A Reliable-Oriented Primary / Backup Route Calculation Method for Satellite Networks Based on Weibull Distribution

Abstract

This invention discloses a reliable-oriented primary / backup routing calculation method for satellite networks based on Weibull distribution, belonging to the fields of satellite networks and industrial internet. The implementation method is as follows: In a low-Earth orbit (LEO) satellite network scenario, historical link availability information is obtained through ephemeris analysis. A time-varying Doppler network effect model is constructed to measure link quality, obtaining historical link reliability indices, which are then normalized. A satellite failure rate probability model is established based on the Weibull distribution, and the joint multi-path selection of the satellite network is optimized based on this model. A greedy algorithm is used to solve the generalized maximum coverage problem derived from multi-path selection, and the solution results ensure that the selected path combination has the joint lowest failure rate. The optimal path combination is stored in a satellite routing table, and routing is performed based on the constructed satellite routing table storing the joint optimal path combination, thereby improving the reliability and robustness of the LEO satellite network's guided primary / backup routing.

Description

Technical Field

[0001] This invention belongs to the field of satellite networks and industrial internet, and specifically relates to a method for calculating the optimal route in a satellite network under fault conditions. Background Technology

[0002] With the rapid development of the Internet, satellite networks have attracted widespread attention from industry and academia. Satellite networks, characterized by wide coverage and high throughput, are playing an increasingly important role in the Internet. Low Earth orbit (LEO) satellites have been more widely used than other orbital satellites due to their lower one-way link transmission latency. However, the movement of satellites in orbit leads to frequent changes in link connections and network topology. Due to the variability and instability of satellite links, satellite network link transmission latency is sometimes high, and link failures are frequent. Ordinary static routing cannot solve this problem of dynamic link changes. Regarding link failures, if a single optimal route is interrupted due to a failure, data cannot be forwarded. Therefore, addressing the poor routing robustness caused by frequent failures in the highly dynamic topology of LEO satellite networks is a key issue.

[0003] Although satellite operations are periodic, there is a lack of good modeling for the periodic quality of the links, and how to translate historical link reliability indicators into routing paths is a key issue worth considering. Furthermore, key metrics for measuring link quality generally include end-to-end delay, throughput, and signal-to-noise ratio. For high-speed low-Earth orbit satellites, the Doppler effect at certain latitudes and longitudes can severely impact these key metrics. Therefore, it is necessary to evaluate the relationship between the Doppler effect and these key network metrics and use it to measure satellite link quality. The main causes of routing failures are link failures and satellite failures. Link failures are difficult to analyze probabilistically due to the influence of the interplanetary environment. Satellites, as industrialized hardware devices, should conform to a certain failure rate distribution model. When the optimal primary route fails, an optimal backup route should be selected. Therefore, selecting multiple jointly optimal paths during route selection can prevent both the primary and backup paths from failing, improving the robustness of satellite network routing. Summary of the Invention

[0004] To address the poor routing robustness caused by frequent failures in the highly dynamic topology of low-Earth orbit (LEO) satellite networks, this invention aims to provide a reliable-oriented primary / backup routing calculation method based on Weibull distribution. In the LEO satellite network scenario, historical link availability information is obtained through ephemeris analysis. A time-varying Doppler network effect model is constructed to measure link quality, yielding historical link reliability indices, which are then normalized. A satellite failure rate probability model is established based on the Weibull distribution, and joint multi-path selection in the satellite network is optimized based on this model. A greedy algorithm is used to solve the generalized maximum coverage problem derived from multi-path selection. The solution results ensure that the selected path combination has a joint minimum failure rate, thereby improving the reliability and robustness of the LEO satellite network-oriented primary / backup routing.

[0005] The objective of this invention is achieved through the following technical solution.

[0006] The reliable-guided primary / backup route calculation method for satellite networks based on Weibull distribution disclosed in this invention includes the following steps:

[0007] Step 1: Describe the position and velocity of the spacecraft using satellite ephemeris. When low-Earth orbit (LEO) satellites exceed a predetermined distance, inter-satellite communication links cannot be established due to signal attenuation and interference. Based on satellite ephemeris, a preliminary assessment is made as to whether an inter-satellite link can be established within a satellite's operational cycle, thus obtaining preliminary connectivity and disconnection history information for the satellite link within one operational cycle. The satellite's operational velocity vector at various time points is obtained from the satellite ephemeris, thereby establishing a time-varying Doppler network effect model to measure link quality. Based on the time-varying Doppler network effect model, historical reliability indices for the links, routes, and path sets within the LEO satellite network's operational cycle are obtained.

[0008] Step 1.1: Describe the position and velocity of the spacecraft using satellite ephemeris data. Based on the satellite ephemeris data, obtain preliminary information on the connection and disconnection history of the satellite link within one operating cycle. If satellite A sends a signal to satellite B, then after Doppler shift, the receiving frequency of satellite B is:

[0009]

[0010] Where f d f is the frequency of the signal received by the satellite at the receiving end. s It is the frequency of the signal emitted by the satellite at the transmitting end, v d v is the tangential velocity of the transmitting end. s The tangential velocity of the receiving satellite, where c is the speed of light, and θ is the velocity of light. d Let θ be the angle between the direction of signal propagation and the direction of the receiving satellite. s It is the angle between the direction of signal propagation and the direction of satellite launch.

[0011] The received signal in a binary phase shift keying (BPSK) modulation communication system is demodulated to obtain the bit error rate P. b The bit error rate P b This translates to an impact on network transmission performance. In low-Earth orbit (LEO) satellite networks, data is transmitted and forwarded in packets. The size of a data packet in a LEO satellite network frame is 360 mm. size Byte, N bit Let be the bits in the data packet, and let FEC's error correction capability be 'a' bits per data packet. Then the probability that the data packet is successfully received is:

[0012]

[0013] The throughput of a low-Earth orbit satellite network is then expressed as:

[0014] T = P packet *B bandwidth (3)

[0015] Among them B bandwidth This refers to the available bandwidth for link communication.

[0016] Equations (1), (2), and (3) are Doppler effect models constructed based on the velocity vector information of satellites at various latitudes and longitudes in the ephemeris.

[0017] Step 1.2: Convert the network throughput in the time-varying Doppler network effect model obtained in Step 1.1 into a link quality index. During the first operational cycle after each satellite joins the low-Earth orbit satellite network, packet routing and forwarding are not performed during the first operational cycle. Only the link quality established between the satellite and its surrounding satellites during the first operational cycle is calculated, yielding the link quality result. This link quality result is used as a measure of the historical reliability within the satellite's operational cycle. A path is composed of multiple links, and the historical reliability index of the path is obtained from the historical reliability index of the links. For the i-th path P... i There are n links, and the historical reliability metrics of the n links are LR1, LR2, LR3, ..., LR n LR i The link quality at each time point is as follows use Let represent the historical reliability index of the i-th path at time t. Then, the historical reliability index PR of the i-th path... i for:

[0018]

[0019] The path set Q has k paths, all of which have the same source and destination nodes. The historical reliability metrics of the k paths are PR1, PR2, PR3, ..., PR4. k PR i The link quality at each time point is as follows Use q t Let Q represent the historical reliability index of the path combination Q at time t. The historical reliability index QR of the path combination Q is expressed as follows:

[0020]

[0021] The historical reliability indicators of the links, routes, and path sets within the operation cycle of the low-orbit satellite network are defined by equations (4) and (5). These historical reliability indicators are used for primary and backup route selection in the subsequent step three.

[0022] Step 2: The main causes of routing failures are link failures and satellite failures. Link failures are difficult to analyze probabilistically due to the influence of the interplanetary environment. Satellite failure distributions conform to failure rate distributions, and a probability distribution model is constructed to characterize the satellite failure distribution. Based on the satellite failure distribution, the failure rate at each moment during the satellite service time is determined, and the historical reliability indicators in Step 1 are corrected. Based on the correction results, the prediction accuracy of the historical reliability indicators for the link, path, and path set link quality within the satellite network operation cycle is improved.

[0023] Step 2.1: The main causes of routing failures are link failures and satellite failures. Link failures are difficult to analyze probabilistically due to the influence of the inter-space environment, while satellite failure distributions conform to failure rate distributions. A Weibull distribution is used to measure failure rate or reliability. A Weibull distribution probability model is constructed to characterize the satellite failure distribution. The three-parameter probability density function of the Weibull distribution is:

[0024]

[0025] Here, β is the shape parameter, also known as the Weibull slope, η is the scaling parameter, and γ is the position parameter, also known as the threshold parameter. The probability distribution function in the Weibull distribution is:

[0026]

[0027] Where t is a random variable, β is a shape parameter, η is a scaling factor, and γ is a position factor.

[0028] Step 2.2: Based on the Weibull distribution probability distribution function in Step 2.1, the cumulative probability of random failures occurring during the satellite's lifespan is characterized. F(t) serves as a failure rate function for the satellite. When the shape parameter β < 1, the failure rate decreases with time. β = 1 represents the period of stable satellite operation, during which failures are random. When the shape parameter β > 1, it indicates that the satellite has undergone wear or aging after long-term use, and the failure rate increases with time. Three different types of graphs based on the transformation of the shape parameter β constitute the spectrum of the satellite's entire lifespan, which conforms to the "bathtub curve".

[0029] Step 2.3: In a low-Earth orbit satellite network, the "bathtub curve" of each satellite is pre-estimated when the satellite joins the network. This pre-estimated "bathtub curve" is stored in the satellite's onboard equipment. During each satellite routing path calculation, the failure rate of the participating satellites is calculated and added to the link quality measurement. When the normalized link historical reliability index obtained in step 1.3 is LR, the link failure rate P is used to measure the link quality. failture After correcting the historical reliability metric LR, the link's historical reliability metric after incorporating the failure rate is LR*(1-P). failture This further improves the accuracy of the historical reliability index (LR) in predicting the quality of links, paths, and path sets within the satellite network's operational cycle. failture Let P be the link failure rate. failture It is the product of the source satellite failure rate and the destination satellite failure rate. That is:

[0030]

[0031] Step 3: Based on the historical reliability indicators of the satellite network from the real-time satellite failures in Step 2, define the optimality of path combinations. Using the optimality of path combinations as the optimization objective and the path affiliation as the constraint, construct a generalized maximum coverage optimization problem. Use a greedy algorithm to solve the generalized maximum coverage optimization problem to obtain the optimal path combination with the joint minimum failure rate based on the Weibull distribution probability model. This reduces the computational time complexity of the optimal path combination and the computation time of backup routes. Store the optimal path combination in the satellite routing table, constructing a satellite routing table that stores the joint optimal path combination. For path combinations already found in the satellite routing table, perform direct routing. For path combinations not found in the satellite routing table, use a greedy algorithm to solve the generalized maximum coverage optimization problem, store the obtained optimal path combination with the minimum failure rate in the satellite routing table to update the satellite routing table, and then perform routing. Perform routing based on the constructed satellite routing table storing the joint optimal path combination, improving the reliability and robustness of the low-Earth orbit satellite network's guided primary / backup routing.

[0032] Step 3.1: Select the joint optimal backup path combination by defining the optimality of the path combination as shown in equation (9):

[0033]

[0034] Where Q represents the selected path combination, and k represents the size of the path combination, which is adjusted according to the failure frequency of the low-Earth orbit satellite network. This refers to a path history reliability metric based on failure rate correction. Based on the historical reliability index PR of path l obtained in step 1 l and the link failure rate P in step 2 failture According to equation (10):

[0035]

[0036] in The path failure rate is the product of the failure rates of all links in path l.

[0037] The quantification of the combined optimal backup path selection is achieved according to equations (9) and (10).

[0038] Step 3.2: Construct a set of candidate paths H, and select k paths from the set of candidate paths H as a set of backup paths Q, based on the optimality of the path combination. To optimize the objective, based on path association... As constrained, the generalized maximum cover optimization problem is constructed as shown in equation (11):

[0039]

[0040] A greedy algorithm is used to solve the generalized maximum coverage problem derived from multi-path selection, and a joint optimal path combination is obtained. This path combination has a joint minimum failure rate based on the Weibull distribution probability model, which improves the reliability and robustness of the primary and backup routing of the low-Earth orbit satellite network. At the same time, the greedy algorithm is used to solve the generalized maximum coverage optimization problem to reduce the computational time complexity and reduce the computation time of backup routes.

[0041] Step 3.3: Store the optimal path combination obtained in Step 3.2 into the satellite routing table to construct a satellite routing table storing the joint optimal path combination. For path combinations already found in the satellite routing table, direct routing is performed. For path combinations not found in the satellite routing table, a greedy algorithm is used to solve the generalized maximum coverage optimization problem. The optimal path combination with the lowest failure rate is then stored in the satellite routing table to update the satellite routing table, and routing is performed. Routing is performed based on the constructed satellite routing table storing the joint optimal path combination, improving the reliability and robustness of the low-Earth orbit satellite network's guided primary / backup routing.

[0042] Beneficial effects:

[0043] 1. The present invention discloses a method for measuring historical reliability indicators within a satellite's operational cycle. It uses satellite ephemeris to describe the position and velocity of a spacecraft, establishes a time-varying Doppler network effect model, measures link quality based on the time-varying Doppler network effect model, and defines historical reliability indicators for the set of links, routes, and paths within the satellite network's operational cycle, thereby achieving accurate evaluation of satellite network routing indicators.

[0044] 2. The present invention discloses a satellite service time failure rate model based on Weibull distribution. It constructs a Weibull probability distribution model to characterize the satellite failure distribution, and uses the characterized periodic failure rate to correct historical reliability indicators, thereby improving the prediction accuracy of historical reliability indicators for the link, route, and path set link quality within the satellite network operation cycle.

[0045] 3. The present invention discloses a method for selecting a joint optimal backup path combination. By defining the optimality of the path combination, a generalized maximum coverage optimization problem is constructed. A greedy algorithm with low time complexity is used to select the k joint optimal paths from all path combinations. This reduces the routing calculation time while obtaining the most reliable path combination, thereby improving the robustness of the satellite network. Attached Figure Description

[0046] Figure 1 This is a flowchart of a reliable-guided primary / backup routing calculation method for satellite networks based on the Weibull distribution;

[0047] Figure 2 This is a schematic diagram of the interstellar Doppler effect model;

[0048] Figure 3 This is a flowchart of a greedy algorithm for selecting paths to include in path combinations;

[0049] Figure 4 It is a diagram showing the connectivity and disconnection information of a portion of the links within one operating cycle of a satellite ephemeris. Detailed Implementation

[0050] The technical solutions of the embodiments of the present invention will be clearly and completely described with reference to the accompanying drawings. These embodiments are only a part of the embodiments of the present invention, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the protection scope of the present invention.

[0051] Example 1:

[0052] In this embodiment, a 64×64 polar-orbiting Walker constellation is constructed in the satellite simulation software STK11. One operating cycle of the satellite is divided into 10 time periods for modeling and normalization analysis. When establishing the time-varying Doppler network effect model, binary phase-shift keying (BPSK) modulation is used for simulation. The average service life of the low-orbit satellite is set to 10 years, and a total of 5 primary and backup paths are selected.

[0053] like Figure 1 As shown in this embodiment, the reliable-oriented primary / backup routing calculation method for satellite networks based on Weibull distribution is implemented in the following ways:

[0054] Step 1: Describe the position and velocity of the spacecraft using satellite ephemeris. When low-Earth orbit satellites exceed a predetermined distance, inter-satellite communication links cannot be established due to signal attenuation and interference. Based on satellite ephemeris, a preliminary judgment is made as to whether an inter-satellite link can be established within a satellite's operational cycle, thus obtaining preliminary information on the connectivity history of the satellite link within one operational cycle. Figure 4 As shown, the satellite's operational velocity vectors at various time points are obtained from the satellite ephemeris, thus establishing a time-varying Doppler network effect model for measuring link quality. Based on the time-varying Doppler network effect model, historical reliability indices of links, routes, and path sets within the operational cycle of the low-Earth orbit satellite network are obtained.

[0055] Step 1.1: Use satellite ephemeris data to describe the position and velocity of the spacecraft. Based on the satellite ephemeris data, preliminary information on the connection and disconnection history of the satellite link within one operational cycle is obtained. For example... Figure 2 As shown in the schematic diagram of the inter-satellite Doppler effect model, if satellite A transmits a signal with a frequency of 1 THz to satellite B, then after the Doppler frequency shift, the receiving frequency of satellite B is:

[0056]

[0057] Where f d f is the frequency of the signal received by the satellite at the receiving end. s It is the frequency of the signal emitted by the satellite at the transmitting end, v d v is the tangential velocity of the transmitting end. s The tangential velocity of the receiving satellite, where c is the speed of light, and θ is the velocity of light. d Let θ be the angle between the direction of signal propagation and the direction of the receiving satellite. s It is the angle between the direction of signal propagation and the direction of satellite launch.

[0058] The received signal in a binary phase shift keying (BPSK) modulation communication system is demodulated to obtain the bit error rate P. b The bit error rate P bThis translates to an impact on network transmission performance. In low-Earth orbit (LEO) satellite networks, data is transmitted and forwarded in packets. The size of a data packet in a LEO satellite network frame is 360 mm. size Byte, N bit This refers to the bits in the data packet, which is 8 in this embodiment. The forward error correction (FEC) capability is 'a' bits per data packet, which is 2 in this embodiment. Therefore, the probability of the data packet being successfully received is:

[0059]

[0060] The throughput of a low-Earth orbit satellite network is then expressed as:

[0061] T = P packet *B bandwidth (3)

[0062] Among them B bandwidth This refers to the available bandwidth for link communication.

[0063] Equations (1), (2), and (3) are Doppler effect models constructed based on the velocity vector information of satellites at various latitudes and longitudes in the ephemeris.

[0064] Step 1.2: Convert the network throughput in the time-varying Doppler network effect model obtained in Step 1.1 into a link quality index. During the first operational cycle after each satellite joins the low-Earth orbit satellite network, packet routing and forwarding are not performed during the first operational cycle. Only the link quality established between the satellite and its surrounding satellites during the first operational cycle is calculated, yielding the link quality result. This link quality result is used as a measure of the historical reliability within the satellite's operational cycle. A path is composed of multiple links, and the historical reliability index of the path is obtained from the historical reliability index of the links. For the i-th path P... i There are n links, and the historical reliability metrics of the n links are LR1, LR2, LR3, ..., LR n LR i The link quality at each time point is as follows use Let represent the historical reliability index of the i-th path at time t. Then, the historical reliability index PR of the i-th path... i for:

[0065]

[0066] In this example, the path set Q has 8 paths, all of which share the same source and destination nodes. The historical reliability metrics for these 8 paths are PR1, PR2, PR3, ..., PR8. iThe link quality at each time point is as follows Use q t Let Q represent the historical reliability index of the path combination Q at time t. The historical reliability index QR of the path combination Q is expressed as follows:

[0067]

[0068] The historical reliability indicators of the links, routes, and path sets within the operation cycle of the low-orbit satellite network are defined by equations (4) and (5). These historical reliability indicators are used for primary and backup route selection in the subsequent step three.

[0069] Step 2: The main causes of routing failures are link failures and satellite failures. Link failures are difficult to analyze probabilistically due to the influence of the interplanetary environment. Satellite failure distributions conform to failure rate distributions, and a probability distribution model is constructed to characterize the satellite failure distribution. Based on the satellite failure distribution, the failure rate at each moment during the satellite service time is determined, and the historical reliability indicators in Step 1 are corrected. Based on the correction results, the prediction accuracy of the historical reliability indicators for the link, path, and path set link quality within the satellite network operation cycle is improved.

[0070] Step 2.1: The main causes of routing failures are link failures and satellite failures. Link failures are difficult to analyze probabilistically due to the influence of the inter-space environment, while satellite failure distributions conform to failure rate distributions. A Weibull distribution is used to measure failure rate or reliability. A Weibull distribution probability model is constructed to characterize the satellite failure distribution. The three-parameter probability density function of the Weibull distribution is:

[0071]

[0072] Here, β is the shape parameter, also known as the Weibull slope, η is the scaling parameter, and γ is the position parameter, also known as the threshold parameter. The probability distribution function in the Weibull distribution is:

[0073]

[0074] Where t is a random variable, β is a shape parameter, η is a scaling factor, and γ is a position factor.

[0075] Step 2.2: Based on the Weibull distribution probability distribution function in Step 2.1, the cumulative probability of random failures occurring during the satellite's lifespan is characterized. F(t) serves as a failure rate function for the satellite. When the shape parameter β < 1, the failure rate decreases with time. β = 1 represents the period of stable satellite operation, during which failures are random. When the shape parameter β > 1, it indicates that the satellite has undergone wear or aging after long-term use, and the failure rate increases with time. Three different types of graphs based on the transformation of the shape parameter β constitute the spectrum of the satellite's entire lifespan, which conforms to the "bathtub curve".

[0076] Step 2.3: In a low-Earth orbit satellite network, the "bathtub curve" of each satellite is pre-estimated when the satellite joins the network. This pre-estimated "bathtub curve" is stored in the satellite's onboard equipment. During each satellite routing path calculation, the failure rate of the participating satellites is calculated and added to the link quality measurement. When the normalized link historical reliability index obtained in step 1.3 is LR, the link failure rate P is used to measure the link quality. failture After correcting the historical reliability metric LR, the link's historical reliability metric after incorporating the failure rate is LR*(1-P). failture This further improves the accuracy of the historical reliability index (LR) in predicting the quality of links, paths, and path sets within the satellite network's operational cycle. failture Let P be the link failure rate. failture It is the product of the source satellite failure rate and the destination satellite failure rate. That is:

[0077]

[0078] Step 3: Based on the historical reliability indicators of the satellite network from the real-time satellite failures in Step 2, define the optimality of path combinations. Using the optimality of path combinations as the optimization objective and the path affiliation as the constraint, construct a generalized maximum coverage optimization problem. Use a greedy algorithm to solve the generalized maximum coverage optimization problem to obtain the optimal path combination with the joint minimum failure rate based on the Weibull distribution probability model. This reduces the computational time complexity of the optimal path combination and the computation time of backup routes. Store the optimal path combination in the satellite routing table, constructing a satellite routing table that stores the joint optimal path combination. For path combinations already found in the satellite routing table, perform direct routing. For path combinations not found in the satellite routing table, use a greedy algorithm to solve the generalized maximum coverage optimization problem, store the obtained optimal path combination with the minimum failure rate in the satellite routing table to update the satellite routing table, and then perform routing. Perform routing based on the constructed satellite routing table storing the joint optimal path combination, improving the reliability and robustness of the low-Earth orbit satellite network's guided primary / backup routing.

[0079] Step 3.1: Select the joint optimal backup path combination by defining the optimality of the path combination as shown in equation (9):

[0080]

[0081] Where Q represents the selected path combination, and k represents the size of the path combination, which is 8 in this embodiment and is adjusted according to the failure frequency of the low-Earth orbit satellite network. This refers to a path history reliability metric based on failure rate correction. Based on the historical reliability index PR of path l obtained in step 1 l and the link failure rate P in step 2 failture According to equation (10):

[0082]

[0083] in The path failure rate is the product of the failure rates of all links in path l.

[0084] The quantification of the combined optimal backup path selection is achieved according to equations (9) and (10).

[0085] Step 3.2: Construct a set of candidate paths H, and select 8 paths from the set of candidate paths H as a set of backup paths Q, based on the optimality of the path combination. To optimize the objective, based on path association... As constrained, the generalized maximum cover optimization problem is constructed as shown in equation (11):

[0086]

[0087] like Figure 3 The flowchart of the greedy algorithm for selecting paths and adding them to the path combination is shown. The greedy algorithm is used to solve the generalized maximum coverage problem derived from multi-path selection, and obtains the joint optimal path combination. This path combination has the joint minimum failure rate based on the Weibull distribution probability model, which improves the reliability and robustness of the primary and backup routing of the low-Earth orbit satellite network. At the same time, the greedy algorithm is used to solve the generalized maximum coverage optimization problem to reduce the computation time complexity and reduce the computation time of backup routes.

[0088] Step 3.3: Store the optimal path combination obtained in Step 3.2 into the satellite routing table to construct a satellite routing table storing the joint optimal path combination. For path combinations already found in the satellite routing table, direct routing is performed. For path combinations not found in the satellite routing table, a greedy algorithm is used to solve the generalized maximum coverage optimization problem. The optimal path combination with the lowest failure rate is then stored in the satellite routing table to update the satellite routing table, and routing is performed. Routing is performed based on the constructed satellite routing table storing the joint optimal path combination, improving the reliability and robustness of the low-Earth orbit satellite network's guided primary / backup routing.

[0089] The above detailed description further illustrates the purpose, technical solution, and beneficial effects of the invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A reliable-guided primary / backup route calculation method for satellite networks based on Weibull distribution, characterized by: Includes the following steps, Step 1: Use satellite ephemeris to describe the position and velocity of the spacecraft. After the distance between low-Earth orbit satellites exceeds the predetermined distance, inter-satellite communication links cannot be established due to signal attenuation and interference. Based on the satellite ephemeris, it is initially determined whether the inter-satellite link can be established within the satellite's operating cycle, that is, the historical information of the satellite link's connection and disconnection within one operating cycle is initially obtained. The satellite's operating velocity vector at each time point is obtained from the satellite ephemeris, thereby establishing a time-varying Doppler network effect model to measure the link quality. Based on the time-varying Doppler network effect model, the historical reliability index of the links, routes, and path sets within the low-Earth orbit satellite network's operating cycle is obtained. Step 2: The main causes of routing failures are link failures and satellite failures. Link failures are difficult to analyze probabilistically due to the influence of the interplanetary environment. Satellite failure distributions conform to failure rate distributions. A probability distribution model is constructed to characterize the satellite failure distribution. Based on the satellite failure distribution, the failure rate at each moment during the satellite service time is determined. The historical reliability indicators in Step 1 are then corrected. Based on the correction results, the accuracy of the historical reliability indicators in predicting the link, path, and path set link quality within the satellite network operation cycle is improved. Step 3: Based on the historical reliability index of the satellite network in step 2 regarding real-time satellite failures, define the optimality of path combinations. Using the optimality of path combinations as the optimization objective and the path affiliation as the constraint, construct a generalized maximum coverage optimization problem. Use a greedy algorithm to solve the generalized maximum coverage optimization problem to obtain the optimal path combination with the joint minimum failure rate based on the Weibull distribution probability model, thereby reducing the computational time complexity of the optimal path combination and reducing the computation time of backup routes. Store the optimal path combination in the satellite routing table to construct a satellite routing table that stores the joint optimal path combination. For the path combinations already in the satellite routing table, directly perform routing and forwarding. For path combinations not found in the satellite routing table, a greedy algorithm is used to solve the generalized maximum coverage optimization problem. The optimal path combination with the lowest failure rate is stored in the satellite routing table to update the satellite routing table and perform route forwarding. Route forwarding is performed based on the constructed satellite routing table storing the joint optimal path combination, thereby improving the reliability and robustness of the low-Earth orbit satellite network's guided primary and backup routing.

2. The reliable-guided primary / backup routing calculation method for satellite networks based on Weibull distribution as described in claim 1, characterized in that: Step 1 is implemented as follows: Step 1.1: Use satellite ephemeris to describe the position and velocity of the spacecraft; based on the satellite ephemeris data, obtain preliminary information on the connection and disconnection history of the satellite link within one operating cycle; if satellite A sends a signal to satellite B, then after Doppler frequency shift, the receiving frequency of satellite B is: (1) in The frequency of the signal received by the satellite at the receiving end. It is the frequency of the signal emitted by the satellite at the transmitting end. , Tangential velocity of the receiving satellite, For the speed of light, The angle between the direction of signal propagation and the direction of the receiving satellite. It is the angle between the direction of signal propagation and the direction of satellite launch; The received signal in a binary phase shift keying (BPSK) modulation communication system is demodulated to obtain the bit error rate. Bit error rate This translates to an impact on network transmission performance. In low-Earth orbit (LEO) satellite networks, data is transmitted and forwarded in packet form; the size of a data packet within a LEO satellite network frame is... , It is in the data packet Furthermore, the error correction capability of Forward Error Correction (FEC) is per data packet. If there are bits, then the probability that the data packet is successfully received is: (2) The throughput of a low-Earth orbit satellite network is then expressed as: (3) in Available bandwidth for link communication; Equations (1), (2), and (3) are Doppler effect models constructed based on the satellite's velocity vector information at various latitudes and longitudes in the ephemeris. Step 1.2: Convert the network throughput in the time-varying Doppler network effect model obtained in Step 1.1 into a link quality index. In the first operating cycle after each satellite joins the low-Earth orbit satellite network, do not route and forward data packets in the first operating cycle. Only calculate the link quality between the satellite and its surrounding satellites in the first operating cycle to obtain the link quality results between the satellite and its surrounding satellites in the first operating cycle. Link quality results are used as a measure of historical reliability over a satellite's operational cycle. The path is composed of multiple links, and the historical reliability index of the path is derived from the historical reliability index of each link. For the first... Path have Link, The historical reliability indicators of the links are as follows: , The link quality at each time point is as follows ;use Indicates the first The path in the first The historical reliability index at the nth time point, then the nth Historical reliability metrics of the path for: (4) The path set Q has Path, All paths have the same source and destination nodes. The historical reliability indicators of the routes are as follows: The link quality at each time point is as follows ;use Represents path combination In the Historical reliability metrics at specific time points; path combination Historical reliability indicators It is expressed as follows: (5) Equations (4) and (5) are used to define the historical reliability indicators of the links, routes, and path sets within the operational cycle of the low-orbit satellite network.

3. The reliable-guided primary / backup routing calculation method for satellite networks based on Weibull distribution as described in claim 2, characterized in that: Step 2 is implemented as follows: Step 2.1: The main causes of routing failures are link failures and satellite failures. Link failures are difficult to analyze probabilistically due to the influence of the interplanetary environment, while satellite failure distributions conform to failure rate distributions. A Weibull distribution is used to measure failure rate or reliability. A Weibull distribution probability model is constructed to characterize the satellite failure distribution. The three-parameter probability density function of the Weibull distribution is: (6) in, The shape parameter is also known as the Weibull slope. For scaling parameters, The location parameter, also known as the threshold parameter; the probability distribution function in the Weibull distribution is: (7) in, For random variables, For shape parameters, Scaling factor For position factors; Step 2.2: Based on the Weibull distribution probability distribution function in Step 2.1, characterize the cumulative probability of random failure times during the satellite's lifespan; As a satellite's failure rate function, when the shape parameter < 1, the failure rate actually decreases over time; =1 represents the period of stable satellite operation; faults occurring during this period are considered random faults; when the shape parameter A value > 1 indicates that the satellite has undergone wear and tear or aging after long-term use, and the failure rate increases with time. Three different types of graphs based on the transformation of the shape parameter β constitute the spectrum of the satellite's entire life cycle, and the spectrum of the satellite's entire life cycle conforms to the "bathtub curve". Step 2.3: In a low-Earth orbit satellite network, when a satellite joins the network, the "bathtub curve" of each satellite is pre-estimated and stored in the satellite's onboard equipment. During each satellite routing path calculation, the failure rate of the satellites involved in the routing is calculated and added to the link quality measurement. When the normalized link historical reliability index obtained in step 1.3 is... By link failure rate Historical reliability metrics The historical reliability index of the link after incorporating the failure rate is then: Historical reliability metrics The accuracy of predicting the quality of links, paths, and path sets within the operational cycle of a satellite network; Link failure rate, link failure rate Source satellite failure rate and target satellite failure rate The product of; that is: (8)。 4. The reliable-guided primary / backup routing calculation method for satellite networks based on Weibull distribution as described in claim 3, characterized in that: Step 3 is implemented as follows: Step 3.1: Select the joint optimal backup path combination by defining the optimality of the path combination as shown in equation (9): (9) in For the selected path combination, The size of the path combination is adjusted based on the failure frequency of the low-Earth orbit satellite network; This refers to a path history reliability metric based on failure rate correction. Based on the path obtained in step 1 Historical reliability indicators Link failure rate in step 2 According to equation (10): (10) in For path The path failure rate is obtained by multiplying the failure rates of all links. The quantification of the combined optimal backup path selection is achieved according to equations (9) and (10); Step 3.2: Construct a set of alternative paths From the set of alternative paths Selected The path is used as a set of backup paths Optimal degree of path combination To optimize the objective, based on path association... As constrained, the generalized maximum cover optimization problem is constructed as shown in equation (11): (11) A greedy algorithm is used to solve the generalized maximum coverage problem derived from multi-path selection, and a joint optimal path combination is obtained. This path combination has a joint minimum failure rate based on the Weibull distribution probability model, which improves the reliability and robustness of the primary and backup routing of the low-Earth orbit satellite network. At the same time, the greedy algorithm is used to solve the generalized maximum coverage optimization problem to reduce the computation time complexity and reduce the computation time of backup routes. Step 3.3: Store the optimal path combination obtained in Step 3.2 into the satellite routing table to construct a satellite routing table that stores the joint optimal path combination; for the path combinations already in the satellite routing table, directly perform routing forwarding; For path combinations not found in the satellite routing table, a greedy algorithm is used to solve the generalized maximum coverage optimization problem. The optimal path combination with the lowest failure rate is stored in the satellite routing table to update the satellite routing table and perform route forwarding. Route forwarding is performed based on the constructed satellite routing table storing the joint optimal path combination, thereby improving the reliability and robustness of the low-Earth orbit satellite network's guided primary and backup routing.

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