A routing parameter optimization method and system based on a homotopy transfer optimization algorithm

Abstract

The application provides a routing parameter optimization method and system based on a Hohmann transfer optimization algorithm, and relates to the technical field of routing protocol optimization. First, routing nodes in a network switching system are initialized. When the routing nodes in the network switching system need to adjust routing protocol parameters, routing protocol data pairs are read from a historical routing protocol data set of the routing node. Iterative calculation is performed based on a Hohmann transfer optimization algorithm to simulate a double-pulse transfer process of a spacecraft between orbits, so that optimal routing protocol parameters of the routing node are obtained. The optimal parameters are sent to all neighbor routing nodes connected by ports, and the parameters of the neighbor routing nodes are modified based on the optimal parameters, so that synchronous optimization of the parameters of the whole network is realized. The scheme has the characteristics of extremely small calculation cost and strong robustness, meets the demand for real-time optimization, and is suitable for various network control architectures such as centralized and distributed architectures.

Description

Technical Field

[0001] This invention relates to the technical field of routing protocol optimization, and more specifically, to a method and system for optimizing routing parameters based on the Hohmann transition optimization algorithm. Background Technology

[0002] The performance of routing protocols is typically evaluated based on two key parameters: route convergence time and route control overhead. Route convergence time refers to the time elapsed from the moment the network topology changes until all routers in the network have updated their routing tables and reached a consensus on the current network state. Route control overhead refers to the non-service data traffic that routers send in the network to run and maintain the routing protocol. In optimizing routing protocols, there is a contradiction in adjusting these two parameters: on the one hand, accelerating convergence requires sending more frequent detection packets, which consumes a large amount of network bandwidth, leading to excessive control overhead; on the other hand, reducing packet sending to save bandwidth slows down route convergence.

[0003] To simultaneously optimize both route convergence time and route control overhead, existing technologies have gradually developed into a combination of heuristic optimization and machine learning-based optimization algorithms, coupled with centralized SDN control to achieve parameter adjustment. Metaheuristic algorithms, including ant colony optimization and PSO, address multiple constraints in route parameter optimization; machine learning-based optimization algorithms, on the other hand, use reinforcement learning and deep learning to find optimal parameters. Based on these different algorithms, centralized SDN control is used to uniformly adjust global routing protocol parameters. While optimization methods combining multi-objective optimization algorithms with SDN control offer strong adaptability, their model building is complex, computationally complex, training cycles are long, real-time optimization capabilities are weak, and most rely on global states, limiting their applicability to centralized control architectures and overall versatility. Summary of the Invention

[0004] To address the issues of high computational complexity, weak real-time optimization capabilities, and insufficient universality in existing routing protocol methods, this invention proposes a routing parameter optimization method based on the Hohmann transition optimization algorithm. This method reduces computational complexity, enables real-time optimization of routing protocols under various network architectures, and improves universality.

[0005] To achieve the above-mentioned technical effects, the technical solution of the present invention is as follows: Firstly, this application proposes a routing parameter optimization method based on the Hohmann transition optimization algorithm. This method is applied to a network switching system, which includes several routing nodes, and comprises the following steps: S1. Initialize the routing nodes in the network switching system; S2. When a routing node in the network switching system needs to adjust its routing protocol parameters, it reads routing protocol data pairs from the historical routing protocol dataset of the routing node and iteratively calculates the optimal routing protocol parameters based on the Hohmann transition optimization algorithm. S3. Send the optimal routing protocol parameters of this routing node to all neighboring routing nodes that have port connections with this routing node. Based on the optimal routing protocol parameters of this routing node, modify the routing protocol parameters of all neighboring routing nodes to complete the routing protocol optimization.

[0006] In this technical solution, the routing nodes in the network switching system are first initialized. When a routing node in the network switching system needs to adjust its routing protocol parameters, it reads routing protocol data pairs from its historical routing protocol dataset. Based on the Hohmann transfer optimization algorithm, it simulates the double-pulse transfer process of a spacecraft in orbit and performs iterative calculations to obtain the optimal routing protocol parameters for that routing node. These optimal parameters are then sent to all neighboring routing nodes with port connections, and the parameters of these neighboring routing nodes are modified based on these parameters, achieving synchronous optimization of parameters across the entire network. This solution features minimal computational overhead, strong robustness, meets the requirements of real-time optimization, and is applicable to various network control architectures, including centralized and distributed systems.

[0007] Preferably, the historical routing protocol dataset of this routing node includes several routing protocol data pairs. Each routing protocol data pair includes routing protocol parameters. The route convergence time when using this routing protocol parameter and the routing control overhead when using this routing protocol parameters .

[0008] Preferably, before calculating the optimal routing protocol parameters, it is also necessary to initialize the optimal routing protocol parameters, including: Set upper bound for routing protocol parameter values Lower bounds of routing protocol parameter values and the number of candidate parameters Calculate the initial values ​​of the optimal routing protocol parameters. The expression is:

[0009] in, Indicates the index of the candidate parameter. .

[0010] Preferably, the step of iteratively calculating the optimal routing protocol parameters based on the Hohmann transition optimization algorithm includes the following steps: S21. Set gravity parameters Maximum number of iterations First weight Second weight Let the number of iterations be... The optimal solution for the semi-major axis of the initialization routing protocol parameters =0; S22. Read the route convergence time and route control overhead from the routing protocol data pairs, and calculate the trajectory metric function for each candidate parameter. The expression is:

[0011] in, This indicates that when the routing protocol parameter takes the value At that time, the route convergence time obtained based on routing protocol data is... This indicates that when the routing protocol parameter takes the value At that time, the routing control overhead is based on the routing protocol data. S23. Calculate the optimal solution for the semi-major axis of the current routing protocol parameters. The expression is:

[0012] S24. Determine the number of iterations Has the maximum number of iterations been exceeded? If not, proceed to step S25; if yes, use the current routing protocol parameters. As the optimal routing protocol parameter; S25. Calculate the first impulse of all candidate parameters. The expression is:

[0013] in, Represents a saturation function. Indicates the first pulse transition factor. , The theoretical semi-major axis represents the candidate parameter transition path, which is the average of the current routing protocol parameters and the optimal routing protocol parameters. ; S26. Based on the first pulse, perform a first pulse transition on all candidate parameters and calculate the values ​​of all candidate parameters after the first pulse transition. The expression is:

[0014] S27. Calculate the second pulse for all candidate parameters. The expression is:

[0015] in, Indicates the second pulse transition factor. ; S28. Based on the second pulse, perform a second pulse transition on all candidate parameters and calculate the values ​​of all candidate parameters after the second pulse transition. The expression is: ; S29. Order And return to S22.

[0016] Preferably, step S22, which involves reading the route convergence time and route control overhead from the route protocol data pair, further includes: Search the current routing protocol data pair to see if it contains the current routing protocol parameters. If a data pair exists, then read the route convergence time and route control overhead from that data pair. If not, retrieve the upper limit neighborhood routing protocol parameter and the lower limit neighborhood routing protocol parameter that are closest to the current routing protocol parameter; Obtain the route convergence time and route control overhead corresponding to the upper limit neighborhood routing protocol parameters and the lower limit neighborhood routing protocol parameters, respectively; Calculate the average route convergence time and average route control overhead corresponding to the upper and lower limit neighborhood routing parameters, and use the obtained averages as the route convergence time of the current routing protocol parameters. and routing control overhead .

[0017] Preferably, step S3, which involves negotiating and modifying the routing protocol parameters of all neighboring routing nodes, includes: S31. Encapsulate the optimal routing protocol parameters of this routing node into a routing parameter negotiation message, and send the message to all neighboring routing nodes connected to the target port; S32. Receive routing protocol parameter acknowledgment messages from all neighboring routing nodes; S33. Send a routing protocol parameter modification execution message to the neighboring routing node, and modify the routing protocol parameters of the corresponding port of this node.

[0018] Preferably, step S32 further includes: S321. Determine whether routing protocol parameter acknowledgment messages have been received from all neighboring routing nodes. If received, proceed to S33. If no acknowledgment messages are received from all neighboring routing nodes, then execute S322; S322. Determine whether the number of retransmissions exceeds the preset retransmission threshold. If it does not exceed the retransmission threshold, retransmit the negotiation message to the unresponsive neighbor routing node, increment the number of retransmissions by one, and return to S321. If the retransmission threshold is exceeded, the negotiation is deemed to have failed, the current routing protocol parameter update is terminated, and the original routing protocol parameters are maintained.

[0019] Preferably, the neighboring routing node receives the routing parameter negotiation message and sends a routing parameter confirmation message back to the local routing node; Receive routing parameter modification execution messages and synchronously modify routing protocol parameters with this routing node.

[0020] Secondly, this application also proposes a routing parameter optimization system based on the Hohmann transition optimization algorithm. The routing protocol optimization system includes a data base module, a routing protocol parameter inference and decision module, and a routing protocol parameter negotiation and adjustment module. The output of the data base module is connected to the input of the routing protocol parameter inference and decision module, and the routing protocol parameter inference and decision module receives the routing protocol data pairs output by the data base module. The output of the routing protocol parameter inference and decision module is connected to the input of the routing protocol parameter negotiation and adjustment module, and the routing protocol parameter negotiation and adjustment module receives the optimal routing protocol parameters output by the routing protocol parameter inference and decision module.

[0021] Thirdly, this application also proposes a computer device, which includes a memory, a processor, and a computer program stored in the memory that can be run by the processor. The processor executes the computer program to implement a routing parameter optimization method based on the Hohmann transition optimization algorithm.

[0022] Compared with the prior art, the beneficial effects of the present invention are: This invention proposes a routing parameter optimization method based on the Hohmann transfer optimization algorithm. First, the historical routing protocol dataset of the current routing node is obtained. This dataset contains multiple data pairs consisting of routing parameters, routing convergence time, and control overhead. The current routing protocol parameters are initialized, and the Hohmann transfer optimization algorithm is used to iteratively calculate the optimal routing protocol parameters for the current routing node by simulating the double-pulse transfer process of a spacecraft in orbit. These optimal parameters are then sent to all neighboring routing nodes with port connections, and the parameters of these neighboring routing nodes are negotiated and modified based on these parameters, achieving synchronous optimization of parameters across the entire network. This scheme features minimal computational overhead, strong robustness, meets the requirements of real-time optimization, and is applicable to various network control architectures, including centralized and distributed systems. Attached Figure Description

[0023] Figure 1This is a flowchart illustrating the routing protocol optimization method based on the Hohmann transition optimization algorithm proposed in Embodiment 1 of the present invention. Figure 2 This is a schematic diagram illustrating the process of iteratively calculating the optimal routing protocol parameters for this routing node using the Hohmann transition algorithm, as proposed in Embodiment 2 of the present invention. Figure 3 This is a schematic diagram illustrating the process of issuing and taking effect the optimal routing protocol parameters proposed in Embodiment 2 of the present invention; Figure 4 This diagram illustrates the structure of the routing protocol optimization system proposed in Embodiment 4 of the present invention. Figure 5 This is a schematic diagram of the structure of the computer device proposed in Embodiment 5 of the present invention. Detailed Implementation

[0024] The accompanying drawings are for illustrative purposes only and should not be construed as limiting the scope of this patent. To better illustrate this embodiment, some parts of the accompanying drawings may be omitted, enlarged, or reduced, and do not represent the actual dimensions; It is understandable to those skilled in the art that some well-known details may be omitted from the accompanying drawings.

[0025] The technical solution of the present invention will be further described below with reference to the accompanying drawings and embodiments.

[0026] The positional relationships depicted in the accompanying drawings are for illustrative purposes only and should not be construed as limiting this patent. Example 1 This embodiment proposes a routing parameter optimization method based on the Hohmann transition optimization algorithm. A flowchart of this method can be found here. Figure 1 This includes the following steps: S1. Initialize the routing nodes in the network switching system; S2. When a routing node in the network switching system needs to adjust its routing protocol parameters, it reads routing protocol data pairs from the historical routing protocol dataset of the routing node and iteratively calculates the optimal routing protocol parameters based on the Hohmann transition optimization algorithm. S3. Send the optimal routing protocol parameters of this routing node to all neighboring routing nodes that have port connections with this routing node. Based on the optimal routing protocol parameters of this routing node, modify the routing protocol parameters of all neighboring routing nodes to complete the routing protocol optimization.

[0027] In this embodiment, the routing nodes in the network switching system are first initialized. When a routing node in the network switching system needs to adjust its routing protocol parameters, it reads routing protocol data pairs from its historical routing protocol dataset. It then performs iterative calculations based on the Hohmann transfer optimization algorithm, simulating the double-pulse transfer process of a spacecraft in orbit, to obtain the optimal routing protocol parameters for that routing node. These optimal parameters are then sent to all neighboring routing nodes with port connections, and the parameters of these neighboring routing nodes are modified based on these parameters, achieving synchronous optimization of the entire network parameters. This scheme features minimal computational overhead, strong robustness, meets the requirements of real-time optimization, and is applicable to various network control architectures, including centralized and distributed systems.

[0028] Example 2 In this embodiment, the historical routing protocol dataset of this routing node includes several routing protocol data pairs. Each routing protocol data pair includes routing protocol parameters. The route convergence time when using this routing protocol parameter and the routing control overhead when using this routing protocol parameters .

[0029] Specifically, the routing protocol parameters can be specific protocol configuration items or path selection weights to be optimized. For example, in the OSPF protocol, this parameter can correspond to the interface's Cost value; in distributed routing policies, it can correspond to the BGP Local Preference or MED attribute. By adjusting the path selection weights, the routing tendency of data traffic can be directly changed, thereby affecting the overall convergence performance of the network. The routing protocol parameters can also be protocol timers, specifically including Hello message sending interval (Hello Timer), neighbor failure determination time (Dead Timer), route update cycle, or retransmission timer, etc.

[0030] Specifically, the routing convergence time This refers to the application network protocol parameters. Then, the time required for the network to go from topology change to a consistent routing state across the entire network; the routing control overhead. This refers to the application network protocol parameters Then, to maintain the bandwidth or processing resources consumed for protocol operation, shortening the Hello timer can speed up fault detection and reduce route convergence time. However, it will send probe packets frequently, leading to increased control traffic and routing control overhead. Increase.

[0031] In this embodiment, before calculating the optimal routing protocol parameters, it is also necessary to initialize the optimal routing protocol parameters, including: Set upper bound for routing protocol parameter values Lower bounds of routing protocol parameter values and the number of candidate parameters Calculate the initial values ​​of the optimal routing protocol parameters. The expression is:

[0032] in, Indicates the index of the candidate parameter. .

[0033] Specifically, the upper bound of the routing protocol parameter values The maximum allowed values ​​for the parameters to be optimized are defined. For example, if the optimization target is the Hello message sending interval of the OSPF protocol, considering the real-time requirements of network-aware topology changes, the maximum allowed value can be... Set to 10 seconds; the lower bound of the routing protocol parameter value The minimum allowed values ​​for the parameters to be optimized are defined. To prevent excessively frequent protocol message transmission from causing CPU overload, the following can be implemented: The time is set to 1 second. In this embodiment, all initialized routing protocol parameters are strictly limited to 1 second. Within the specified range, protocol crashes caused by illegal parameters were avoided; utilizing Random numbers ensure a uniform distribution of candidate parameters within the search space, effectively reducing the risk of the algorithm getting trapped in local optima. This scheme successfully maps abstract routing parameter values ​​to the "orbit semi-major axis" in the Hohmann transfer model, laying a mathematical foundation for subsequent simulation of double-pulse orbit transfer and calculation of the transfer orbit step size.

[0034] In this embodiment, the step of iteratively calculating the optimal routing protocol parameters based on the Hohmann transition optimization algorithm includes the following steps: S21. Set gravity parameters Maximum number of iterations First weight Second weight Let the number of iterations be... The optimal solution for the semi-major axis of the initialization routing protocol parameters =0; S22. Read the route convergence time and route control overhead from the routing protocol data pairs, and calculate the trajectory metric function for each candidate parameter. The expression is:

[0035] in, This indicates that when the routing protocol parameter takes the value At that time, the route convergence time obtained based on routing protocol data is... This indicates that when the routing protocol parameter takes the value At that time, the routing control overhead is based on the routing protocol data. S23. Calculate the optimal solution for the semi-major axis of the current routing protocol parameters. The expression is:

[0036] S24. Determine the number of iterations Has the maximum number of iterations been exceeded? If not, proceed to step S25; if yes, use the current routing protocol parameters. As the optimal routing protocol parameter; S25. Calculate the first impulse of all candidate parameters. The expression is:

[0037] in, Represents a saturation function. Indicates the first pulse transition factor. , The theoretical semi-major axis represents the candidate parameter transition path, which is the average of the current routing protocol parameters and the optimal routing protocol parameters. ; S26. Based on the first pulse, perform a first pulse transition on all candidate parameters and calculate the values ​​of all candidate parameters after the first pulse transition. The expression is:

[0038] S27. Calculate the second pulse for all candidate parameters. The expression is:

[0039] in, Indicates the second pulse transition factor. ; S28. Based on the second pulse, perform a second pulse transition on all candidate parameters and calculate the values ​​of all candidate parameters after the second pulse transition. The expression is: ; S29. Order And return to S22.

[0040] Specifically, the flowchart illustrating the process of iteratively calculating the optimal routing protocol parameters for this routing node using the Hohmann transition algorithm based on the routing convergence time and routing control overhead in the routing protocol data pair is shown below. Figure 2 As shown, this embodiment applies the Hohmann transfer algorithm to iterative calculations to obtain optimal routing protocol parameters. The Hohmann transfer algorithm is a flight path algorithm that minimizes fuel consumption when a spacecraft switches between two circular orbits with different radii. This application transfers the Hohmann transfer algorithm to iterative calculations to obtain optimal routing protocol parameters, enabling the parameters to simultaneously shorten the routing convergence time and reduce routing control overhead. In the Hohmann transfer algorithm, the spacecraft corresponds to candidate parameters. The spacecraft obtains the ideal orbital semi-major axis and enters the target orbit through two pulses. The candidate parameters are used to obtain the optimal solution of the routing protocol parameters under the current iteration through the first pulse transfer step size and the second pulse transfer step size, respectively.

[0041] In this embodiment, step S22, which involves reading the route convergence time and route control overhead in the route protocol data pair, further includes: Search the current routing protocol data pair to see if it contains the current routing protocol parameters. If a data pair exists, then read the route convergence time and route control overhead from that data pair. If not, retrieve the upper limit neighborhood routing protocol parameter and the lower limit neighborhood routing protocol parameter that are closest to the current routing protocol parameter; Obtain the route convergence time and route control overhead corresponding to the upper limit neighborhood routing protocol parameters and the lower limit neighborhood routing protocol parameters, respectively; Calculate the average route convergence time and average route control overhead corresponding to the upper and lower limit neighborhood routing parameters, and use the obtained averages as the route convergence time of the current routing protocol parameters. and routing control overhead .

[0042] Specifically, this embodiment searches for the two "neighbors" in the dataset that are numerically closest to the candidate parameter. The value that is slightly larger than the candidate parameter and is the closest is defined as the upper limit neighborhood routing protocol parameter. The value that is slightly smaller than and closest to the candidate parameter is defined as the lower bound neighborhood routing protocol parameter. ; Retrieve Corresponding performance indicators as well as Corresponding performance indicators ; The mean calculation logic is used to arithmetically average the performance metrics of the upper and lower bound neighborhoods to obtain the current routing protocol parameters. The route convergence time and route control overhead are calculated using the following expression:

[0043]

[0044] The obtained route convergence time and route control overhead will be used as parameters of the current routing protocol. The route convergence time and route control overhead in this iteration are used to make optimization judgments based on the input track metric function.

[0045] This application not only stores the measured routing data pairs, but also has the ability to infer and evaluate the performance of unknown parameters. If the current candidate parameter value has not been recorded in the historical routing protocol dataset, a neighborhood search mechanism will be initiated to perform performance evaluation by inferring the unknown from the known, thus avoiding the interruption of the optimization process due to data loss.

[0046] In this embodiment, step S3, which involves negotiating and modifying the routing protocol parameters of all neighboring routing nodes, includes: S31. Encapsulate the optimal routing protocol parameters of this routing node into a routing parameter negotiation message, and send the message to all neighboring routing nodes connected to the target port; S32. Receive routing protocol parameter acknowledgment messages from all neighboring routing nodes; S33. Send a routing protocol parameter modification execution message to the neighboring routing node, and modify the routing protocol parameters of the corresponding port of this node.

[0047] In this embodiment, step S32 further includes: S321. Determine whether routing protocol parameter acknowledgment messages have been received from all neighboring routing nodes. If received, proceed to S33. If no acknowledgment messages are received from all neighboring routing nodes, then execute S322; S322. Determine whether the number of retransmissions exceeds the preset retransmission threshold. If it does not exceed the retransmission threshold, retransmit the negotiation message to the unresponsive neighbor routing node, increment the number of retransmissions by one, and return to S321. If the retransmission threshold is exceeded, the negotiation is deemed to have failed, the current routing protocol parameter update is terminated, and the original routing protocol parameters are maintained.

[0048] In this embodiment, the neighboring routing node receives a routing parameter negotiation message and sends a routing parameter confirmation message back to the local routing node; Receive routing parameter modification execution messages and synchronously modify routing protocol parameters with this routing node.

[0049] Specifically, the flowchart illustrating the issuance and activation of the optimal routing protocol parameters is as follows: Figure 3As shown, with node 1 as the local routing node and node 2 as the neighboring routing node, after generating new routing parameters, node 1 sends a routing parameter negotiation message to node 2, and node 2 sends a routing parameter confirmation message to node 1. After receiving the routing parameter confirmation message, node 1 modifies its own routing protocol parameters and sends a routing parameter modification execution message to node 2 to instruct node 2 to modify the routing protocol parameters.

[0050] Specifically, during the optimal routing protocol parameter distribution and activation phase, this routing node ensures network topology stability by executing a rigorous distributed coordination process. First, the routing node invokes the communication interface module to encapsulate the optimal routing protocol parameters, obtained through the aforementioned iterative calculations, into a pre-formatted routing parameter negotiation message. This negotiation message typically includes a parameter type identifier, the optimal parameter value, and a unique serial number used to track this configuration task. Subsequently, this node sends the negotiation message through a physical port or logical sub-interface to all neighboring routing nodes connected to its port, ensuring that all related nodes within the local topology are aware in advance of the impending parameter changes.

[0051] After sending the negotiation message, this routing node enters a listening state, receiving and parsing routing protocol parameter confirmation messages from all neighboring routing nodes in real time. This step establishes a reliable confirmation mechanism, ensuring that all neighboring nodes have the technical capabilities to process the new parameters under the current service load and are ready for synchronous switching. Once this node has received all confirmation messages from all neighboring nodes within the preset response time window, it proves that the entire network has reached a consensus on the modification, and then proceeds to the final execution phase.

[0052] During the execution phase, the local routing node sends a routing protocol parameter modification execution message to all neighboring routing nodes. This execution message serves as the final effective instruction, guiding neighboring nodes to immediately apply the new routing parameters. Simultaneously with sending this execution message, the local routing node synchronously modifies the routing protocol parameters of its corresponding ports, achieving synchronized parameter transitions between the local node and all neighboring nodes within milliseconds. Through this three-stage control logic based on "proposal—confirmation—synchronous execution," this invention ensures that the protocol timers or path weights among neighboring nodes remain consistent throughout the parameter optimization process. This eliminates network faults such as routing loops, protocol oscillations, or data packet misdirection caused by asynchronous configuration updates, achieving a smooth transition of the routing protocol during dynamic optimization.

[0053] Example 3 In this embodiment, taking the calculation of the optimal value of the routing protocol timer as an example, the routing protocol parameter is the routing protocol timer, and the spacecraft is the number of candidate parameters. Maximum number of iterations The historical routing protocol dataset includes:

[0054] The process of the routing protocol optimization method based on Hohmann transition is as follows: Set upper bound for routing protocol parameter values Lower bounds of routing protocol parameter values , Based on the initial values ​​of the semi-major axis of the current orbits of each spacecraft, respectively , , ; Set gravity parameters Maximum number of iterations Number of spacecraft Initialize the number of iterations First weight Second ; optimal solution for semi-major axis Initialize to 0.

[0055] Based on the training data, when the routing protocol parameter is 4, the routing convergence time is 5 and the control overhead is 40. When the routing protocol parameter is 2, since there are no historical data pairs with this value, the average method is simply used. Based on the routing convergence time and control overhead of routing protocol parameters 1 and 3, the routing convergence time of routing protocol parameter 2 is estimated to be 2, and the control overhead is estimated to be 85. When the routing protocol parameter is 7, the routing convergence time is 8 and the control overhead is 30. Therefore, according to the expression:

[0056] The orbital metric functions for each spacecraft are as follows: , ,

[0057] Then calculate the optimal solution for the semi-major axis of the current routing protocol parameters. for:

[0058] At this point, the number of iterations... Not exceeded the maximum number of iterations ; Calculate the first pulse transition factor and the current routing protocol parameters respectively. The average value of the optimal routing protocol parameters is:

[0059] , ,

[0060] The first pulse transfer step size for each spacecraft can be calculated as follows: , ,

[0061] Calculate the values ​​of each spacecraft after the first pulse transfer: , ,

[0062] Calculate the second pulse transfer step size for each spacecraft:

[0063] , ,

[0064] Calculate the values ​​of the second pulse transfer for each spacecraft. : , ,

[0065] Update iteration count, ; Return to resolving the optimal values ​​of the orbital metric function and semi-major axis: , ,

[0066]

[0067] At this point, the number of iterations... Not exceeded the maximum number of iterations ; The first pulse transition factor and the average of the current routing protocol parameters and the optimal routing protocol parameters in the second iteration are calculated as follows: , , ,

[0068] The calculation yields the first pulse transfer step size for each spacecraft in the second iteration as follows: ,

[0069]

[0070] Calculate the values ​​of each spacecraft after the first pulse transfer: , ,

[0071] Calculate the second pulse transfer step size for each spacecraft: , , ,

[0072] Calculate the values ​​of the second pulse transfer for each spacecraft. : , ,

[0073] Update iteration count, ; Step 13: Solving for the optimal values ​​of the orbital metric function and semi-major axis: , ,

[0074]

[0075] At this point, the number of iterations... Not exceeded the maximum number of iterations The average values ​​of the first pulse transition factor and the current routing protocol parameters compared to the optimal routing protocol parameters for each spacecraft in the third iteration are calculated as follows: , , ,

[0076] The calculation yields the first pulse transfer step size for each spacecraft in the third iteration as follows: , ,

[0077] Calculate the value of the first pulse transfer for each spacecraft in the third iteration: , ,

[0078] Calculate the second pulse transfer step size for each spacecraft in the third iteration:

[0079] , ,

[0080] Calculate the value of the second pulse transfer after the third iteration for each spacecraft. : , ,

[0081] Update iteration count, ; Solve for the optimal values ​​of the orbital metric function and the semi-major axis: , ,

[0082]

[0083] at this time Output optimal routing protocol parameters .

[0084] Example 4 A routing protocol optimization system for a network switching system, the structural diagram of which is shown below. Figure 4 The routing protocol optimization system shown includes a data base module, a routing protocol parameter inference and decision module, and a routing protocol parameter negotiation and adjustment module; The output of the data base module is connected to the input of the routing protocol parameter inference and decision module, and the routing protocol parameter inference and decision module receives the routing protocol data pairs output by the data base module. The output of the routing protocol parameter inference and decision module is connected to the input of the routing protocol parameter negotiation and adjustment module, and the routing protocol parameter negotiation and adjustment module receives the optimal routing protocol parameters output by the routing protocol parameter inference and decision module.

[0085] Example 5 In this embodiment, a computer device is proposed, comprising a memory 101, a processor 102, and a computer program stored in the memory 101 that can be executed by the processor. The processor 102 executes the computer program to implement a routing parameter optimization method based on the Hohmann transition optimization algorithm. A schematic diagram of the device is shown below. Figure 5 As shown.

[0086] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the implementation of the present invention. Those skilled in the art can make other variations or modifications based on the above description. It is neither necessary nor possible to exhaustively describe all embodiments here. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the claims of the present invention.

Claims

1. A routing parameter optimization method based on the Hohmann transition optimization algorithm, wherein the routing parameter optimization method is applied to a network switching system, the network switching system comprising a plurality of routing nodes, characterized in that, Includes the following steps: S1. Initialize the routing nodes in the network switching system; S2. When a routing node in the network switching system needs to adjust its routing protocol parameters, it reads routing protocol data pairs from the historical routing protocol dataset of the routing node and iteratively calculates the optimal routing protocol parameters based on the Hohmann transition optimization algorithm. S3. Send the optimal routing protocol parameters of this routing node to all neighboring routing nodes that have port connections with this routing node. Based on the optimal routing protocol parameters of this routing node, modify the routing protocol parameters of all neighboring routing nodes to complete the routing protocol optimization.

2. The routing parameter optimization method based on the Hohmann transition optimization algorithm according to claim 1, characterized in that, The historical routing protocol dataset of this routing node includes several routing protocol data pairs. Each routing protocol data pair includes routing protocol parameters. The route convergence time when using this routing protocol parameter and the routing control overhead when using this routing protocol parameters .

3. The routing parameter optimization method based on the Hohmann transition optimization algorithm according to claim 2, characterized in that, Before calculating the optimal routing protocol parameters, it is also necessary to initialize the optimal routing protocol parameters, including: Set upper bound for routing protocol parameter values Lower bounds of routing protocol parameter values and the number of candidate parameters Calculate the initial values ​​of the optimal routing protocol parameters. The expression is: in, Indicates the index of the candidate parameter. .

4. The routing parameter optimization method based on the Hohmann transition optimization algorithm according to claim 3, characterized in that, The process of iteratively calculating the optimal routing protocol parameters based on the Hohmann transition optimization algorithm includes the following steps: S21. Set gravity parameters Maximum number of iterations First weight Second weight Let the number of iterations be... The optimal solution for the semi-major axis of the initialization routing protocol parameters =0; S22. Read the route convergence time and route control overhead from the routing protocol data pairs, and calculate the trajectory metric function for each candidate parameter. The expression is: in, This indicates that when the routing protocol parameter takes the value At that time, the route convergence time obtained based on routing protocol data is... This indicates that when the routing protocol parameter takes the value At that time, the routing control overhead is based on the routing protocol data. S23. Calculate the optimal solution for the semi-major axis of the current routing protocol parameters. The expression is: S24. Determine the number of iterations Has the maximum number of iterations been exceeded? If not, proceed to step S25; if yes, use the current routing protocol parameters. As the optimal routing protocol parameter; S25. Calculate the first impulse of all candidate parameters. The expression is: in, Represents a saturation function. Indicates the first pulse transition factor. , The theoretical semi-major axis represents the candidate parameter transition path, which is the average of the current routing protocol parameters and the optimal routing protocol parameters. ; S26. Based on the first pulse, perform a first pulse transition on all candidate parameters and calculate the values ​​of all candidate parameters after the first pulse transition. The expression is: S27. Calculate the second pulse for all candidate parameters. The expression is: in, Indicates the second pulse transition factor. ; S28. Based on the second pulse, perform a second pulse transition on all candidate parameters and calculate the values ​​of all candidate parameters after the second pulse transition. The expression is: ； S29. Order And return to S22.

5. The routing parameter optimization method based on the Hohmann transition optimization algorithm according to claim 4, characterized in that, Step S22, which involves reading the route convergence time and route control overhead from the routing protocol data pair, further includes: Search the current routing protocol data pair to see if it contains the current routing protocol parameters. If a data pair exists, then read the route convergence time and route control overhead from that data pair. If not, retrieve the upper limit neighborhood routing protocol parameter and the lower limit neighborhood routing protocol parameter that are closest to the current routing protocol parameter; Obtain the route convergence time and route control overhead corresponding to the upper limit neighborhood routing protocol parameters and the lower limit neighborhood routing protocol parameters, respectively; Calculate the average route convergence time and average route control overhead corresponding to the upper and lower limit neighborhood routing parameters, and use the obtained averages as the route convergence time of the current routing protocol parameters. and routing control overhead .

6. The routing parameter optimization method based on the Hohmann transition optimization algorithm according to claim 5, characterized in that, Step S3, which involves modifying the routing protocol parameters of all neighboring routing nodes, includes: S31. Encapsulate the optimal routing protocol parameters of this routing node into a routing parameter negotiation message, and send the message to all neighboring routing nodes connected to the target port; S32. Receive routing protocol parameter acknowledgment messages from all neighboring routing nodes; S33. Send a routing protocol parameter modification execution message to the neighboring routing node, and modify the routing protocol parameters of the corresponding port of this node.

7. The routing parameter optimization method based on the Hohmann transition optimization algorithm according to claim 6, characterized in that, Step S32 also includes: S321. Determine whether routing protocol parameter acknowledgment messages have been received from all neighboring routing nodes. If received, proceed to S33. If no acknowledgment messages are received from all neighboring routing nodes, then execute S322; S322. Determine whether the number of retransmissions exceeds the preset retransmission threshold. If it does not exceed the retransmission threshold, retransmit the negotiation message to the unresponsive neighbor routing node, increment the number of retransmissions by one, and return to S321. If the retransmission threshold is exceeded, the negotiation is deemed to have failed, the current routing protocol parameter update is terminated, and the original routing protocol parameters are maintained.

8. The routing parameter optimization method based on the Hohmann transition optimization algorithm according to claim 7, characterized in that, The neighboring routing node receives the routing parameter negotiation message and sends a routing parameter confirmation message back to the local routing node. Receive routing parameter modification execution messages and synchronously modify routing protocol parameters with this routing node.

9. A routing parameter optimization system based on the Hohmann transfer optimization algorithm, characterized in that, The routing protocol optimization system includes a data base module, a routing protocol parameter inference and decision module, and a routing protocol parameter negotiation and adjustment module. The output of the data base module is connected to the input of the routing protocol parameter inference and decision module, and the routing protocol parameter inference and decision module receives the routing protocol data pairs output by the data base module. The output of the routing protocol parameter inference and decision module is connected to the input of the routing protocol parameter negotiation and adjustment module, and the routing protocol parameter negotiation and adjustment module receives the optimal routing protocol parameters output by the routing protocol parameter inference and decision module.

10. A computer device, characterized in that, The computer device includes a memory, a processor, and a computer program stored in the memory that can be run on the processor, wherein the processor executes the computer program to implement the method according to any one of claims 1 to 8.

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