Ant colony-based low earth orbit satellite network routing optimization method, device and storage medium

Abstract

The embodiment of the present specification provides a kind of low-orbit satellite network routing optimization method, device and storage medium based on ant colony, method includes: forward ant reaches preset terminal point from preset starting point, forms path;After the forward ant reaches the terminal point, backward ant is transmitted along the path;For each node on the path except the starting point and the terminal point, the backward ant determines the link reliability coefficient of the path, transmission cost ratio and load evaluation factor;The backward ant determines the reward value of the path according to the link reliability coefficient, the transmission cost ratio and the load evaluation factor.The technical scheme provided in the present application is used to solve the problem of slow convergence speed and low efficiency of determining routing strategy in the prior art.

Description

Technical Field

[0001] This document relates to the field of low-Earth orbit (LEO) satellite network technology, and in particular to a method, apparatus, and storage medium for LEO satellite network routing optimization based on ant colony. Background Technology

[0002] With the advent of the 6G era, a globally integrated network will be an inevitable trend for future development, and satellite communication plays a crucial role in this regard.

[0003] Currently, most routing solutions for low-Earth orbit satellite networks can be categorized into centralized routing, distributed routing, and routing schemes based on artificial intelligence algorithms.

[0004] However, the above method has a slow convergence speed when determining the routing strategy, which increases the time for determining the path and thus reduces the efficiency of determining the routing strategy. Summary of the Invention

[0005] Based on the above analysis, this application aims to propose a method, apparatus, and storage medium for low-Earth orbit satellite network routing optimization based on ant colony, in order to solve the problems of slow convergence speed and low routing strategy determination.

[0006] Firstly, one or more embodiments of this specification provide a routing optimization method for low-Earth orbit satellite networks based on ant colonies, including:

[0007] The forward-moving ant travels from a preset starting point to a preset ending point, forming a path;

[0008] After the forward ant reaches the destination, the backward ant carries on the path.

[0009] For each node on the path other than the starting point and the ending point, the backward ant determines the link reliability coefficient, transmission overhead ratio and load evaluation factor of the path.

[0010] The backward ants determine the reward value of the path they traverse based on the link reliability coefficient, the transmission overhead ratio, and the load evaluation factor.

[0011] Furthermore, after sending the forward ant and before the forward ant reaches the destination, the method further includes:

[0012] The forward ant detects whether the length of the waiting queue of the current node where the forward ant is located exceeds a preset threshold;

[0013] When the length of the waiting queue of the current node exceeds a preset threshold, the forward ant sends a temporary ant to the previous node of the current node according to the path information.

[0014] Furthermore, after sending the temporary ant, the method further includes:

[0015] After the temporary ant reaches the previous node, it determines the link reliability coefficient, transmission overhead ratio, and load evaluation factor of the path it has taken.

[0016] The temporary ant determines the reward value of the path it traverses based on the link reliability coefficient, the transmission overhead ratio, and the load evaluation factor.

[0017] Furthermore, the forward-moving ant reaching the destination from a preset starting point includes:

[0018] After reaching each node on the path, the forward ant generates a random value;

[0019] The forward-moving ant compares the random value with the preset value;

[0020] When the random value is greater than the preset value, the forward ant randomly selects one of the adjacent nodes of the current node as its forward target;

[0021] When the random value is not greater than the preset value, the forward ant selects one of the neighboring nodes of the current node as its forward target based on the reward value of each path stored in the current node.

[0022] Furthermore, the backward ants determine the link reliability coefficient of the traversed path by including:

[0023] Collect the physical distance of the path, the transmission speed and delay time of the path;

[0024] The link reliability coefficient is determined based on the physical distance, the transmission speed, and the delay time.

[0025] Furthermore, the backward ant determines the transmission overhead ratio of the traversed path, including:

[0026] Collect the total number of data packets transmitted within a preset time period corresponding to the path and the total number of data packets successfully transmitted within the preset time period;

[0027] The transmission overhead ratio is determined based on the total number of data packets transmitted within the preset time period and the total number of data packets successfully transmitted within the preset time period.

[0028] Furthermore, the load evaluation factor for determining the path taken by the backward ants includes:

[0029] The load evaluation factor ζ(t) is calculated using the following formula:

[0030]

[0031] Among them, e, ω is a constant, t is the transmission time corresponding to the path, θ is a preset threshold, and QL is used to characterize the link occupancy rate corresponding to the path.

[0032] Further, the backward ants determine the reward value of the traversed path based on the link reliability coefficient, the transmission overhead ratio, and the load evaluation factor, including:

[0033] The feedback value corresponding to the path is determined based on the link reliability coefficient, the transmission overhead ratio, and the load evaluation factor.

[0034] Based on the feedback value, the reward value Q of the route is calculated using the following formula. t (i,j):

[0035]

[0036] Where i and j correspond to two adjacent nodes, λ and γ are constants, and Q′ t (i,j) is Q t (i,j) represents the old value before calculation. The backward ant performs action a at time t. t From the state S of the current node i i The state S of the neighboring node j j The obtained feedback value, Max t (j) is used to characterize state S j Based on the maximum reward value for the next state from the old Q-table, execute action a. t The backward ant moves from the current node i to the adjacent node j.

[0037] Secondly, embodiments of this application provide a method and apparatus for optimizing routing in low-Earth orbit satellite networks based on ant colonies, comprising: a first ant control module and a second ant control module;

[0038] The first ant control module is used to control the forward ants to reach the preset end point from the preset starting point, forming a path;

[0039] The second ant control module is used to control the backward ant to transmit along the path after the forward ant reaches the destination; for each node on the path except the starting point and the destination, control the backward ant to determine the link reliability coefficient, transmission overhead ratio and load evaluation factor of the path; and control the backward ant to determine the reward value of the path based on the link reliability coefficient, the transmission overhead ratio and the load evaluation factor.

[0040] Thirdly, embodiments of this application provide a storage medium for storing computer-executable instructions, which, when executed, implement the method described in any one of the first aspects.

[0041] Compared with the prior art, this application can achieve at least the following technical effects:

[0042] Based on the link reliability coefficient, transmission overhead ratio, and load evaluation factor, this application transforms the impact of the path on information transmission efficiency into data, thereby adding the impact of the path on information transmission efficiency into the ant colony's pheromone in numerical form, which in turn improves the convergence speed and the efficiency of determining the routing strategy. Attached Figure Description

[0043] To more clearly illustrate the technical solutions in one or more embodiments of this specification or in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0044] Figure 1 A schematic diagram of a satellite topology provided for one or more embodiments of this specification;

[0045] Figure 2 This is a flowchart illustrating a low-Earth orbit satellite network routing optimization method based on ant colonies, provided for one or more embodiments of this specification. Detailed Implementation

[0046] To enable those skilled in the art to better understand the technical solutions in one or more embodiments of this specification, the technical solutions in one or more embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this specification, and not all of the embodiments. Based on one or more embodiments of this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of this document.

[0047] In this embodiment of the application, the low-Earth orbit satellite topology is as follows: Figure 1 As shown, N ij (V i V jThe symbol () represents the logical address of the satellite, where i is the orbital number and j is the satellite number within its orbit. Dashed lines represent inter-orbit links, and solid lines represent intra-orbit inter-satellite links. Each satellite typically has two intra-orbit inter-satellite links and two inter-orbit inter-satellite links. In other words, satellites are nodes, and the connections between these nodes and links form paths. Determining the routing strategy is equivalent to selecting the optimal path.

[0048] Existing non-ant colony algorithms typically focus on the busyness of nodes, ignoring the varying busyness levels across different paths. Meanwhile, existing ant colony algorithms simply rely on the number of ants to establish a pheromone advantage on the target path, increasing the time required to determine the routing strategy.

[0049] To address the aforementioned problems, this application proposes a route optimization method for low-Earth orbit satellite networks based on ant colonies, such as... Figure 2 As shown, it includes the following steps:

[0050] Step 1: The forward-moving ants travel from the preset starting point to the preset ending point, forming a path.

[0051] In this embodiment, a path is first established by forward-moving ants. The preset starting point and ending point are nodes in a low-Earth orbit satellite network model.

[0052] In this embodiment, when forward ants choose a path, they typically select the path with the highest information transmission efficiency. However, forward ants need to move step by step, which can lead to the overall path's information transmission efficiency being suboptimal. For example, consider two paths: one is the starting point - A - B - C - ending point (5 nodes), where the information transmission time between adjacent nodes is 1 second; the other is the starting point - D - ending point. The information transmission time from the starting point to D is 2 seconds, while the transmission time from D to the ending point is 1 second. Clearly, the starting point - D - ending point path has higher information transmission efficiency. However, forward ants starting from the starting point might choose the starting point - A - B - C - ending point path because the starting point - A path is one second faster than the starting point - D path, resulting in the ant colony algorithm ultimately not selecting the path with the highest information transmission efficiency.

[0053] To overcome the aforementioned problems, after reaching each node on the path, the forward ant generates a random value. The forward ant compares the random value with a preset value. If the random value is greater than the preset value, the forward ant randomly selects one of the current node's neighboring nodes as its next target. If the random value is not greater than the preset value, the forward ant selects one of the current node's neighboring nodes as its next target based on the reward values ​​of each path stored at the current node. The random value can be calculated using a pseudo-random algorithm. This method allows the forward ant to explore new paths, thus avoiding the selection of the path with the highest information transmission efficiency.

[0054] Step 2: After the forward ant reaches the destination, the backward ant carries the data along the path.

[0055] In this embodiment, the forward ant automatically triggers the backward ant to start after reaching the destination. The backward ant will then travel from the destination to the starting point along the path formed by the forward ant.

[0056] Step 3: For each node on the path except the starting point and the ending point, the backward ants determine the link reliability coefficient, transmission overhead ratio and load evaluation factor of the path.

[0057] In this embodiment, the path taken by the backward ant is a link between two adjacent nodes. The link reliability coefficient, transmission overhead ratio, and load evaluation factor are all path-related data.

[0058] Specifically, the link reliability coefficient is the reliability coefficient of the link between node i and node j, where node i and node j are adjacent nodes. The transmission overhead ratio is the probability of successful data packet transmission on the path. The load evaluation factor is used to distinguish between congested paths and unused paths.

[0059] The calculation process for the link reliability coefficient is as follows: Collect the physical distance length of the path, the corresponding transmission speed, and the delay time; determine the link reliability coefficient based on the physical distance length, transmission speed, and delay time. The calculation formula is:

[0060]

[0061] F t (,j) is the reliability coefficient of the link between node i and node j, D(i,j) is the physical distance of the link, C is the transmission speed, and (,j) is the delay time for satellite node i to transmit data packets to satellite node j.

[0062] The transmission overhead ratio is calculated as follows: The total number of data packets transmitted and the total number of successfully transmitted data packets within a preset time period are collected for the corresponding path. Based on these two data packet transmission amounts, the transmission overhead ratio is determined. The calculation formula is:

[0063]

[0064] M t (i,j) represents the transmission cost ratio of the link between node i and node j, NA t (i,j) represents the total number of data packets transmitted by the link within time t, N success It represents the total number of data packets successfully transmitted at time t.

[0065] The formula for calculating the load evaluation factor is:

[0066]

[0067] Among them, e, ω is a constant, t is the transmission time corresponding to the path, θ is a preset threshold, and QL is used to characterize the link occupancy rate corresponding to the path. The value of ω is in the range [0,1]. QL < θ indicates that the path is not a congested path.

[0068] Step 4: The backward ants determine the reward value of the path based on the link reliability coefficient, transmission overhead ratio, and load evaluation factor.

[0069] In this embodiment of the application, in order to accelerate the convergence speed, a learning rate λ is introduced, specifically...

[0070] The feedback value corresponding to the path is determined based on the link reliability coefficient, the transmission overhead ratio, and the load evaluation factor.

[0071] The formula for calculating the feedback value is:

[0072]

[0073] Where R Max and R C Let θ be a constant, representing the positive feedback reward for successfully reaching the destination and the negative feedback penalty for failing to reach the destination, respectively. σ, Φ, and ζ represent the link reliability, transmission overhead ratio, and the weight of the load evaluation factor, respectively. QL < θ indicates that the path is not a congested path. Therefore, when QL < θ, the influence of the load evaluation factor is ignored, and σ + Φ = 1. In other cases, the influence of the load evaluation factor needs to be considered, and σ + Φ + ζ = 1.

[0074] Based on the feedback value, the reward value Q of the route is calculated using the following formula. t (i,j):

[0075]

[0076] Where i and j correspond to two adjacent nodes, λ and γ are constants, and Q′ t (i,j) is Q t (i,j) represents the old value before calculation. The backward ant performs action a at time t. t From the state S of the current node i i The state S of the neighboring node j j The obtained feedback value, Max t (j) is used to characterize state S j Based on the maximum reward value for the next state from the old Q-table, execute action a.t The backward ant moves from the current node i to the adjacent node j.

[0077] Preferably, to better bypass congested nodes, after step 2 and before step 3, the forward ant checks whether the waiting queue length of the current node where the forward ant is located exceeds a preset threshold. If the waiting queue length of the current node exceeds the preset threshold, the forward ant sends a temporary ant to the previous node of the current node based on the path information. The temporary ant then calculates the reward value of the path between the previous node and the current node. Specifically, after the temporary ant reaches the previous node, it determines the link reliability coefficient, transmission overhead ratio, and load evaluation factor of the path it has traversed; the temporary ant determines the reward value of the path based on the link reliability coefficient, transmission overhead ratio, and load evaluation factor. After calculating the reward value, the temporary ant automatically disappears, thus not affecting the information transmission efficiency of the previous node. In this way, the temporary ant informs subsequent forward ants through the reward value that the path between the previous node and the current node is congested, thereby achieving the goal of bypassing the congested node.

[0078] This application provides a method and apparatus for optimizing routing in low-Earth orbit satellite networks based on ant colonies, including: a first ant control module and a second ant control module;

[0079] The first ant control module is used to control the forward ants to reach the preset end point from the preset starting point, forming a path;

[0080] The second ant control module is used to control the backward ant to transmit along the path after the forward ant reaches the destination; for each node on the path except the starting point and the destination, control the backward ant to determine the link reliability coefficient, transmission overhead ratio and load evaluation factor of the path; and control the backward ant to determine the reward value of the path based on the link reliability coefficient, the transmission overhead ratio and the load evaluation factor.

[0081] This application provides a storage medium for storing computer-executable instructions, which, when executed, implement the methods described in any of the above embodiments.

[0082] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0083] In the 1930s, improvements to a technology could be clearly distinguished as either hardware improvements (e.g., improvements to the circuit structure of diodes, transistors, switches, etc.) or software improvements (improvements to the methodology). However, with technological advancements, many improvements to the methodology today can be considered direct improvements to the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved methodology into the hardware circuit. Therefore, it cannot be said that an improvement to the methodology cannot be implemented using a hardware physical module. For example, a Programmable Logic Device (PLD) (e.g., a Field Programmable Gate Array (FPGA)) is such an integrated circuit whose logic function is determined by the user programming the device. Designers can program a digital system themselves to "integrate" it onto a PLD, without needing chip manufacturers to design and manufacture dedicated integrated circuit chips. Furthermore, nowadays, instead of manually manufacturing integrated circuit chips, this programming is mostly implemented using "logic compiler" software. Similar to the software compiler used in program development, the original code before compilation must be written in a specific programming language, called a Hardware Description Language (HDL). There are many HDLs, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, and RHDL (Ruby Hardware Description Language). Currently, the most commonly used are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should understand that by simply performing some logic programming on the method flow using one of these hardware description languages ​​and programming it into an integrated circuit, the hardware circuit implementing the logical method flow can be easily obtained.

[0084] The controller can be implemented in any suitable manner. For example, it can take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicon Labs C8051F320. A memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art will also recognize that, in addition to implementing the controller in purely computer-readable program code form, the same functionality can be achieved by logically programming the method steps to make the controller take the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, such a controller can be considered a hardware component, and the means included therein for implementing various functions can also be considered as structures within the hardware component. Alternatively, the means for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0085] The systems, devices, modules, or units described in the above embodiments can be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, a computer can be, for example, a personal computer, laptop computer, cellular phone, camera phone, smartphone, personal digital assistant, media player, navigation device, email device, game console, tablet computer, wearable device, or any combination of these devices.

[0086] For ease of description, the above apparatus is described by dividing it into various functional units. Of course, when implementing the embodiments of this specification, the functions of each unit can be implemented in one or more software and / or hardware.

[0087] Those skilled in the art will understand that one or more embodiments of this specification can be provided as a method, system, or computer program product. Therefore, one or more embodiments of this specification may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this specification may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0088] This specification is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this specification. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0089] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0090] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0091] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0092] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0093] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0094] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0095] One or more embodiments of this specification can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a particular task or implement a particular abstract data type. One or more embodiments of this specification can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0096] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0097] The above description is merely an embodiment of this document and is not intended to limit the scope of this document. Various modifications and variations can be made to this document by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this document should be included within the scope of the claims of this document.

Claims

1. A routing optimization method for low-Earth orbit satellite networks based on ant colony management, characterized in that, include: The forward-moving ant travels from a preset starting point to a preset ending point, forming a path; After the forward ant reaches the destination, the backward ant carries on the path. For each node on the path other than the starting point and the ending point, the backward ant determines the link reliability coefficient, transmission overhead ratio and load evaluation factor of the path. The backward ants determine the reward value of the path they traverse based on the link reliability coefficient, the transmission overhead ratio, and the load evaluation factor. The method further includes, after sending the forward ant but before the forward ant reaches the destination: The forward ant detects whether the length of the waiting queue of the current node where the forward ant is located exceeds a preset threshold; When the length of the waiting queue of the current node exceeds a preset threshold, the forward ant sends a temporary ant to the previous node of the current node according to the path information. After sending the temporary ant, the method further includes: After the temporary ant reaches the previous node, it determines the link reliability coefficient, transmission overhead ratio, and load evaluation factor of the path it has taken. The temporary ant determines the reward value of the path it traverses based on the link reliability coefficient, the transmission overhead ratio, and the load evaluation factor.

2. The method according to claim 1, characterized in that, The forward-moving ant reaches the destination from the preset starting point, including: After reaching each node on the path, the forward ant generates a random value; The forward-moving ant compares the random value with the preset value; When the random value is greater than the preset value, the forward ant randomly selects one of the adjacent nodes of the current node as its forward target; When the random value is not greater than the preset value, the forward ant selects one of the neighboring nodes of the current node as its forward target based on the reward value of each path stored in the current node.

3. The method according to claim 1, characterized in that, The link reliability coefficient for determining the path traversed by the backward ants includes: Collect the physical distance of the path, the transmission speed and delay time of the path; The link reliability coefficient is determined based on the physical distance, the transmission speed, and the delay time.

4. The method according to claim 1, characterized in that, The transmission overhead ratio for determining the path traversed by the backward ants includes: Collect the total number of data packets transmitted within a preset time period corresponding to the path and the total number of data packets successfully transmitted within the preset time period; The transmission overhead ratio is determined based on the total number of data packets transmitted within the preset time period and the total number of data packets successfully transmitted within the preset time period.

5. The method according to claim 1, characterized in that, The load evaluation factors for determining the path taken by the backward ants include: Calculate the load evaluation factor using the following formula. : in, e, φ, ω All are constants. t The transmission time corresponding to the path taken. θ For the preset threshold, QL Used to characterize the link occupancy rate corresponding to the path taken.

6. The method according to claim 1, characterized in that, The backward ants determine the reward value of the traversed path based on the link reliability coefficient, the transmission overhead ratio, and the load evaluation factor, including: The feedback value corresponding to the path is determined based on the link reliability coefficient, the transmission overhead ratio, and the load evaluation factor. Based on the feedback value, the reward value of the route is calculated using the following formula. : in, i and j Each corresponds to two adjacent nodes. λ and γ All are constants. The old value before calculation For the backward ants in time t By performing actions a t From the current node i status S i to adjacent nodes j status S j The feedback value obtained, Used to characterize state S j Based on the maximum reward value for the next state from the old Q-table, execute the action. a t For backward ants from the current node i Move to adjacent node j .

7. A method and apparatus for optimizing routing in low-Earth orbit satellite networks based on ant colonies, characterized in that, include: First ant control module and second ant control module; The first ant control module is used to control the forward ants to reach the preset end point from the preset starting point, forming a path; The second ant control module is used to control the backward ant to transmit along the path after the forward ant reaches the destination; for each node on the path except the starting point and the destination, control the backward ant to determine the link reliability coefficient, transmission overhead ratio and load evaluation factor of the path; and control the backward ant to determine the reward value of the path based on the link reliability coefficient, the transmission overhead ratio and the load evaluation factor. The device further includes, after sending the forward ant but before the forward ant reaches its destination: The forward congestion detection and temporary distribution module is used by the forward ant to detect whether the waiting queue length of the current node where the forward ant is located exceeds a preset threshold. When the length of the waiting queue of the current node exceeds a preset threshold, the forward ant sends a temporary ant to the previous node of the current node according to the path information. After sending the temporary ants, the device further includes: The temporary feedback calculation module is used to determine the link reliability coefficient, transmission overhead ratio, and load evaluation factor of the path taken by the temporary ant after it reaches the previous node. The temporary ant determines the reward value of the path it traverses based on the link reliability coefficient, the transmission overhead ratio, and the load evaluation factor.

8. A storage medium, characterized in that, Used to store computer-executable instructions, which, when executed, implement the method of any one of claims 1-6.

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