Inter-satellite routing method and device based on genetic taboo hybrid algorithm

Abstract

The embodiment of the invention discloses an inter-satellite routing method and device based on a genetic taboo hybrid algorithm. A specific embodiment of the method comprises the following steps: initializing a satellite network environment, slicing according to time slices, and establishing a cross-orbit topological relation of satellites in each time slice; according to the cross-orbit topological relation of each satellite, transmission information of each satellite is determined, and the transmission information comprises routing path total delay, path data packet total loss rate and data total delivery rate; establishing a routing path utility function of each satellite according to the routing path total delay, the path data packet loss rate and the data delivery rate included in the transmission information; based on a genetic taboo hybrid algorithm, optimizing each routing path utility function to obtain an optimized inter-satellite routing table; and performing inter-satellite routing communication according to the optimized inter-satellite routing table. According to the embodiment, the genetic taboo hybrid algorithm is used for routing calculation, the general calculation service is met, the network load is balanced, and the network throughput is improved.

Description

Technical Field

[0001] The embodiments disclosed herein relate to the field of inter-satellite routing, and specifically to an inter-satellite routing method and apparatus based on a genetic tabu hybrid algorithm. Background Technology

[0002] Low Earth Orbit (LEO) satellite communication, as a crucial component of 6G, is attracting increasing attention from academia and industry to provide seamless and efficient network services. LEO satellites are expected to compensate for the lack of seamless coverage in terrestrial cell communications due to their lower cost, particularly in sparsely populated areas. Furthermore, LEO satellites offer significant advantages over geostationary Earth Orbit (GEO) satellites in terms of low latency and high throughput. LEO satellite communication is a vital component of 6G. In recent years, companies like SpaceX and OneWeb have been building their own LEO satellite constellations to provide global communication services with low latency and high throughput, especially in ocean, desert, air, and even space domains. However, existing routing strategies are primarily designed for terrestrial networks or small-scale satellite networks, and are therefore unsuitable for the future ultra-dense, highly dynamic, and large-scale LEO satellite constellations. Moreover, as LEO satellite networking matures, the services processed by ground terminals on satellites are diversifying, making the establishment of an inter-satellite routing system that integrates communication, sensing, and computing a worthwhile area of ​​discussion. Summary of the Invention

[0003] The summary portion of this disclosure is intended to provide a brief overview of the concepts, which will be described in detail in the detailed description portion. This summary portion is not intended to identify key or essential features of the claimed technical solutions, nor is it intended to limit the scope of the claimed technical solutions.

[0004] Some embodiments of this disclosure propose inter-satellite routing methods, apparatuses, electronic devices, and computer-readable media based on genetic tabu hybrid algorithms to address the technical problems mentioned in the background section above.

[0005] In a first aspect, some embodiments of this disclosure provide an inter-satellite routing method based on a genetic tabu hybrid algorithm. The method includes: initializing a satellite network environment, slicing it according to time slices, and establishing cross-orbit topology relationships for each satellite within each time slice, wherein the satellite network environment contains multiple satellites; determining transmission information for each satellite based on its cross-orbit topology relationships, wherein the transmission information includes: total routing path delay, total path packet loss rate, and total data delivery rate; establishing a routing path utility function for each satellite based on the total routing path delay, path packet loss rate, and data delivery rate included in the transmission information; optimizing the aforementioned routing path utility functions based on the genetic tabu hybrid algorithm to obtain an optimized inter-satellite routing table; and performing inter-satellite routing communication based on the optimized inter-satellite routing table.

[0006] Secondly, some embodiments of this disclosure provide an inter-satellite routing device based on a genetic tabu hybrid algorithm. The device includes: an initialization unit configured to initialize a satellite network environment, slice it according to time slices, and establish cross-orbit topology relationships for each satellite within each time slice, wherein the satellite network environment corresponds to a satellite network containing multiple satellites; a determination unit configured to determine the transmission information of each satellite based on the cross-orbit topology relationships of each satellite, wherein the transmission information includes: total routing path delay, total path packet loss rate, and total data delivery rate; an establishment unit configured to establish a routing path utility function for each satellite based on the total routing path delay, path packet loss rate, and data delivery rate included in the transmission information; an optimization unit configured to optimize the above-mentioned routing path utility functions based on the genetic tabu hybrid algorithm to obtain an optimized inter-satellite routing table; and a communication unit configured to perform inter-satellite routing communication based on the above-mentioned optimized inter-satellite routing table.

[0007] Thirdly, some embodiments of this disclosure provide an electronic device, including: one or more processors; and a storage device having one or more programs stored thereon, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any implementation of the first aspect above.

[0008] Fourthly, some embodiments of this disclosure provide a computer-readable medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the method described in any of the implementations of the first aspect above.

[0009] The various embodiments of this disclosure have the following beneficial effects: The inter-satellite routing method based on a genetic tabu search algorithm, as described in some embodiments of this disclosure, applies the genetic tabu search algorithm to inter-satellite routing in satellite networks. A set of inter-satellite routes is treated as a chromosome, and new individuals are obtained through crossover and mutation operations. Based on the genetic algorithm, a tabu search algorithm is introduced to further optimize the quality of the solution. The tabu search algorithm avoids repeated searches by recording already visited routing schemes and escapes local optima by setting tabu tables and amnesty rules. Using a genetic tabu search algorithm for routing calculation satisfies the needs of interconnected computing services, balances network load, and improves network throughput. Attached Figure Description

[0010] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and elements are not necessarily drawn to scale.

[0011] Figure 1 This is a flowchart of some embodiments of the inter-satellite routing method based on the genetic tabu hybrid algorithm according to this disclosure;

[0012] Figure 2 This is a schematic diagram of the cross-orbit topology of the various satellites;

[0013] Figure 3 This is a schematic diagram of a mutation operation scenario;

[0014] Figure 4 This is a schematic diagram of the structure of some embodiments of the inter-satellite routing device based on the genetic tabu hybrid algorithm according to the present disclosure;

[0015] Figure 5 This is a schematic diagram of the structure of an electronic device suitable for implementing some embodiments of the present disclosure. Detailed Implementation

[0016] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0017] It should also be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings. Unless otherwise specified, the embodiments and features described in this disclosure can be combined with each other.

[0018] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are used only to distinguish different devices, modules or units, and are not used to limit the order of functions performed by these devices, modules or units or their interdependencies.

[0019] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0020] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

[0021] This disclosure will now be described in detail with reference to the accompanying drawings and embodiments.

[0022] Figure 1 This is a flowchart 100 of some embodiments of the inter-satellite routing method based on the genetic tabu mixing algorithm of this disclosure. The inter-satellite routing method based on the genetic tabu mixing algorithm includes the following steps:

[0023] Step 101: Initialize the satellite network environment, slice it according to time slices, and establish the cross-orbit topology relationship of each satellite in each time slice.

[0024] In some embodiments, the execution entity (e.g., a computing device) of the inter-satellite routing method based on the genetic tabu mixing algorithm can initialize the satellite network environment, slice it according to time slices, and establish the cross-orbit topology relationships of each satellite within each time slice. The satellite network environment corresponds to a satellite network containing multiple satellites. Each satellite contains four laser communication terminals. The satellite network environment is detected and sliced ​​according to time slices, each time slice being one minute. By default, the topology is static within each time slice. Each satellite is typically equipped with four laser communication terminals, two of which establish connections with adjacent satellites in the same orbit, and the other two establish connections with satellites in other orbital planes. Low Earth orbit mega-constellations have a large number of satellites, and the effective communication range of the laser terminals can span multiple orbital planes. Inter-orbit link connections are divided into adjacent orbital connections and cross-orbital connections.

[0025] In practice, the aforementioned implementing entities can establish the cross-orbit topology relationships of each satellite within each time slice through the following steps:

[0026] The first step, for each satellite, is to perform the following processing steps:

[0027] 1. Establish connections between the satellite's two laser communication terminals and adjacent satellites in the same orbit.

[0028] 2. Establish connections between the satellite's other two laser communication terminals and satellites in other orbital planes.

[0029] The second step, for adjacent orbit connections, is to establish a link between satellites with the same number in two adjacent orbits. An adjacent orbit connection refers to satellites with the same number in two adjacent orbits. and Establish the link.

[0030] Third, in the inter-orbit connection method, for each satellite, perform the following processing steps:

[0031] 1. When the satellite's orbital number is odd and the satellite number is odd, then this satellite will be compared with the first eastern satellite. Establish a link and connect with the second western satellite. Establish the link.

[0032] 2. When the satellite's orbital number is odd and the satellite number is even, the satellite will be compared with the first western satellite. Establish a link and connect with the second eastern satellite. Establish the link.

[0033] For example, for satellites When orbital number i is odd and satellite number j is odd, the satellite and the satellite to the east... Establish a link with the western satellite. Establish a link; satellites with even-numbered satellite numbers (j) connect with satellites to the west. Establish a link with the eastern satellite. Establish a link. The case where track number i is even is the opposite of the case where track number i is odd, as illustrated in the diagram below. Figure 2 As shown.

[0034] Step 102: Determine the transmission information of each satellite based on the cross-orbit topology relationship of each satellite.

[0035] In some embodiments, the aforementioned execution entity can determine the transmission information of each satellite based on the cross-orbit topology of each satellite. This transmission information includes: total routing path delay, total packet loss rate, and total data delivery rate. In practice, the aforementioned execution entity can analyze communication, sensing, and computing services. During the inter-satellite link phase, these three types of services have different sensitivities to transmission delay, throughput, and data reliability. Communication services are particularly sensitive to the impact of transmission delay; sensing services typically require high-throughput routing to transmit sensed image information; and computing services need to ensure data reliability during transmission to avoid data loss. Then, the sensitivity indicators for each service are modeled according to its characteristics.

[0036] Transmission delay includes queuing delay, propagation delay, and forwarding delay. Assume that LEO satellites with limited buffers forward data packets in a first-out (FIFO) manner, following an M / M / 1 / m queuing model, where M represents the time interval distribution between consecutive data packet arrivals and the service time distribution, 1 indicates the existence of a single queue in the router, and m represents the buffer capacity. In this queuing model, the occupancy rate ρ can be defined as:

[0037] .

[0038] in, Let μ represent the packet arrival rate of the LEO satellite, and μ represent the packet forwarding rate. Therefore, the packet forwarding delay in the LEO satellite can be represented by 1 / μ, and then the average number of packets queued in the LEO satellite buffer can be expressed as:

[0039] .

[0040] The effective data packet processing rate of the LEO satellite can be expressed as:

[0041] .

[0042] Where P0 represents the probability that the LEO satellite is idle:

[0043] .

[0044] Based on the above conditions, we state the queuing delay for LEO satellites as follows:

[0045] .

[0046] A data packet from LEO satellite v i to v j The propagation delay can be determined based on the spatial distance e i,j The calculation is as follows:

[0047] .

[0048] Here, c represents the propagation speed of the laser in space. Therefore, the speed of propagation from the LEO satellite v can be calculated. i to v j The one-hop delay is as follows:

[0049] .

[0050] Therefore, the total delay of the routing path is:

[0051] .

[0052] Then, considering the limited buffer capacity of LEO satellites, the packet loss rate of LEO satellite i can be expressed as:

[0053] .

[0054] Total packet loss rate P along the path path It can be represented as:

[0055] .

[0056] The throughput can be represented by the total data delivery rate of each LEO satellite over a period of time, which in turn represents the forwarding capacity. The total data delivery rate can be denoted as:

[0057] .

[0058] in, This indicates that within a given time period, data from LEO satellite v... i Number of packets successfully sent to their destination. Indicates LEO satellite v i The number of packets sent within a given time period. (D) path It is the packet delivery rate (total data delivery rate) of the entire routing path.

[0059] Step 103: Based on the total routing path delay, path packet loss rate, and data delivery rate included in the transmission information, establish the routing path utility function for each satellite.

[0060] In some embodiments, the aforementioned execution entity may establish a routing path utility function for each satellite based on the total routing path delay, path packet loss rate, and data delivery rate included in the transmission information.

[0061] For example, different QoS models are defined for the synergistic computing service to reflect diverse needs. A utility function is defined to represent the sensitivity of different services to three considered QoS metrics. Since the value ranges of the three considered QoS metrics are different, a standardization process is first performed, and then the weight w of each QoS metric is heuristically set according to QoS requirements. The routing path utility function for each routing path can be as follows:

[0062] .

[0063] in, , and represents the normalized values ​​of total routing path delay, total packet loss rate, and total data delivery rate, respectively. w1, w2, and w3 represent the normalized weights of service link delay, remaining bandwidth, and packet loss rate, respectively. Since this paper studies a multi-objective routing algorithm integrating sensing and computation, its objective should be to minimize the overall utility function, taking into account the transmission power R. t and LEO satellite buffer size N b With queue length N q The constraints can be expressed as follows:

[0064] .

[0065] Step 104: Based on the genetic tabu hybrid algorithm, optimize the utility functions of each of the above routing paths to obtain the optimized inter-satellite routing table.

[0066] In some embodiments, the aforementioned execution entity can optimize the utility functions of each routing path based on a genetic tabu hybrid algorithm to obtain an optimized inter-satellite routing table. For example, to optimize the routing path utility function using a genetic tabu hybrid algorithm, firstly, individual encoding is performed. In low-Earth orbit satellite network routing, each chromosome (individual) represents an inter-satellite routing path, and the fitness value of the chromosome is calculated to evaluate the quality of the path. Then, a crossover operation is performed to exchange some genes of the chromosome to form a new chromosome, which is also a new route. Mutation operations can also be used to form new chromosomes to expand the search range. After one round of genetics, tabu search is used as a genetic operator to enhance the fitness value of some chromosomes.

[0067] In practice, the aforementioned execution entity can optimize the utility functions of each routing path through the following steps:

[0068] The first step is to encode the inter-satellite routing paths corresponding to each routing path utility function to generate encoded paths, which are then treated as individuals. For example, in low-Earth orbit satellite network routing, each chromosome represents an inter-satellite routing path, and the fitness value of the chromosome is calculated to evaluate the path's quality. This can be calculated using the fitness function described below.

[0069] The second step is to randomly select a group of individuals from among the individuals as the initial population, where each individual in the initial population is an inter-satellite routing path from the initial satellite to the target satellite.

[0070] Third, for the initial population, perform the following iterative steps:

[0071] 1. Perform crossover operation on each individual in the initial population to obtain the crossover population.

[0072] The crossover operation is performed on each individual in the initial population, including:

[0073] First, randomly select two individuals from different parent generations from the initial population. (a) Randomly select two individuals from different parent generations from the current population (initial population).

[0074] Second, generate random numbers between 0 and 1. Generate random numbers p between 0 and 1, where p is determined by the crossover probability p. c The size relationship between the two parent individuals determines whether to perform cross-operations on them.

[0075] Third, in response to determining that the random number is less than or equal to a preset value p c Two integers within a preset range are randomly generated and used as the intersection point. If p > p c If p, then no crossover is needed, and the current crossover operation ends. <p c This generates two distinct integers within the range [1, len] as the intersection point. The default range is [1, len]. The value of len can be set according to requirements.

[0076] Fourth, swap the portions between the two intersection points of two individuals from different parents to obtain crossover individuals. Then, perform multiple crossovers between the portions between the two intersection points of two parents to create two new individuals.

[0077] 2. Perform mutation operations on individuals in the crossover population to obtain the mutated population. The process of performing mutation operations is as follows: Figure 3 As shown, we will use a specific mutation probability p m Selected individuals from the crossover population were mutated. The purpose of this mutation operation is to introduce new individuals into the population, thereby expanding the search space of the algorithm, ensuring the diversity of the population, and effectively avoiding the algorithm from getting trapped in local optima. Given that the individual genes in this paper represent data transmission paths, it is necessary to ensure that the mutated path is still a complete pathway when performing mutation operations. To this end, a set of specific rules were designed to implement mutation operations: (1) not increasing the number of routing hops based on the parallelogram principle; (2) adding two hops in the inter-orbit route to reach the same destination satellite; (3) reducing the number of two-hop paths in the inter-orbit route to reach the same destination satellite.

[0078] 3. Based on the designed fitness function, select the m individuals with the highest fitness from the mutant population to construct a new selection population. Design the fitness function and calculate whether the fitness value of individuals in the current population meets the termination condition, that is, if the best individual has not changed for Q consecutive generations, the algorithm ends; otherwise, continue with the subsequent operations in step 3. The fitness function is as follows:

[0079] .

[0080] in, , Let be the weight coefficient, and satisfy... + =1, This indicates the QoS of the routing communication service. This represents the index of routing load balancing.

[0081] The purpose of the selection operation is to directly pass on optimized individuals to the offspring population. This invention first selects the K individuals with the highest fitness based on their fitness ranking, then randomly selects M individuals, and from these M individuals, selects the m individuals with the highest fitness. This process is repeated until the new population reaches its maximum population size.

[0082] 4. Perform a tabu search on the selected population to obtain a search solution, and add the search solution to the tabu list. During the tabu search phase, the initial solution of the tabu search algorithm can be randomly generated, but the quality of the initial solution has a significant impact on the search performance. Therefore, this disclosure uses the optimization result from the genetic search phase as the initial solution for tabu search, and then adds the search solution to the tabu list. Create a candidate solution set for the current solution, i.e., the neighborhood solution set of the current solution. Select the candidate solution with the best fitness value in this round from the candidate solution set and compare it with the global optimum. If it is better than the global optimum and meets the contempt principle, then regardless of whether it is tabu, use the best candidate solution to update the global optimum and use it as the current solution for the next iteration, and then add the corresponding tabu object to the tabu list. Add the new current solution to the tabu list and update the tabu list. If the tabu list is full, perform corresponding processing according to the tabu length and contempt criterion, such as releasing some tabu objects or selecting the best tabu object for amnesty. Determine whether the termination criterion is met. If the conditions are met, output the optimal solution found and end the algorithm; otherwise, repeat the above steps to continue the search.

[0083] The fourth step involves determining if the tabu list satisfies the termination condition and outputting the optimized inter-satellite routing table. The termination condition is: the optimal individual for Q consecutive generations has not changed. The optimized inter-satellite routing table can refer to a tabu list that satisfies the termination condition.

[0084] Step 105: Perform inter-satellite routing communication based on the optimized inter-satellite routing table described above.

[0085] In some embodiments, the aforementioned implementing entity can perform inter-satellite routing communication based on the optimized inter-satellite routing table. That is, inter-satellite communication can be performed according to the various routing paths in the optimized inter-satellite routing table. Specifically, when data is transmitted between satellites, data communication is performed according to the routing paths in the optimized inter-satellite routing table.

[0086] Further reference Figure 4As an implementation of the methods shown in the above figures, this disclosure provides some embodiments of an inter-satellite routing device based on a genetic tabu hybrid algorithm. These device embodiments are similar to... Figure 1 Corresponding to the method embodiments shown, this inter-satellite routing device based on the genetic tabu mixing algorithm can be specifically applied to various electronic devices.

[0087] like Figure 4 As shown, an inter-satellite routing device 400 based on a genetic tabu mixing algorithm in some embodiments includes: an initialization unit 401, a determination unit 402, an establishment unit 403, an optimization unit 404, and a communication unit 405. The initialization unit 401 is configured to initialize the satellite network environment, slice it according to time slices, and establish the cross-orbit topology relationship of each satellite within each time slice. The satellite network environment contains multiple satellites. The determination unit 402 is configured to determine the transmission information of each satellite based on the cross-orbit topology relationship. The transmission information includes: total routing path delay, total path packet loss rate, and total data delivery rate. The establishment unit 403 is configured to establish the routing path utility function of each satellite based on the total routing path delay, path packet loss rate, and data delivery rate included in the transmission information. The optimization unit 404 is configured to optimize the above-mentioned routing path utility functions based on the genetic tabu mixing algorithm to obtain an optimized inter-satellite routing table. The communication unit 405 is configured to perform inter-satellite routing communication based on the optimized inter-satellite routing table.

[0088] It is understandable that the units described in the inter-satellite routing device 400 based on the genetic tabu mixing algorithm are related to the reference... Figure 1 The steps described in the method correspond to each other. Therefore, the operations, features, and beneficial effects described above for the method are also applicable to the inter-satellite routing device 400 based on the genetic tabu hybrid algorithm and the units contained therein, and will not be repeated here.

[0089] The following is for reference. Figure 5 It illustrates a schematic diagram of the structure of an electronic device (such as a computing device) suitable for implementing some embodiments of the present disclosure. Figure 5 The electronic device shown is merely an example and should not be construed as limiting the functionality or scope of the embodiments of this disclosure. Figure 5As shown, the computer device includes a processor, memory, and a network interface connected via a system bus. The memory may include non-volatile storage media and internal memory. The non-volatile storage media may store the operating system and computer programs. The computer programs include program instructions that, when executed, cause the processor to execute any inter-satellite routing method based on a genetic tabu mixing algorithm. The processor provides computational and control capabilities to support the operation of the entire computer device. The internal memory provides an environment for the execution of the computer program in the non-volatile storage media; when executed by the processor, this program causes the processor to execute any inter-satellite routing method based on a genetic tabu mixing algorithm. The network interface is used for network communication, such as sending assigned tasks. Those skilled in the art will understand that... Figure 5 The structure shown is merely a block diagram of a portion of the structure related to the present disclosure and does not constitute a limitation on the computer device to which the present disclosure is applied. A specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0090] It should be understood that the processor can be a Central Processing Unit (CPU), but it can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among these, a general-purpose processor can be a microprocessor or any conventional processor.

[0091] In one embodiment, the processor is configured to run a computer program stored in a memory to perform the following steps: initializing the satellite network environment, slicing it according to time slices, and establishing the cross-orbit topology relationship of each satellite within each time slice, wherein the satellite network environment contains multiple satellites; determining the transmission information of each satellite based on the cross-orbit topology relationship of each satellite, wherein the transmission information includes: total routing path delay, total path packet loss rate, and total data delivery rate; establishing the routing path utility function of each satellite based on the total routing path delay, path packet loss rate, and data delivery rate included in the transmission information; optimizing the above-mentioned routing path utility functions based on a genetic tabu hybrid algorithm to obtain an optimized inter-satellite routing table; and performing inter-satellite routing communication based on the above-mentioned optimized inter-satellite routing table.

[0092] This disclosure also provides a computer-readable storage medium storing a computer program, which includes program instructions. When the program instructions are executed, the method implemented can be referred to various embodiments of the inter-satellite routing method based on the genetic tabu hybrid algorithm disclosed herein.

[0093] The aforementioned computer-readable storage medium may be an internal storage unit of the computer device described in the foregoing embodiments, such as the hard disk or memory of the computer device. Alternatively, the aforementioned computer-readable storage medium may be an external storage device of the computer device, such as a plug-in hard disk, SmartMedia Card (SMC), Secure Digital (SD) card, or Flash Card equipped on the computer device.

[0094] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system 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 system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0095] The above description is merely a selection of preferred embodiments of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in the embodiments of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described inventive concept. For example, technical solutions formed by substituting the above-described features with (but not limited to) technical features with similar functions disclosed in the embodiments of this disclosure.

Claims

1. An inter-satellite routing method based on a genetic tabu hybrid algorithm, characterized in that, include: Initialize the satellite network environment, slice it according to time slices, and establish the cross-orbit topology relationship of each satellite in each time slice. The satellite network environment contains multiple satellites in the satellite network. Based on the cross-orbit topology of each satellite, the transmission information of each satellite is determined. The transmission information includes: total routing path delay, total path packet loss rate, and total data delivery rate. Based on the total routing path delay, path packet loss rate, and data delivery rate included in the transmission information, establish the routing path utility function for each satellite; Based on the genetic tabu hybrid algorithm, the utility function of each routing path is optimized to obtain an optimized inter-satellite routing table; Inter-satellite routing communication is performed based on the optimized inter-satellite routing table.

2. The method according to claim 1, characterized in that, Each satellite includes: 4 laser communication terminals; and the establishment of cross-orbit topology relationships among the satellites within each time slice, including: For each satellite, perform the following processing steps: Establish connections between the satellite's two laser communication terminals and adjacent satellites in the same orbit; The satellite's other two laser communication terminals will establish connections with satellites in other orbital planes; For adjacent orbit connections, a link is established between satellites with the same number in two adjacent orbits; In the inter-orbit connection method, the following processing steps are performed for each satellite: When the satellite's orbital number is odd and the satellite number is odd, establish a link between the satellite and the first eastern satellite, and establish a link between the satellite and the second western satellite. When the satellite's orbital number is odd and the satellite number is even, a link is established between the satellite and the first western satellite, and a link is established between the satellite and the second eastern satellite.

3. The method according to claim 2, characterized in that, The genetic tabu hybrid algorithm optimizes the utility function of each routing path to obtain an optimized inter-satellite routing table, including: Encode the inter-satellite routing path corresponding to each routing path utility function to generate an encoded path as an individual; A group of individuals is randomly selected from the individuals to form an initial population, where each individual in the initial population is an inter-satellite routing path from the initial satellite to the target satellite. For the initial population, perform the following iterative steps: Perform a crossover operation on each individual in the initial population to obtain a crossover population; Perform mutation operations on individuals in the crossover population to obtain the mutated population; Based on the designed fitness function, select the m individuals with the highest fitness from the mutant population to construct a new selection population; Perform a tabu search on the selected population to obtain a search solution, and add the search solution to the tabu table; In response to the determination that the tabu list meets the termination condition, an optimized inter-satellite routing table is output.

4. The method according to claim 3, characterized in that, The process of performing a crossover operation on each individual in the initial population to obtain a crossover population includes: Two individuals from different parents are randomly selected from the initial population; Generate a random number between 0 and 1; In response to determining that the random number is less than or equal to a preset value, two integers within a preset range are randomly generated as the intersection point; By swapping the portions between two intersection points corresponding to individuals from two different parents, we obtain the intersection individuals.

5. An inter-satellite routing device based on a genetic tabu hybrid algorithm, characterized in that, include: The initialization unit is configured to initialize the satellite network environment, slice it according to time slices, and establish the cross-orbit topology relationship of each satellite in each time slice. The satellite network environment contains multiple satellites in the satellite network. The determining unit is configured to determine the transmission information of each satellite based on the cross-orbit topology relationship of each satellite, wherein the transmission information includes: total routing path delay, total path packet loss rate, and total data delivery rate; The establishment unit is configured to establish the routing path utility function for each satellite based on the total routing path delay, path packet loss rate, and data delivery rate included in the transmission information. The optimization unit is configured to optimize the utility function of each routing path based on a genetic tabu hybrid algorithm to obtain an optimized inter-satellite routing table; The communication unit is configured to perform inter-satellite routing communication according to the optimized inter-satellite routing table.

6. An electronic device, characterized in that, include: One or more processors; A storage device on which one or more programs are stored; When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any one of claims 1 to 4.

7. A computer-readable medium, characterized in that, It stores a computer program thereon, wherein the computer program, when executed by a processor, implements the method as described in any one of claims 1 to 4.

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