. However, due to the lack of prediction of the load saturation of satellites assisting in data relay in the next time period, it is possible that various LEO satellites may relay data to the satellite in a concentrated manner, causing congestion and affecting the quality of satellite communication.

[0005] There is currently no effective solution to the technical problem in the existing technology that lacks the ability to predict the load saturation of satellites assisting in data relay, which affects communication quality. Summary of the Invention

[0006] The embodiments of this disclosure provide a method, apparatus, and storage medium for predicting the load saturation of inter-satellite links, in order to at least solve the technical problem in the prior art of lacking the ability to predict the load saturation of satellites assisting in forwarding data, which affects communication quality.

[0007] According to one aspect of the present disclosure, a load saturation prediction method for inter-satellite links is provided, applied to a gateway station, comprising: acquiring first traffic information required for a first satellite to assist in forwarding data from various second satellites within the same first time period in each sampling period, constructing a first dataset corresponding to each first time period based on the first traffic information, and determining a first distribution curve corresponding to each first dataset; acquiring second traffic information required for a first satellite to assist in forwarding data from various second satellites within a second time period, constructing a second dataset corresponding to the second time period based on the second traffic information, and determining a second distribution curve corresponding to the second dataset, wherein the second time period is the current time period; and determining the channel capacity corresponding to the inter-satellite link. The channel capacity, the first distribution curve, and the second distribution curve are broadcast to the first satellite, where the inter-satellite link represents the communication link established between the first satellite and each of the second satellites. The conversion parameter between the first distribution curve corresponding to the second time period and the first distribution curve corresponding to the third time period is determined, and the third distribution curve corresponding to the third time period is predicted using the conversion parameter and the second distribution curve, where the third time period represents the next time period after the second time period. A prediction point is selected in the third distribution curve, and the load saturation of the first satellite in the third time period is determined based on the prediction point and the channel capacity, where the prediction point includes the traffic required for the first satellite to assist in forwarding data from each of the second satellites in the third time period, and the corresponding probability density.

[0008] According to another aspect of the present disclosure, a storage medium is also provided, the storage medium including a stored program, wherein, when the program is executed, a processor performs any of the methods described above.

[0009] According to another aspect of the present disclosure, a load saturation prediction device for inter-satellite links is also provided, comprising: a first distribution curve determination module, configured to acquire first traffic information required for a first satellite to assist in forwarding data from various second satellites within the same first time period in each sampling period, and construct a first dataset corresponding to each first time period based on the first traffic information, and determine a first distribution curve corresponding to each first dataset; a second distribution curve determination module, configured to acquire second traffic information required for a first satellite to assist in forwarding data from various second satellites within a second time period, and construct a second dataset corresponding to the second time period based on the second traffic information, and determine a second distribution curve corresponding to the second dataset, wherein the second time period is the current time period; and an information broadcasting module, configured to determine the load saturation prediction device for inter-satellite links. The system determines the channel capacity and broadcasts the channel capacity, first distribution curve, and second distribution curve to the first satellite, where the inter-satellite link represents the communication link established between the first satellite and each of the second satellites; a third distribution curve prediction module is used to determine the conversion parameter between the first distribution curve corresponding to the second time period and the first distribution curve corresponding to the third time period, and uses the conversion parameter and the second distribution curve to predict the third distribution curve corresponding to the third time period, where the third time period represents the next time period after the second time period; and a prediction module is used to select prediction points in the third distribution curve, and determine the load saturation of the first satellite in the third time period based on the prediction points and the channel capacity, where the prediction points include the traffic required for the first satellite to assist in forwarding data from each of the second satellites in the third time period, and the corresponding probability density.

[0010] According to another aspect of the present disclosure, a load saturation prediction device for inter-satellite links is also provided, comprising: a processor; and a memory connected to the processor, configured to provide the processor with instructions for processing the following steps: acquiring first traffic information required for a first satellite to assist in forwarding data from various second satellites within the same first time period in each sampling period, constructing a first dataset corresponding to each first time period based on the first traffic information, and determining a first distribution curve corresponding to each first dataset; acquiring second traffic information required for a first satellite to assist in forwarding data from various second satellites within a second time period, constructing a second dataset corresponding to the second time period based on the second traffic information, and determining a second distribution curve corresponding to the second dataset, wherein the second time period is the current... The process involves: determining the channel capacity corresponding to the inter-satellite link and broadcasting the channel capacity, the first distribution curve, and the second distribution curve to the first satellite, where the inter-satellite link represents the communication link established between the first satellite and each of the second satellites; determining the conversion parameter between the first distribution curve corresponding to the second time period and the first distribution curve corresponding to the third time period, and using the conversion parameter and the second distribution curve to predict the third distribution curve corresponding to the third time period, where the third time period represents the next time period after the second time period; selecting prediction points in the third distribution curve, and determining the load saturation of the first satellite in the third time period based on the prediction points and the channel capacity, where the prediction points include the traffic required for the first satellite to assist in forwarding data from each of the second satellites in the third time period, and the corresponding probability density.

[0011] To address the lack of prediction for the load saturation of the first satellite assisting in relaying data from the second satellite, this application provides a method for predicting load saturation in inter-satellite links. The gateway station obtains a transformation parameter between the first distribution curve corresponding to the second time period and the first distribution curve corresponding to the third time period, based on a pre-determined first distribution curve. Further, the gateway station uses the transformation parameter to transform the second distribution curve corresponding to the second time period, thereby predicting the third distribution curve corresponding to the third time period.

[0012] Therefore, based on the traffic and corresponding probability density information contained in the prediction points extracted from the third distribution curve, the gateway station can predict the load saturation of the first satellite in the third time period, so as to coordinate the task of the first satellite assisting in forwarding data from various second satellites. This solves the technical problem in existing technologies of lacking the ability to predict the load saturation of satellites assisting in forwarding data, which affects communication quality. Attached Figure Description

[0013] The accompanying drawings, which are included to provide a further understanding of this disclosure and form part of this application, illustrate exemplary embodiments of this disclosure and are used to explain this disclosure, but do not constitute an undue limitation of this disclosure. In the drawings: Figure 1 This is a schematic diagram illustrating the communication connection relationship between the first satellite, the second satellite, and the gateway station according to Embodiment 1 of this disclosure; Figure 2A This is a hardware structure block diagram of the first and second satellites according to Embodiment 1 of this disclosure; Figure 2B This is a schematic diagram of the hardware architecture of the gateway station according to Embodiment 1 of this disclosure; Figure 3 This is a flowchart illustrating the load saturation prediction method for inter-satellite links according to Embodiment 1 of this disclosure; Figure 4 It is a comparison diagram of the first distribution curve corresponding to the second time period and the first distribution curve corresponding to the third time period, according to Embodiment 1 of this disclosure; Figure 5A This is a schematic diagram of the second distribution curve according to Embodiment 1 of this disclosure; Figure 5B This is a schematic diagram of the first distribution curve according to Embodiment 1 of this disclosure; Figure 6 This is a schematic diagram of a load saturation prediction device for inter-satellite links according to Embodiment 2 of this disclosure; and Figure 7 This is a schematic diagram of a load saturation prediction device for inter-satellite links according to Embodiment 3 of this disclosure. Detailed Implementation

[0014] To enable those skilled in the art to better understand the technical solutions of this disclosure, the technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this disclosure, and not all embodiments. Based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this disclosure.

[0015] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this disclosure described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus. Example 1

[0016] According to this embodiment, a method embodiment for predicting load saturation of inter-satellite links is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Also, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0017] Figure 1 A schematic diagram illustrating the communication connection relationship between the first satellite, the second satellite, and the gateway station according to this embodiment is shown. (Reference) Figure 1 As shown, the second satellites 201-202 establish communication connections with the terminal equipment in the corresponding areas 301-302. Since the data transmission traffic required for areas 301-302 exceeds the processing capacity of the corresponding second satellites 201-202, the first satellite 101 is needed as a relay node to assist the second satellites 201-202 in forwarding some data from areas 301-302. The aforementioned communication switching and forwarding assistance process is managed and coordinated by the gateway station 40.

[0018] Figure 2A Further shown Figure 1 A schematic diagram of the hardware architecture of the first satellite 101 and the second satellites 201-202. (Reference) Figure 2A As shown, the first satellite 101 and the second satellites 201-202 include an integrated electronic system, which includes a processor, a memory, a bus management module, and a communication interface. The memory is connected to the processor, allowing the processor to access the memory, read program instructions stored in the memory, read data from the memory, or write data to the memory. The bus management module is connected to the processor and also to a bus such as a CAN bus. Thus, the processor can communicate with onboard peripherals connected to the bus through the bus managed by the bus management module. Furthermore, the processor also communicates with devices such as cameras, star sensors, telemetry and control transponders, and data transmission equipment via the communication interface. Those skilled in the art will understand that... Figure 2A The structure shown is for illustrative purposes only and does not limit the structure of the aforementioned electronic device. For example, the first and second satellites may also include components that are more... Figure 2A The more or fewer components shown, or having the same Figure 2A The different configurations shown.

[0019] Figure 2B Further shown Figure 1 A schematic diagram of the hardware architecture of CITIC Gateway 40. (Reference) Figure 2BAs shown, the gateway station 40 may include one or more processors (processors may include, but are not limited to, microprocessors such as MCUs or programmable logic devices such as FPGAs), a memory for storing data, a transmission device for communication functions, and an input / output interface. The memory, transmission device, and input / output interface are connected to the processor via a bus. In addition, it may also include a display, keyboard, and cursor control device connected to the input / output interface. Those skilled in the art will understand that... Figure 2B The structure shown is for illustrative purposes only and does not limit the structure of the aforementioned electronic device. For example, a gateway station may also include... Figure 2B The more or fewer components shown, or having the same Figure 2B The different configurations shown.

[0020] It should be noted that, Figure 2A and Figure 2B One or more processors and / or other data processing circuits shown herein may generally be referred to as "data processing circuitry". This data processing circuitry may be embodied, in whole or in part, in software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuitry may be a single, independent processing module, or may be integrated, in whole or in part, into any other element in a computing device. As involved in embodiments of this disclosure, the data processing circuitry serves as processor control (e.g., selection of a variable resistor termination path connected to an interface).

[0021] Figure 2A and Figure 2B The memory shown can be used to store software programs and modules for application software, such as the program instruction / data storage device corresponding to the load saturation prediction method for inter-satellite links in the embodiments of this disclosure. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, thereby implementing the load saturation prediction method for inter-satellite links described above. The memory may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory.

[0022] It should be noted here that, in some optional embodiments, the above... Figure 2A and Figure 2B The device shown may include hardware elements (including circuitry), software elements (including computer code stored on a computer-readable medium), or a combination of both hardware and software elements. It should be noted that... Figure 2A and Figure 2B This is only one instance of a specific particular instance, and is intended to illustrate the types of components that may exist in the aforementioned devices.

[0023] Under the aforementioned operating environment, according to the first aspect of this embodiment, a method for predicting the load saturation of inter-satellite links is provided. This method consists of... Figure 1 The gateway station 40 shown is implemented. Figure 3 A flowchart illustrating the method is shown below. (Refer to...) Figure 3 As shown, the method includes: S302: Obtain the first traffic information required for the first satellite to assist in forwarding the data of each second satellite within the same first time period in each sampling period, and construct the first dataset corresponding to each first time period based on the first traffic information, and determine the first distribution curve corresponding to each first dataset; S304: Obtain the second traffic information required for the first satellite to assist in forwarding data from each of the second satellites during the second time period, and construct a second dataset corresponding to the second time period based on the second traffic information, and determine the second distribution curve corresponding to the second dataset, wherein the second time period is the current time period; S306: Determine the channel capacity corresponding to the inter-satellite link, and broadcast the channel capacity, the first distribution curve, and the second distribution curve to the first satellite, where the inter-satellite link represents the communication link established between the first satellite and each of the second satellites; S308: Determine the transformation parameter between the first distribution curve corresponding to the second time period and the first distribution curve corresponding to the third time period, and use the transformation parameter and the second distribution curve to predict the third distribution curve corresponding to the third time period, where the third time period represents the next time period after the second time period; and S310: Select prediction points in the third distribution curve, and determine the load saturation of the first satellite in the third time period based on the prediction points and channel capacity. The prediction points include the traffic required for the first satellite to assist in forwarding data from each of the second satellites in the third time period, as well as the corresponding probability density.

[0024] Specifically, refer to Figure 1 and Figure 3 As shown, taking the first satellite 101 and the second satellites 201-202 as examples, the gateway station 40 first acquires data for each sampling period. The same first time period in The first traffic information required by the first satellite 101 to assist in forwarding data from the second satellites 201-202 Furthermore, based on the first traffic information, the gateway station 40... Building and each first period The corresponding first dataset Determine the relationship with each of the first datasets. The corresponding first distribution curve .in, Indicates the number of sampling periods. This indicates the quantity in the first time period. And within that, (Corresponding to step 302).

[0025] Then, the gateway station 40 obtains the second time period. The first satellite 101 assists in relaying the second traffic information required by the second satellites 201-202. Furthermore, gateway station 40, based on the second traffic information... Construction and the second phase The corresponding second dataset Determine the relationship with the second dataset. The corresponding second distribution curve The second period This refers to the current time period (corresponding to step 304).

[0026] Subsequently, gateway station 40 determined the inter-satellite link. Corresponding channel capacity and channel capacity First distribution curve and the second distribution curve Broadcast to Satellite 101. Inter-satellite link. This indicates the communication links established between the first satellite 101 and each of the second satellites 201-202 (corresponding to step 306).

[0027] Furthermore, the information from station 40 was confirmed to be related to the second time period. The corresponding first distribution curve and the third period The corresponding first distribution curve The transformation parameters between them. Using the transformation parameters and the second distribution curve. The forecast for the third time period is based on the information gate station 40. The corresponding third distribution curve The third period Indicates the second time period The next time period (corresponding to step 308).

[0028] Finally, the signal station 40 is on the third distribution curve. Prediction point A is selected from the data. Furthermore, based on prediction point A and channel capacity... The customs station has determined the third time period. The load saturation of the first satellite 101. Prediction point A includes the third time period. The first satellite 101 within the system assists in relaying the data required by the various second satellites 201-202. and the corresponding probability density (Corresponding to step 310).

[0029] Therefore, the method provided in this application, through the second time period The corresponding first distribution curve and the third period The corresponding first distribution curve The conversion parameters obtained between the two periods, and the conversion between the two periods. The corresponding second distribution curve Predicting the third period The corresponding third distribution curve Therefore, based on the third distribution curve... The flow contained in the extracted prediction point A and the corresponding probability density Information, gateway station 40 can predict that the first satellite 101 will be in the third period. The load saturation within the system is monitored to allow for coordinated management of the task of the first satellite 101 assisting in relaying data from the various second satellites 201-202. This, in turn, avoids [problems] starting from the second time period. By the third period During the handover process, the second satellite 201~202 concentrates on forwarding data to the first satellite 101, which causes load saturation and improves the quality of satellite-to-ground communication services.

[0030] As described in the background section, low-Earth orbit (LEO) satellites achieve continuous coverage and communication services by constructing satellite constellations. However, the high-speed movement of LEO satellites causes their coverage areas to continuously and dynamically switch, and the connections between LEO satellites and ground terminals, as well as inter-satellite links, change frequently, resulting in a constantly evolving network topology. In actual operation, the communication capacity of LEO satellites is physically limited; the bandwidth and processing power of onboard relay equipment cannot be infinitely expanded, especially in areas with high data relay demand, which may exceed the processing capacity of the corresponding LEO satellite. That is, the LEO satellite cannot independently handle all data relay tasks. This leads to localized congestion in the satellite network, causing data loss, increased transmission latency, and other problems, severely impacting the quality of communication services. Therefore, it is necessary to add satellites to assist LEO satellites in relaying data, sharing the data relay tasks exceeding the LEO satellite's processing capacity. However, due to the lack of prediction of the load saturation of satellites assisting in data relay in the next time period, it is possible that various LEO satellites may simultaneously relay data to a particular satellite, causing congestion and affecting satellite communication quality.

[0031] To address the lack of prediction capabilities for the load saturation of first satellites assisting in the relay of data from second satellites, this application provides a load saturation prediction method for inter-satellite links. A gateway station obtains a transformation parameter between a first distribution curve corresponding to a second time period and a first distribution curve corresponding to a third time period, based on a pre-determined first distribution curve. Further, the gateway station uses the transformation parameter to transform the second distribution curve corresponding to the second time period, predicting a third distribution curve corresponding to the third time period. Thus, based on the traffic and corresponding probability density information contained in the prediction points extracted from the third distribution curve, the gateway station can predict the load saturation of the first satellite in the third time period, enabling comprehensive management of the task of the first satellite assisting in the relay of data from various second satellites. This solves the technical problem in the prior art of lacking the ability to predict the load saturation of satellites assisting in data relay, which affects communication quality.

[0032] Optionally, the operation of selecting prediction points in the third distribution curve and determining the load saturation of the first satellite in the third time period based on the prediction points and channel capacity includes: randomly sampling prediction points in the third distribution curve; obtaining the third traffic information and corresponding probability density required for the first satellite to assist in forwarding data from each of the second satellites in the third time period based on the prediction points; calculating the traffic rate of the first satellite in the third time period based on the third traffic information and channel capacity; and determining the load saturation of the first satellite in the third time period based on the traffic rate and probability density.

[0033] Specifically, firstly, using a random sampling method, the signal station 40 in the third time period The corresponding third distribution curve Prediction point A is extracted from the data.

[0034] Then, based on the x and y coordinates of the predicted point A, gateway station 40 obtains the third time period. The first satellite 101 assists in relaying data from the second satellites 201-202, requiring the bandwidth of this data. With the corresponding probability density .

[0035] Furthermore, the gateway station 40, based on each equal probability density... and probability density The corresponding third time period is obtained. The bandwidth required for the first satellite 101 to assist in relaying data from the second satellite 201 and the third period The bandwidth required for the first satellite 101 to assist in relaying data from the second satellite 202 .

[0036] Furthermore, calculate the third time period. The flow rate of the first satellite 101 The formula is as follows: .

[0037] in, The third period The flow rate of the first satellite 101, in bps. The third period The weight corresponding to the traffic required for the first satellite 101 to assist in forwarding data from the second satellite 201. The third period The first satellite 101 assists in relaying the data required by the second satellite 201. Inter-satellite link between satellite 101 and satellite 201 The corresponding channel capacity. The third period The weight corresponding to the traffic required for the first satellite 101 to assist in forwarding data from the second satellite 202. The third period The first satellite 101 assists in relaying the data required by the second satellite 202. Inter-satellite link between satellite 101 and satellite 202 The corresponding channel capacity.

[0038] Furthermore, due to the inter-satellite links between the first satellite 101 and each of the second satellites 201-202... Since it remains unchanged, inter-satellite links can be configured. Corresponding channel capacity Second period and the third period It is consistent. That is, in calculating the third time period... The flow rate of the first satellite 101 At that time, the second time period will still be used. Intrasatellite Links Corresponding channel capacity .

[0039] Finally, based on the flow rate of the first satellite 101 With the corresponding probability density It was determined to be in the third time period. The load saturation of the first satellite 101 in the country.

[0040] Optionally, the third distribution curve prediction module includes: a transformation submodule, used to scale and translate the second distribution curve using transformation parameters to generate a third distribution curve corresponding to the third time period.

[0041] Specifically, based on the scaling parameters Translation parameters Second period The corresponding second distribution curve By scaling and panning, the transformation is generated and compared with the third time period. The corresponding third distribution curve .

[0042] Based on the properties of the normal distribution, the third distribution curve can be calculated. random variables The formula is: .

[0043] in, The third distribution curve A random variable. The second distribution curve A random variable. In order to the second period The corresponding first distribution curve and the third period The corresponding first distribution curve Scaling parameters between. In order to the second period The corresponding first distribution curve and the third period The corresponding first distribution curve The translation parameters between them. To be in the third period The corresponding first distribution curve The second standard deviation. In order to the second period The corresponding first distribution curve The first standard deviation. To be in the third period The corresponding first distribution curve The second mean. In order to the second period The corresponding first distribution curve The first mean.

[0044] Thus, through the second period The corresponding first distribution curve and the third period The corresponding first distribution curve The conversion parameters between them can achieve the transformation of the second distribution curve. The transformation. Furthermore, it is possible to generate a third distribution curve. .

[0045] Optionally, the operation of determining the transformation parameters between the first distribution curve corresponding to the second time period and the first distribution curve corresponding to the third time period includes: determining the corresponding first mean and first standard deviation based on the first distribution curve corresponding to the second time period; determining the corresponding second mean and second standard deviation based on the first distribution curve corresponding to the third time period; and calculating the transformation parameters between the first distribution curve corresponding to the second time period and the first distribution curve corresponding to the third time period based on the first mean, the first standard deviation, the second mean, and the second standard deviation.

[0046] Specifically, Figure 4 A comparison diagram of the first distribution curve corresponding to the second time period and the first distribution curve corresponding to the third time period, according to Embodiment 1 of this disclosure, is shown.

[0047] refer to Figure 4 As shown, firstly, the first distribution curve is broadcast. The information was obtained from the second time period at the customs station. The corresponding first distribution curve And calculate the corresponding first mean. Compared with the first standard deviation .in, .

[0048] Furthermore, the information was obtained from the third time period by the gateway station 40. The corresponding first distribution curve And calculate the corresponding second mean. Compared with the second standard deviation .

[0049] Furthermore, let's consider the second time period. The corresponding first distribution curve for , and the third period The corresponding first distribution curve for Based on the property that a normal distribution remains normal after a linear transformation, and the properties of variance and mean in a normal distribution, we can obtain: ; .

[0050] in, In order to the second period The corresponding first distribution curve and the third period The corresponding first distribution curve Scaling parameters between. In order to the second period The corresponding first distribution curve The first standard deviation. To be in the third period The corresponding first distribution curve The second standard deviation. In order to the second period The corresponding first distribution curve and the third period The corresponding first distribution curve The translation parameters between them. In order to the second period The corresponding first distribution curve The first mean. To be in the third period The corresponding first distribution curve The second mean.

[0051] In other words, compared with the second period The corresponding first distribution curve and the third period The corresponding first distribution curve The conversion relationship between them is as follows: .

[0052] in, In order to the second period The corresponding first distribution curve A random variable. To be in the third period The corresponding first distribution curve random variable. In order to the second period The corresponding first distribution curve and the third period The corresponding first distribution curve Scaling parameters between. In order to the second period The corresponding first distribution curve and the third period The corresponding first distribution curve The translation parameters between them.

[0053] Therefore, it is possible to determine the second time period. The corresponding first distribution curve and the third period The corresponding first distribution curve Scaling parameters between Translation parameters That is, compared with the second period. The corresponding first distribution curve and the third period The corresponding first distribution curve The deformation parameters between them.

[0054] Optionally, the operation of determining the channel capacity corresponding to the inter-satellite link includes: determining the channel capacity using Shannon's formula based on the channel bandwidth and signal-to-noise ratio corresponding to the inter-satellite link.

[0055] Specifically, gateway station 40, based on inter-satellite links Corresponding channel bandwidth and signal-to-noise ratio Calculate inter-satellite links Corresponding channel capacity The formula is as follows: .

[0056] in, Inter-satellite links The corresponding channel capacity. Inter-satellite links Corresponding channel bandwidth . Inter-satellite links Corresponding signal-to-noise ratio .

[0057] Optionally, the operation of constructing a second dataset corresponding to the second time period based on the second traffic information and determining a second distribution curve corresponding to the second dataset includes: dividing the second time period into multiple sub-time periods, obtaining the second traffic information required for the first satellite to assist in forwarding data from each second satellite in each sub-time period; constructing a second dataset based on the second traffic information; and fitting the second dataset to generate a second distribution curve corresponding to the second time period.

[0058] Specifically, the second period Divided into multiple sub-time periods Then, gateway station 40 collected and summarized data for each sub-time period. The first satellite 101 assists in relaying the second traffic information required by the second satellites 201-202. Construction and the second phase The corresponding second dataset .in, , This indicates the number of sub-time periods. See Tables 1 and 2 below for details.

[0059] Table 1 shows the second time period. Each sub-period The first satellite 101 assists in relaying the second traffic information required by the second satellites 201-202. .

[0060] Table 1

[0061] Referring to Table 1, in the second time period sub-period Inside, the first satellite 101 assists in relaying the second data from the second satellite 201, requiring the second traffic information. In the second period sub-period Inside, the first satellite 101 assists in relaying the second data from the second satellite 202, requiring the second traffic information. .

[0062] Second period sub-period Inside, the first satellite 101 assists in relaying the second data from the second satellite 201, requiring the second traffic information. In the second period sub-period Inside, the first satellite 101 assists in relaying the second data from the second satellite 202, requiring the second traffic information. .

[0063] And so on.

[0064] Second period sub-period Inside, the first satellite 101 assists in relaying the second data from the second satellite 201, requiring the second traffic information. In the second period sub-period Inside, the first satellite 101 assists in relaying the second data from the second satellite 202, requiring the second traffic information. .

[0065] Table 2 shows the second time period. The corresponding second dataset .

[0066] Table 2

[0067] Referring to Table 2, in the second time period Within, the first satellite 101 assists in relaying the second dataset corresponding to the data from the second satellite 201. In the second period Within, the first satellite 101 assists in relaying the second dataset corresponding to the data from the second satellite 202. .

[0068] Figure 5A A schematic diagram of the second distribution curve according to this embodiment is shown. (Reference) Figure 5A As shown, fitting each of the second datasets Generate the corresponding second distribution curve Among them, the second distribution curve All are log-normal distribution curves.

[0069] Optionally, the operation of constructing a first dataset corresponding to each first time period based on the first traffic information and determining a first distribution curve corresponding to each first dataset includes: constructing a first dataset corresponding to each first time period based on the first traffic information required for the first satellite to assist in forwarding data from the second satellite in each first time period of each sampling period; and fitting the first dataset to generate a first distribution curve corresponding to each first time period.

[0070] Specifically, the 40 gateway stations collected and summarized data from each sampling period. The same first time period in The first satellite 101 assists in relaying the second traffic information required by the data from the various second satellites 201-202. Build and connect with each first period The corresponding second dataset .in, Indicates the number of sampling periods. This indicates the quantity in the first time period. And within that, The details are shown in Tables 3 to 6 below.

[0071] Table 3 shows the sampling period. Each of the first periods The first traffic information required by the first satellite 101 to assist in forwarding data from the second satellites 201-202 .

[0072] Table 3

[0073] Referring to Table 3, during the sampling period The first period Inside, the first satellite 101 assists in relaying the first traffic information required by the second satellite 201. During the sampling period The first period Inside, the first satellite 101 assists in relaying the first traffic information required by the second satellite 202. .

[0074] During the sampling period The first period Inside, the first satellite 101 assists in relaying the first traffic information required by the second satellite 201. During the sampling period The first period Inside, the first satellite 101 assists in relaying the first traffic information required by the second satellite 202. .

[0075] And so on.

[0076] During the sampling period The first period Inside, the first satellite 101 assists in relaying the first traffic information required by the second satellite 201. During the sampling period The first period Inside, the first satellite 101 assists in relaying the first traffic information required by the second satellite 202. .

[0077] Table 4 shows the sampling period. Each of the first periods The first traffic information required by the first satellite 101 to assist in forwarding data from the second satellites 201-202 .

[0078] Table 4

[0079] Referring to Table 4, during the sampling period The first period Inside, the first satellite 101 assists in relaying the first traffic information required by the second satellite 201. During the sampling period The first period Inside, the first satellite 101 assists in relaying the first traffic information required by the second satellite 202. .

[0080] During the sampling period The first period Inside, the first satellite 101 assists in relaying the first traffic information required by the second satellite 201. During the sampling period The first period Inside, the first satellite 101 assists in relaying the first traffic information required by the second satellite 202. .

[0081] And so on.

[0082] During the sampling period The first period Inside, the first satellite 101 assists in relaying the first traffic information required by the second satellite 201. During the sampling period The first period Inside, the first satellite 101 assists in relaying the first traffic information required by the second satellite 202. .

[0083] Table 5 shows the sampling period. Each of the first periods The first traffic information required by the first satellite 101 to assist in forwarding data from the second satellites 201-202 .

[0084] Table 5

[0085] Referring to Table 5, during the sampling period The first period Inside, the first satellite 101 assists in relaying the first traffic information required by the second satellite 201. During the sampling period The first period Inside, the first satellite 101 assists in relaying the first traffic information required by the second satellite 202. .

[0086] During the sampling period The first period Inside, the first satellite 101 assists in relaying the first traffic information required by the second satellite 201. During the sampling period The first period Inside, the first satellite 101 assists in relaying the first traffic information required by the second satellite 202. .

[0087] And so on.

[0088] During the sampling period The first period Inside, the first satellite 101 assists in relaying the first traffic information required by the second satellite 201. During the sampling period The first period Inside, the first satellite 101 assists in relaying the first traffic information required by the second satellite 202. .

[0089] Table 6 shows the various first time periods. The first satellite 101 assists in relaying the first dataset corresponding to the data from each of the second satellites 201-202. .

[0090] Table 6

[0091] Based on Tables 3-5 above, the information from gateway 40 can be found in Table 6. Referring to Table 6, in the first time period... Within, the first satellite 101 assists in relaying the first dataset corresponding to the data from the second satellite 201. In the first period Within, the first satellite 101 assists in relaying the first dataset corresponding to the data from the second satellite 202. .

[0092] First period Within, the first satellite 101 assists in relaying the first dataset corresponding to the data from the second satellite 201. In the first period Within, the first satellite 101 assists in relaying the first dataset corresponding to the data from the second satellite 202. .

[0093] And so on.

[0094] First period Within, the first satellite 101 assists in relaying the first dataset corresponding to the data from the second satellite 201. In the first period Within, the first satellite 101 assists in relaying the first dataset corresponding to the data from the second satellite 202. .

[0095] Figure 5B A schematic diagram of the first distribution curve according to this embodiment is shown. (Reference) Figure 5B As shown, fitting each of the first datasets Generate the corresponding first distribution curve Among them, the first distribution curve All are log-normal distribution curves.

[0096] Therefore, according to the first aspect of this embodiment, by using the transformation parameters obtained from the first distribution curve corresponding to the second time period and the first distribution curve corresponding to the third time period, the second distribution curve corresponding to the second time period is transformed, and the third distribution curve corresponding to the third time period is predicted. Thus, based on the traffic and corresponding probability density information contained in the prediction points extracted from the third distribution curve, the gateway station can predict the load saturation of the first satellite in the third time period, so as to coordinate the task of the first satellite assisting in forwarding data from various second satellites. Furthermore, it can avoid congestion caused by the second satellites concentrating on forwarding data to the first satellite during the handover from the second time period to the third time period, thereby improving the quality of satellite-to-ground communication services.

[0097] In addition, refer to Figure 1 As shown, according to a second aspect of this embodiment, a storage medium is provided. The storage medium includes a stored program, wherein, when the program is executed, a processor performs any of the methods described above.

[0098] Therefore, according to this embodiment, by using the transformation parameters obtained from the first distribution curve corresponding to the second time period and the first distribution curve corresponding to the third time period, the second distribution curve corresponding to the second time period is transformed, and the third distribution curve corresponding to the third time period is predicted. Thus, based on the traffic and corresponding probability density information contained in the prediction points extracted from the third distribution curve, the gateway station can predict the load saturation of the first satellite in the third time period, so as to coordinate the task of the first satellite assisting in forwarding data from various second satellites. Furthermore, it can avoid congestion caused by the second satellites concentrating on forwarding data to the first satellite during the handover from the second time period to the third time period, thereby improving the quality of satellite-to-ground communication services.

[0099] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that the present invention is not limited to the described order of actions, because according to the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to the present invention.

[0100] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0101] Example 2 Figure 6 A load saturation prediction device 600 for inter-satellite links according to this embodiment is shown, which corresponds to the method described according to the first aspect of Embodiment 1. Reference Figure 6As shown, the device 600 includes: a first distribution curve determination module 610, used to acquire first traffic information required for a first satellite to assist in forwarding data from each second satellite within the same first time period in each sampling period, and to construct a first dataset corresponding to each first time period based on the first traffic information, and to determine a first distribution curve corresponding to each first dataset; a second distribution curve determination module 620, used to acquire second traffic information required for the first satellite to assist in forwarding data from each second satellite within a second time period, and to construct a second dataset corresponding to the second time period based on the second traffic information, and to determine a second distribution curve corresponding to the second dataset, wherein the second time period is the current time period; and an information broadcasting module 630, used to determine the channel capacity corresponding to the inter-satellite link, and to broadcast the channel capacity, the first distribution curve, and the first distribution curve. The second distribution curve is broadcast to the first satellite, wherein the inter-satellite link represents the communication link established between the first satellite and each of the second satellites; the third distribution curve prediction module 640 is used to determine the conversion parameter between the first distribution curve corresponding to the second time period and the first distribution curve corresponding to the third time period, and to predict the third distribution curve corresponding to the third time period using the conversion parameter and the second distribution curve, wherein the third time period represents the next time period after the second time period; and the prediction module 650 is used to select a prediction point in the third distribution curve, and to determine the load saturation of the first satellite in the third time period based on the prediction point and the channel capacity, wherein the prediction point includes the traffic required for the first satellite to assist in forwarding the data of each of the second satellites in the third time period, and the corresponding probability density.

[0102] Optionally, the prediction module 650 includes: a prediction point extraction submodule, used to extract prediction points from the third distribution curve through random sampling; a traffic information acquisition submodule, used to acquire the third traffic information and corresponding probability density required for the first satellite to assist in forwarding data from each of the second satellites in the third time period based on the prediction points; a traffic rate calculation submodule, used to calculate the traffic rate of the first satellite in the third time period based on the third traffic information and channel capacity; and a load saturation determination submodule, used to determine the load saturation of the first satellite in the third time period based on the traffic rate and probability density.

[0103] Optionally, the third distribution curve prediction module 640 includes: a transformation submodule, used to scale and translate the second distribution curve using transformation parameters to generate a third distribution curve corresponding to the third time period.

[0104] Optionally, the third distribution curve prediction module 640 includes: a first calculation submodule, used to determine the corresponding first mean and first standard deviation based on the first distribution curve corresponding to the second time period; a second calculation submodule, used to determine the corresponding second mean and second standard deviation based on the first distribution curve corresponding to the third time period; and a transformation parameter calculation submodule, used to calculate the transformation parameter between the first distribution curve corresponding to the second time period and the first distribution curve corresponding to the third time period based on the first mean, the first standard deviation, the second mean, and the second standard deviation.

[0105] Therefore, according to this embodiment, by using the transformation parameters obtained from the first distribution curve corresponding to the second time period and the first distribution curve corresponding to the third time period, the second distribution curve corresponding to the second time period is transformed, and the third distribution curve corresponding to the third time period is predicted. Thus, based on the traffic and corresponding probability density information contained in the prediction points extracted from the third distribution curve, the gateway station can predict the load saturation of the first satellite in the third time period, so as to coordinate the task of the first satellite assisting in forwarding data from various second satellites. Furthermore, it can avoid congestion caused by the second satellites concentrating on forwarding data to the first satellite during the handover from the second time period to the third time period, thereby improving the quality of satellite-to-ground communication services.

[0106] Example 3 Figure 7 A load saturation prediction device 700 for inter-satellite links according to a first aspect of this embodiment is shown, which corresponds to the method described according to the first aspect of Embodiment 1. Reference Figure 7As shown, the device 700 includes: a processor 710; and a memory 720 connected to the processor 710, used to provide the processor 710 with instructions to process the following steps: acquiring first traffic information required for a first satellite to assist in forwarding data from various second satellites within the same first time period in each sampling period, constructing a first dataset corresponding to each first time period based on the first traffic information, and determining a first distribution curve corresponding to each first dataset; acquiring second traffic information required for a first satellite to assist in forwarding data from various second satellites within a second time period, constructing a second dataset corresponding to the second time period based on the second traffic information, and determining a second distribution curve corresponding to the second dataset, wherein the second time period is the current time period; and determining an inter-satellite link. The system determines the channel capacity corresponding to the path and broadcasts the channel capacity, the first distribution curve, and the second distribution curve to the first satellite, where the inter-satellite link represents the communication link established between the first satellite and each of the second satellites; it determines the conversion parameter between the first distribution curve corresponding to the second time period and the first distribution curve corresponding to the third time period, and uses the conversion parameter and the second distribution curve to predict the third distribution curve corresponding to the third time period, where the third time period represents the next time period after the second time period; it selects prediction points in the third distribution curve, and determines the load saturation of the first satellite in the third time period based on the prediction points and the channel capacity, where the prediction points include the traffic required for the first satellite to assist in forwarding data from each of the second satellites in the third time period, and the corresponding probability density.

[0107] Optionally, the operation of selecting prediction points in the third distribution curve and determining the load saturation of the first satellite in the third time period based on the prediction points and channel capacity includes: randomly sampling prediction points in the third distribution curve; obtaining the third traffic information and corresponding probability density required for the first satellite to assist in forwarding data from each of the second satellites in the third time period based on the prediction points; calculating the traffic rate of the first satellite in the third time period based on the third traffic information and channel capacity; and determining the load saturation of the first satellite in the third time period based on the traffic rate and probability density.

[0108] Optionally, the operation of predicting the third distribution curve corresponding to the third time period using the transformation parameters and the second distribution curve includes: scaling and shifting the second distribution curve using the transformation parameters to generate the third distribution curve corresponding to the third time period.

[0109] Optionally, the operation of determining the transformation parameters between the first distribution curve corresponding to the second time period and the first distribution curve corresponding to the third time period includes: determining the corresponding first mean and first standard deviation based on the first distribution curve corresponding to the second time period; determining the corresponding second mean and second standard deviation based on the first distribution curve corresponding to the third time period; and calculating the transformation parameters between the first distribution curve corresponding to the second time period and the first distribution curve corresponding to the third time period based on the first mean, the first standard deviation, the second mean, and the second standard deviation.

[0110] Therefore, according to this embodiment, by using the transformation parameters obtained from the first distribution curve corresponding to the second time period and the first distribution curve corresponding to the third time period, the second distribution curve corresponding to the second time period is transformed, and the third distribution curve corresponding to the third time period is predicted. Thus, based on the traffic and corresponding probability density information contained in the prediction points extracted from the third distribution curve, the gateway station can predict the load saturation of the first satellite in the third time period, so as to coordinate the task of the first satellite assisting in forwarding data from various second satellites. Furthermore, it can avoid congestion caused by the second satellites concentrating on forwarding data to the first satellite during the handover from the second time period to the third time period, thereby improving the quality of satellite-to-ground communication services.

[0111] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0112] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0113] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0114] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0115] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0116] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0117] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for predicting load saturation in inter-satellite links, applied to gateway stations, characterized in that, include: Obtain the first traffic information required for the first satellite to assist in forwarding data from each second satellite within the same first time period in each sampling period, and construct a first dataset corresponding to each first time period based on the first traffic information, and determine the first distribution curve corresponding to each first dataset; The second traffic information required for the first satellite to assist in forwarding data from each of the second satellites during the second time period is obtained, and a second dataset corresponding to the second time period is constructed based on the second traffic information. A second distribution curve corresponding to the second dataset is determined, wherein the second time period is the current time period. The channel capacity corresponding to the inter-satellite link is determined, and the channel capacity, the first distribution curve, and the second distribution curve are broadcast to the first satellite, wherein the inter-satellite link refers to the communication link established between the first satellite and each of the second satellites; Determine the transformation parameter between the first distribution curve corresponding to the second time period and the first distribution curve corresponding to the third time period, and use the transformation parameter and the second distribution curve to predict the third distribution curve corresponding to the third time period, wherein the third time period represents the next time period after the second time period; as well as A prediction point is selected in the third distribution curve, and the load saturation of the first satellite in the third time period is determined based on the prediction point and the channel capacity. The prediction point includes the traffic required for the first satellite to assist in forwarding the data of each of the second satellites in the third time period, and the corresponding probability density.

2. The method according to claim 1, characterized in that, The operation of selecting a prediction point in the third distribution curve and determining the load saturation of the first satellite in the third time period based on the prediction point and the channel capacity includes: The prediction points are extracted from the third distribution curve by random sampling. Based on the predicted point, obtain the third traffic information and corresponding probability density required for the first satellite to assist in forwarding data from each of the second satellites during the third time period; Based on the third traffic information and the channel capacity, calculate the traffic rate of the first satellite during the third time period; and The load saturation of the first satellite during the third time period is determined based on the flow rate and the probability density.

3. The method according to claim 1, characterized in that, The operation of predicting the third distribution curve corresponding to the third time period using the transformation parameters and the second distribution curve includes: The second distribution curve is scaled and shifted using the transformation parameters to generate a third distribution curve corresponding to the third time period.

4. The method according to claim 1, characterized in that, The operation of determining the transformation parameters between the first distribution curve corresponding to the second time period and the first distribution curve corresponding to the third time period includes: Based on the first distribution curve corresponding to the second time period, determine the corresponding first mean and first standard deviation; Based on the first distribution curve corresponding to the third time period, determine the corresponding second mean and second standard deviation; and Based on the first mean, the first standard deviation, the second mean, and the second standard deviation, calculate the transformation parameter between the first distribution curve corresponding to the second time period and the first distribution curve corresponding to the third time period.

5. A storage medium, characterized in that, The storage medium includes a stored program, wherein, when the program is executed, the method described in any one of claims 1 to 4 is performed by a processor.

6. A load saturation prediction device for inter-satellite links, characterized in that, include: The first distribution curve determination module is used to obtain the first traffic information required for the first satellite to assist in forwarding the data of each second satellite in the same first time period in each sampling period, and to construct a first dataset corresponding to each first time period based on the first traffic information, and to determine the first distribution curve corresponding to each first dataset. The second distribution curve determination module is used to obtain the second traffic information required for the first satellite to assist in forwarding the data of each second satellite during the second time period, and to construct a second dataset corresponding to the second time period based on the second traffic information, and to determine the second distribution curve corresponding to the second dataset, wherein the second time period is the current time period; The information broadcasting module is used to determine the channel capacity corresponding to the inter-satellite link and broadcast the channel capacity, the first distribution curve and the second distribution curve to the first satellite, wherein the inter-satellite link refers to the communication link established between the first satellite and each of the second satellites; The third distribution curve prediction module is used to determine the transformation parameter between the first distribution curve corresponding to the second time period and the first distribution curve corresponding to the third time period, and to predict the third distribution curve corresponding to the third time period using the transformation parameter and the second distribution curve, wherein the third time period represents the next time period after the second time period; as well as The prediction module is used to select prediction points in the third distribution curve and determine the load saturation of the first satellite in the third time period based on the prediction points and the channel capacity, wherein the prediction points include the traffic required for the first satellite to assist in forwarding data from each of the second satellites in the third time period, and the corresponding probability density.

7. The apparatus according to claim 6, characterized in that, The prediction module includes: The prediction point extraction submodule is used to extract the prediction points from the third distribution curve by random sampling. The traffic information acquisition submodule is used to acquire, based on the prediction point, the third traffic information and the corresponding probability density required for the first satellite to assist in forwarding the data of each of the second satellites during the third time period; A flow rate calculation submodule is used to calculate the flow rate of the first satellite during the third time period based on the third flow information and the channel capacity; and The load saturation determination submodule is used to determine the load saturation of the first satellite during the third time period based on the flow rate and the probability density.

8. The apparatus according to claim 6, characterized in that, The third distribution curve prediction module includes: The transformation submodule is used to scale and translate the second distribution curve using the transformation parameters to generate a third distribution curve corresponding to the third time period.

9. The apparatus according to claim 6, characterized in that, The third distribution curve prediction module includes: The first calculation submodule is used to determine the corresponding first mean and first standard deviation based on the first distribution curve corresponding to the second time period; The second calculation submodule is used to determine the corresponding second mean and second standard deviation based on the first distribution curve corresponding to the third time period; and The transformation parameter calculation submodule is used to calculate the transformation parameter between the first distribution curve corresponding to the second time period and the first distribution curve corresponding to the third time period based on the first mean, the first standard deviation, the second mean, and the second standard deviation.

10. A load saturation prediction device for inter-satellite links, characterized in that, include: processor; as well as A memory, connected to the processor, for providing the processor with instructions to perform the following processing steps: Obtain the first traffic information required for the first satellite to assist in forwarding data from each second satellite within the same first time period in each sampling period, and construct a first dataset corresponding to each first time period based on the first traffic information, and determine the first distribution curve corresponding to each first dataset; The second traffic information required for the first satellite to assist in forwarding data from each of the second satellites during the second time period is obtained, and a second dataset corresponding to the second time period is constructed based on the second traffic information. A second distribution curve corresponding to the second dataset is determined, wherein the second time period is the current time period. The channel capacity corresponding to the inter-satellite link is determined, and the channel capacity, the first distribution curve, and the second distribution curve are broadcast to the first satellite, wherein the inter-satellite link refers to the communication link established between the first satellite and each of the second satellites; Determine the transformation parameter between the first distribution curve corresponding to the second time period and the first distribution curve corresponding to the third time period, and use the transformation parameter and the second distribution curve to predict the third distribution curve corresponding to the third time period, wherein the third time period represents the next time period after the second time period; as well as A prediction point is selected in the third distribution curve, and the load saturation of the first satellite in the third time period is determined based on the prediction point and the channel capacity. The prediction point includes the traffic required for the first satellite to assist in forwarding the data of each of the second satellites in the third time period, and the corresponding probability density.

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