Task scheduling method and device for heterogeneous star cluster in dynamic scenario, medium and equipment

Abstract

The application discloses a task scheduling method and device for a heterogeneous star cluster in a dynamic scenario, a medium and equipment. The method comprises the following steps: taking the maximum profit of the heterogeneous star cluster as a target, constructing a task scheduling model for the heterogeneous star cluster in the dynamic scenario based on core constraint conditions, wherein the core constraint conditions are used to reduce alliance disturbance and protect individual profits in the task allocation process; determining a candidate alliance that can undertake a to-be-allocated task based on the task scheduling model; and allocating the to-be-allocated task to a target satellite management agency in the candidate alliance based on the Shapley value of the to-be-allocated task and the number of effective visible time windows of the candidate satellite management agency. The method reduces the disturbance risk in the alliance, effectively avoids the disintegration or reorganization of the alliance caused by uneven income distribution, promotes the long-term stability of the alliance in the task scheduling process, and improves the task execution effect and service level of the entire heterogeneous star cluster in the dynamic scenario.

Description

Technical Field

[0001] This application relates to the field of constellation mission planning and scheduling technology, and in particular to a mission scheduling method, apparatus, medium and device for heterogeneous constellations in dynamic scenarios. Background Technology

[0002] In recent years, with the continuous advancement of aerospace technology, the cost of satellite launches has become increasingly lower. More and more government departments, enterprises and other satellite control agencies have launched their own Earth imaging observation satellites or constellations, forming a large-scale heterogeneous constellation in space.

[0003] Because each satellite control agency pursues its own profit maximization, limited large-scale mission orders become a resource that they compete for, resulting in complex competitive relationships. Meanwhile, satellites under the same control agency may collaborate. Furthermore, authority barriers exist between different satellite control agencies, preventing cross-agency control over satellites belonging to other agencies.

[0004] Currently, large-scale heterogeneous constellation collaborative cooperation in dynamic scenarios still faces the following challenges: 1) Existing dynamic scenarios primarily consider the dynamic arrival of missions, rarely taking into account disturbances during mission planning. They do not consider the individual benefits of satellite control agencies and rarely consider disturbances that occur after planning. 2) The mission planning problem for large-scale heterogeneous constellation collaboration in dynamic scenarios is more complex. Traditional algorithms cannot effectively balance minimizing dynamic scenario disturbances with ensuring that the benefits of satellite control agencies are not lost. Summary of the Invention

[0005] In view of this, this application provides a method, apparatus, medium and equipment for mission scheduling of heterogeneous satellite constellations in dynamic scenarios, which achieves a balance between the individual benefits of satellite control agencies and the overall benefits of the alliance.

[0006] According to one aspect of this application, a task scheduling method for heterogeneous star clusters in dynamic scenarios is provided, comprising: With the goal of maximizing the benefits of heterogeneous constellations, a task scheduling model for heterogeneous constellations in dynamic scenarios is constructed based on core constraints. The core constraints are used to reduce coalition disturbances and protect individual benefits during task allocation. Based on the task scheduling model, candidate alliances capable of undertaking and assigning tasks are determined, wherein the tasks to be assigned are generated by the dynamic perturbation of heterogeneous constellations, and the candidate alliances include at least one candidate satellite management agency. Based on the Shapley value of the task to be assigned and the number of effective visible time windows for the candidate satellite management agencies, the task to be assigned is assigned to the target satellite management agency in the candidate alliance, wherein the effective visible time windows satisfy the relaxed insertion principle.

[0007] Optionally, assigning the task to a target satellite management agency in the candidate consortium based on the Shapley value and the number of valid visible time windows of the task to be assigned by the candidate satellite management agency includes: The target satellite control agency is selected from the candidate consortium based on the Shapley value; Based on the Shapley value and the number of effective visible time windows, the target satellite control agency calculates the expected value of the task to be assigned. The task to be assigned is inserted into the satellite mission sequence managed by the target satellite control agency with the highest expected value.

[0008] Optionally, the step of screening the target satellite control agency from the candidate consortium based on the Shapley value includes: Obtain the original revenue value of the candidate satellite management agency for the task to be assigned in a nuclear alliance under static scenarios; Based on the relationship between the Shapley value and the original revenue value, the candidate satellite management agency in the candidate alliance that is qualified to bid is selected as the target satellite management agency.

[0009] Optionally, calculating the target satellite control agency's expected value for the task to be assigned, based on the Shapley value and the quantity, includes: The priority weight of the candidate satellite management agency is determined based on the difference between the Shapley value and the original benefit value of the candidate satellite management agency for the task to be assigned in a nuclear alliance under static scenarios. The quantity is updated based on the priority weight; The expected value is calculated as the quotient of the updated quantity and the total number of valid visible time windows for the candidate alliance to the task to be assigned.

[0010] Optionally, the core constraints include: Individual rational constraints are expressed as: ; Alliance rational constraints are expressed as: ; The task scheduling model is also configured with basic constraints, which include: The matching constraint between mission payload requirements and satellite payload type is expressed as: ; The maximum power-on time constraint per satellite orbit is expressed as: ; The uniqueness constraint of mission observations is expressed as: ; The observation time constraint is expressed as: , , , ; The satellite's conversion time constraint is expressed as: , =1, , , ; The maximum power-on time constraint for each satellite orbit is expressed as: ; In the formula, This indicates the satellite control agency after task allocation. k The benefits; f k This indicates that the nuclear alliance satellite control agency k The benefits; v ( S ) indicates alliance S The benefits; Indicates alliance S Tasks to be assigned; This indicates a nuclear alliance; R S Indicates alliance S Satellites that can be used to perform missions; T i Indicates satellite i Observable tasks; Indicates satellite i In the u A time window for the task j Decision variables; Z j Indicates task j Load requirement related parameters; Q io Indicates satellite i Maximum operating time per lap; b Indicates the start time of observation; e Indicates the end time of the observation; t Indicates the duration of mission observation; l Indicates the duration of task observation; Indicates satellite i For the task j In the u The visible time window of a time window; θ Indicates the minimum operating time of the satellite; g Indicates the conversion time; q il Indicates task l Following the mission j Decision variables to be observed; τThis indicates the maximum operating time for each satellite orbit.

[0011] Optionally, the relaxation insertion criterion includes the basic constraints and the upper and lower bound constraints of the satellite control agency's revenue.

[0012] Optionally, the task scheduling method for heterogeneous constellations in dynamic scenarios also includes: The Shapley value is calculated based on the marginal contribution and occurrence probability of the candidate satellite management agency for the assigned task.

[0013] According to another aspect of this application, a task scheduling device for heterogeneous constellations in dynamic scenarios is provided, comprising: The module is used to construct a task scheduling model for heterogeneous constellations in a dynamic scenario with the goal of maximizing the benefits of heterogeneous constellations, based on core constraints. The core constraints are used to reduce coalition disturbances and protect individual benefits during the task allocation process. The task allocation module is used to determine candidate alliances capable of accepting and allocating tasks based on the task scheduling model, wherein the tasks to be allocated are generated by dynamic perturbations of heterogeneous constellations, and the candidate alliances include at least one candidate satellite management agency; and to allocate the tasks to be allocated to target satellite management agencies in the candidate alliances based on the Shapley value of the tasks to be allocated and the number of effective visible time windows of the candidate satellite management agencies, wherein the effective visible time windows satisfy the relaxation insertion principle.

[0014] Optionally, the task allocation module is specifically used to filter the target satellite management agency from the candidate consortium based on the Shapley value; calculate the expected value of the target satellite management agency for the task to be allocated based on the Shapley value and the number of valid visible time windows; and insert the task to be allocated into the satellite task sequence managed by the target satellite management agency with the largest expected value.

[0015] Optionally, the task allocation module is specifically used to obtain the original revenue value of the candidate satellite management agency in the nuclear alliance under static scenarios for the task to be allocated; based on the relationship between the Shapley value and the original revenue value, the candidate satellite management agency in the candidate alliance that is qualified to bid is selected as the target satellite management agency.

[0016] Optionally, the task allocation module is specifically used to determine the priority weight of the candidate satellite management agency based on the difference between the Shapley value and the original benefit value of the candidate satellite management agency in the nuclear consortium under static scenarios for the task to be allocated; update the quantity based on the priority weight; and calculate the quotient of the updated quantity and the total number of effective visible time windows of the candidate consortium for the task to be allocated as the expected value.

[0017] Optionally, the core constraints include: Individual rational constraints are expressed as: ; Alliance rational constraints are expressed as: ; The task scheduling model is also configured with basic constraints, which include: The matching constraint between mission payload requirements and satellite payload type is expressed as: ; The maximum power-on time constraint per satellite orbit is expressed as: ; The uniqueness constraint of mission observations is expressed as: ; The observation time constraint is expressed as: , , , ; The satellite's conversion time constraint is expressed as: , =1, , , ; The maximum power-on time constraint for each satellite orbit is expressed as: ; In the formula, This indicates the satellite control agency after task allocation. k The benefits; f k This indicates that the nuclear alliance satellite control agency k The benefits; v ( S ) indicates alliance S The benefits; Indicates alliance S Tasks to be assigned; This indicates a nuclear alliance; R S Indicates alliance S Satellites that can be used to perform missions; T i Indicates satellite i Observable tasks; Indicates satellite i In the u A time window for the task j Decision variables; Z j Indicates task j Load requirement related parameters; Q io Indicates satellite i Maximum operating time per lap; b Indicates the start time of observation; e Indicates the end time of the observation; t Indicates the duration of mission observation; l Indicates the duration of task observation; Indicates satellite i For the task j In the u The visible time window of a time window; θ Indicates the minimum operating time of the satellite; g Indicates the conversion time; q il Indicates task l Following the mission j Decision variables to be observed; τ This indicates the maximum operating time for each satellite orbit.

[0018] Optionally, the relaxation insertion criterion includes the basic constraints and the upper and lower bound constraints of the satellite control agency's revenue.

[0019] Optionally, the task allocation module is further configured to calculate the Shapley value based on the marginal contribution and occurrence probability of the candidate satellite management agency for the task to be allocated.

[0020] According to another aspect of this application, a readable storage medium is provided, on which a program or instructions are stored, which, when executed by a processor, implement the steps of the above-described task scheduling method for heterogeneous constellations in dynamic scenarios.

[0021] According to another aspect of this application, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the above-described task scheduling method for heterogeneous constellations in dynamic scenarios.

[0022] Using the aforementioned technical solutions, this paper deeply analyzes the impact mechanism of temporary mission changes on the alliance structure and individual benefits of satellite control agencies, and constructs a mission scheduling model. This model optimizes resource utilization and mission allocation as a whole, ensuring that the allocation scheme of newly added unassigned missions output by the mission scheduling model protects the benefits obtainable by any satellite control agency. This reduces the risk of disturbance within the alliance, effectively preventing alliance disintegration or reorganization due to uneven benefit distribution, and promoting long-term alliance stability during mission scheduling. Furthermore, unassigned missions are modeled as auction items. Taking full account of satellite time resource constraints, the Shapley value is used to meticulously measure the contribution of each candidate satellite control agency to the unassigned missions. This allows agencies with greater contributions to mission benefits to undertake more missions, ensuring that agencies with larger marginal contributions receive reasonable benefits, thereby improving overall benefits. Ultimately, this maximizes the execution quality and success rate of unassigned missions, improving the mission execution effect and service level of the entire heterogeneous constellation in dynamic scenarios.

[0023] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0024] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1 A flowchart illustrating the task scheduling method for heterogeneous constellations in a dynamic scenario provided in an embodiment of this application is shown. Figure 2 This paper shows a structural block diagram of a task scheduling device for heterogeneous star clusters in a dynamic scenario provided in an embodiment of this application. Figure 3 This paper presents a schematic diagram comparing the benefits of satellite control agencies with Shapley values ​​before and after task reallocation in a dynamic scenario, as shown in an embodiment of this application. Figure 4 This illustration shows a comparison of the increase in the number of tasks for the satellite control agency before and after task reallocation in a dynamic scenario, as shown in an embodiment of this application. Figure 5 A schematic diagram of the electronic structure of a computer device provided in an embodiment of this application is shown. Detailed Implementation

[0025] The present application will be described in detail below with reference to the accompanying drawings and embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in the embodiments of the present application can be combined with each other.

[0026] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain this application, and should not be construed as limiting this application.

[0027] Those skilled in the art will understand that, unless specifically stated otherwise, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be further understood that the term “comprising” as used in this application means the presence of the stated features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. It should be understood that when we say an element is “connected” or “attached” to another element, it can be directly connected or attached to the other element, or there may be intermediate elements. Furthermore, “connected” or “attached” as used herein can include wireless connections or wireless interconnections. The term “and / or” as used herein includes all or any unit and all combinations of one or more associated listed items.

[0028] Exemplary embodiments according to this application will now be described in more detail with reference to the accompanying drawings. However, these exemplary embodiments may be implemented in many different forms and should not be construed as being limited to the embodiments set forth herein. It should be understood that these embodiments are provided so that the disclosure of this application is thorough and complete, and that the concept of these exemplary embodiments is fully conveyed to those skilled in the art.

[0029] This embodiment provides a task scheduling method for heterogeneous star clusters in dynamic scenarios, such as Figure 1 As shown, the method includes: Step 101: With the goal of maximizing the benefits of heterogeneous star clusters, construct a task scheduling model for heterogeneous star clusters in a dynamic scenario based on core constraints.

[0030] This refers to a constellation of satellites of different types and functions (such as high-resolution imaging satellites, synthetic aperture radar satellites, communication relay satellites, and electronic reconnaissance satellites). A dynamic scenario refers to a scenario where, based on a static scenario, uncertainties arise regarding missions and satellites. This includes situations where, after the initial mission planning, some satellite management agencies add emergency missions or suddenly cancel missions, or even experience emergency situations such as satellite failures. Core constraints are used to reduce alliance disturbances and protect individual benefits during mission allocation.

[0031] In this embodiment, based on static task allocation, and with the goal of maximizing the benefits of heterogeneous constellations, a task scheduling model for heterogeneous constellations in dynamic scenarios is constructed by introducing core constraints. When unexpected tasks occur, the system automatically selects the task allocation combination that brings the maximum total benefit, thereby enabling reasonable allocation of benefits in dynamic scenarios, protecting individual interests, preventing individuals / sub-alliances from having an incentive to leave, reducing alliance disturbances, and ensuring alliance stability during task redistribution.

[0032] Specifically, the core constraints include: individual rationality constraints and coalition rationality constraints.

[0033] The individual rationality constraint means that after the redistribution and replanning of the tasks to be assigned, the revenue of each satellite control agency cannot be higher than the original revenue allocated to each satellite control agency by the nuclear consortium during the task allocation phase in a static scenario, expressed as: .

[0034] The rational constraint of the alliance means that after the core alliance redistributes and replans the assigned tasks, the sum of the income of any sub-alliance member is not less than the income of the sub-alliance operating alone, expressed as: .

[0035] In the formula, This indicates the satellite control agency after task allocation. k The benefits; f k This indicates that the nuclear alliance satellite control agency k The benefits; v ( S ) indicates alliance S The benefits; Indicates alliance S Tasks to be assigned; It signifies a nuclear alliance.

[0036] It is worth mentioning that, in addition to the core constraints ensuring the stability of the alliance structure and the rationality of profit distribution in dynamic scenarios, necessary basic constraints for large-scale heterogeneous constellation collaborative mission planning can also be set, specifically including: The matching constraint between mission payload requirements and satellite payload type is expressed as: .

[0037] The maximum power-on time constraint per satellite orbit is expressed as: .

[0038] The task observation uniqueness constraint, meaning that the task to be assigned can only be observed once, is expressed as: .

[0039] The observation time constraint, which states that the task observation start time must be earlier than the start time of the visible time window, is expressed as: Furthermore, the task's observation end time must be earlier than the end time of the visible time window. This is represented as: Furthermore, the duration of each satellite power-on session must not be less than the satellite's minimum power-on duration, expressed as: , .

[0040] When observation task l Following the observation mission j On the satellite i The satellite's conversion time constraint during observation is expressed as: , =1, , , .

[0041] in, , Indicates task j and tasks l The angle of attitude transition between tasks is determined by the task. j Pointing angle at the end of observation and the task l The pointing angle at the start of observation is calculated using the following formula. The pointing angle of the task is represented by a vector over time (...). α ( t ) ,β ( t ) ,χ ( t ))express. Specifically: α represents the satellite pitch angle, β represents the yaw angle, and χ represents the roll angle.

[0042] The maximum power-on time constraint for each satellite orbit is expressed as: .

[0043] In the formula, R S Indicates alliance S Satellites that can be used to perform missions; T i Indicates satellite i Observable tasks; Indicates satellite i In the u A time window for the task j Decision variables; Z j Indicates task j Load requirement related parameters; Q io Indicates satellite i Maximum operating time per lap; b Indicates the start time of observation; eIndicates the end time of the observation; t Indicates the duration of mission observation; l Indicates the duration of task observation; Indicates satellite i For the task j In the u The visible time window of a time window; θ Indicates the minimum operating time of the satellite; g Indicates the conversion time; q il Indicates task l Following the mission j Decision variables to be observed; τ This indicates the maximum power-on time for each satellite orbit; the maximum power-on time varies for each type of satellite.

[0044] Step 102: Determine candidate alliances that can accept and assign tasks based on the task scheduling model.

[0045] The candidate consortium includes at least one candidate satellite management agency capable of undertaking task assignments. Tasks to be assigned are generated by dynamic perturbations of heterogeneous constellations. For example, in a static scenario, this could include tasks suddenly added by a satellite management agency, tasks canceled, redundant tasks from higher-yielding satellite management agencies, or unfinished tasks due to satellite failures. For instance, for satellite management agency k, its yield in a core-based consortium in a static scenario is... In dynamic scenarios where tasks change, the Shapley value in the alliance... That is, the benefits one should receive within the alliance. If... > Then the satellite control agency k The revenue needs to be The tasks are transferred out and added to the set of tasks to be assigned for reallocation.

[0046] Understandably, the task scheduling model can be solved using the Adaptive Large Neighborhood Search (ALNS) algorithm and the Core Solution-based cooperative task planning algorithm.

[0047] It is worth noting that the reallocation and replanning of assigned tasks need to consider three types of satellites: satellites from the same satellite management agency within the same nuclear alliance, satellites from different satellite management agencies within the same nuclear alliance, and satellites from different nuclear alliances. Since the revenue of a satellite management agency is the sum of the revenues from managing satellites to complete their tasks, assigning tasks to the first type of satellite does not require consideration of nuclear decomposition. However, assigning tasks to the second and third types of satellites requires consideration of nuclear decomposition; otherwise, it will alter the alliance's revenue distribution, causing instability and preventing the formation of a long-term stable cooperation mechanism.

[0048] Step 103: Based on the Shapley value of the task to be assigned and the number of effective visible time windows of the candidate satellite management agencies, assign the task to be assigned to the target satellite management agency in the candidate consortium.

[0049] The effective visible time window satisfies the relaxed insertion principle. The relaxed insertion criterion includes the aforementioned basic constraints and the upper and lower bound constraints on the revenue of satellite management agencies. The upper bound refers to the revenue of each satellite management agency after redistribution and replanning. No greater than the benefits in the existing nuclear alliance Since the sum of the upper limits of satellite control agencies in each nuclear alliance is the upper limit of the alliance function value, only the satellite control agencies need to be considered. The lower limit is to prevent satellite control agencies from abandoning cooperation due to excessively low returns within the nuclear alliance. When the returns for a satellite control agency are too low, it will disrupt the stability of the nuclear alliance, leading to its disintegration into multiple sub-alliances or individuals. Therefore, a lower limit for the returns of each satellite control agency is set during task redistribution and planning. ,Right now > ,at the same time The following constraints also need to be met: .

[0050] It should be noted that the Shapley value is used to measure the contribution or importance of each participant to the overall alliance in a cooperative game among multiple participants, in order to facilitate a fair distribution of benefits. The Shapley value can be calculated using existing formulas based on the marginal contribution and probability of occurrence of the candidate satellite control agency for the assigned mission, and this application does not impose specific limitations on it.

[0051] The task scheduling method for heterogeneous satellite constellations in dynamic scenarios provided in this application provides an in-depth analysis of the impact mechanism of temporary task changes on the alliance structure and individual benefits of satellite control agencies, and constructs a task scheduling model. This model is applicable to various processing scenarios. By utilizing the task scheduling model, resource utilization and the arrangement of large-scale satellite tasks (tens of thousands of satellites) are optimized as a whole. It ensures that the allocation scheme for newly added tasks protects the benefits obtainable by any satellite control agency, thereby reducing the risk of disturbance within the alliance and effectively avoiding alliance disintegration or reorganization due to uneven benefit distribution, promoting long-term alliance stability during task scheduling. Furthermore, tasks to be assigned are modeled as auction items. Based on full consideration of satellite time resource constraints, the Shapley value is used to meticulously measure the contribution of each candidate satellite control agency to the tasks to be assigned. Agencies with greater contributions to task benefits are assigned more tasks, ensuring that agencies with larger marginal contributions receive reasonable benefits, thereby improving overall benefits. This maximizes the execution quality and success rate of tasks to be assigned, improving the overall task execution effect and service level of the entire heterogeneous satellite constellation in dynamic scenarios.

[0052] It is understood that the task scheduling method for heterogeneous constellations in dynamic scenarios provided in this application embodiment can be applied to a terminal, a server, or software running on either a terminal or a server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, etc.; the server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms.

[0053] In one embodiment, step 103, which is to assign the tasks to be assigned to the target satellite management agencies in the candidate coalition based on the Shapley value of the tasks to be assigned and the number of effective visible time windows of the candidate satellite management agencies, specifically includes the following: Step 103-1: Select target satellite control agencies from the candidate consortium based on Shapley values.

[0054] In this embodiment, the Shapley value is used to comprehensively quantify the marginal contribution of each candidate alliance member to the task. This allows for an objective assessment of the marginal contribution of each management agency to the alliance's benefits without changing the alliance members, preventing high-benefit holders from continuously acquiring more tasks, maintaining a balance in collaboration, and improving overall resource utilization.

[0055] In practical application scenarios, the selection of target satellite control agencies from candidate consortia based on Shapley values ​​includes: obtaining the original revenue value of the candidate satellite control agencies in the nuclear consortium under static scenarios for the tasks to be assigned; and selecting the candidate satellite control agencies in the candidate consortia that are qualified to bid as target satellite control agencies based on the relationship between the Shapley value and the original revenue value.

[0056] It is understandable that in a nuclear-powered alliance under a static scenario, the original reward value for a task to be assigned is the reward that could be obtained after task assignment has been completed under the current alliance structure and fixed resource configuration in the static scenario. For newly added tasks that have not been assigned under the current static resource and environmental constraints, the original reward value is the minimum reward; for tasks that have not been completed due to reasons such as satellite failure, the original reward value is the expected total reward that should have been obtained when the task was completed.

[0057] In this embodiment, based on the new consortium (candidate consortium) planned for the tasks to be assigned, the Shapley value of each candidate satellite management agency is calculated, along with the difference between this Shapley value and the revenue of the original core consortium. If the difference is greater than 0, it indicates that the candidate satellite management agency is likely to experience a reduction in revenue, and thus the candidate satellite management agency is eligible to become a bidder for the tasks to be assigned. If the difference is less than or equal to 0, it indicates that the candidate satellite management agency's revenue is too high, and continuously obtaining more revenue through observation tasks would lead to a decrease in the revenue of some agencies in the consortium; therefore, it is determined that the candidate satellite management agency cannot become a bidder. This reduces cooperation friction caused by unfair revenue distribution and ensures the long-term stability of the constellation consortium.

[0058] Step 103-2: Based on the Shapley value and the number of effective visible time windows, calculate the expected value of the target satellite control agency for the assigned tasks.

[0059] In practical application scenarios, step 103-2 specifically includes: determining the priority weight of the candidate satellite management agency based on the difference between the Shapley value and the original revenue value of the candidate satellite management agency in the nuclear alliance under static scenarios; updating the quantity based on the priority weight; and calculating the quotient of the updated quantity and the total number of effective visible time windows for the candidate alliance to be assigned as the expected value.

[0060] Specifically, based on the Shapley value and quantity, the expected value of the target satellite control agency for the assigned tasks is calculated as follows: ; In the formula, P represents the expected value. Indicates satellite control agency k Shapley value for assigning tasks. f k Indicates satellite control agency kThe original revenue value in a core-based alliance under static scenarios. Indicates satellite control agency k Task assignment i The number of effective visible time windows, The candidate alliance indicated its attitude towards task allocation. i The total number of valid visible time windows.

[0061] When satellite control agency k For the auction task i The number of effective visible time windows that satisfy the relaxation insertion principle When the value is 0, the agency's bidding expectation for the task is 0. When the satellite control agency... k For the auction task i The number of effective visible time windows that satisfy the relaxation insertion principle When the value is not equal to 0, the greater the quantity, the greater the expectation.

[0062] Step 103-3: Insert the task to be assigned into the satellite mission sequence managed by the target satellite control agency with the highest expected value.

[0063] In this embodiment, the expected value considers both the magnitude of contribution and the task execution time window, ensuring that the selected target organization not only contributes in accordance with the redistribution requirements but also can actually complete the task. Based on a comprehensive judgment using the expected value, the satellite control organization with the highest bidding expected value is selected as the executable organization for the task to be assigned. This task is then inserted into the task sequence of the relevant satellites using a relaxed insertion method, and the collaborative task planning scheme is updated. This balances resource contribution and timeliness, ensuring that the task is assigned to the control organization with the most advantages and the best execution conditions, thus contributing to improving the overall benefits of the satellite constellation.

[0064] In one specific embodiment, four experimental scenarios were designed to verify the effectiveness of the Shapley value-based auction algorithm. As shown in Table 1, different satellite control agencies were randomly selected for each experimental scenario to add 50 tasks, cancel 30 tasks, or simultaneously add 50 tasks and cancel 20 tasks.

[0065] Table 1

[0066] Tasks are generated randomly globally. The task generation design is shown in Table 2. Task priority, resolution requirements, number of observations, and payload requirements are all generated in a uniformly distributed manner.

[0067] Table 2

[0068] The design of satellite orbital elements is shown in Table 3.

[0069] Table 3

[0070] The relevant parameters for satellite resource constraints are shown in Table 4. The main differences between optical satellites and SAR satellites are: first, SAR satellites do not have a pitch function; second, the maximum power-on time per orbit is different, with the power-on time per orbit for SAR satellites being twice that of optical satellites.

[0071] Table 4

[0072] Table 5 shows the overall task completion rate and profitability of heterogeneous constellations under various dynamic scenarios. As can be seen from the table, the task scheduling method for heterogeneous constellations in dynamic scenarios proposed in this application can effectively redistribute tasks.

[0073] Table 5

[0074] Figure 3 (a) Figure 3 (b) Figure 3 (c) Figure 3 (d) This section shows a comparison of the revenue (SVBAA value) and Shapley value of each satellite control agency in four different scenarios in Table 1 after applying the task scheduling method for heterogeneous constellations in dynamic scenarios proposed in the embodiments of this application. From Figure 3 As can be seen from the embodiments of this application, the method proposed can make the revenue of each satellite management agency approach the Shapley value, ensuring that the revenue distribution follows the principle of contribution rate allocation, enabling the alliance to reasonably cope with mission disturbances in dynamic scenarios and effectively maintain the stability of cooperation. In the actual mission allocation process, because different satellite management agencies have different visible time windows for different missions, different remaining power-on time per satellite orbit, and different observation durations for each mission, the allocation result cannot completely achieve the Shapley value.

[0075] Figure 4 (a) Figure 4 (b) Figure 4 (c) Figure 4 (d) This section shows a comparison of the increase in the number of tasks for each satellite control agency in four different scenarios in Table 1 before and after applying the task scheduling method for heterogeneous constellations in dynamic scenarios proposed in the embodiments of this application. From Figure 4As can be seen from the embodiments of this application, the increased tasks can be allocated to other satellite control agencies according to their contribution rate. The satellite control agency that increases its tasks will have the largest increase in the number of tasks because its contribution rate becomes higher. Conversely, when a satellite control agency cancels a task, its contribution rate becomes lower, and some of its sub-tasks will be allocated to other satellite control agencies. This provides robustness in dynamic environments and enables a planning scheme that provides a fair distribution of benefits with minimal disturbance.

[0076] It should be noted that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0077] Furthermore, such as Figure 2 As shown, as a specific implementation of the task scheduling method for heterogeneous star clusters in the above-mentioned dynamic scenario, this application embodiment provides a task scheduling device 200 for heterogeneous star clusters in a dynamic scenario. The task scheduling device 200 for heterogeneous star clusters in a dynamic scenario includes: a construction module 201 and a task allocation module 202.

[0078] Module 201 is used to construct a task scheduling model for heterogeneous star clusters in a dynamic scenario with the goal of maximizing the benefits of heterogeneous star clusters based on core constraints. The core constraints are used to reduce coalition disturbances and protect individual benefits during task allocation. The task allocation module 202 is used to determine candidate alliances that can accept assigned tasks based on a task scheduling model, wherein the assigned tasks are generated by dynamic perturbations of heterogeneous constellations, and the candidate alliances include at least one candidate satellite management agency; and to allocate the assigned tasks to target satellite management agencies in the candidate alliances based on the Shapley value of the assigned tasks and the number of effective visible time windows of the candidate satellite management agencies, wherein the effective visible time windows satisfy the relaxed insertion principle.

[0079] Furthermore, the task allocation module 202 is specifically used to screen target satellite management agencies from the candidate coalition based on the Shapley value; calculate the expected value of the target satellite management agency for the task to be allocated based on the Shapley value and the number of effective visible time windows; and insert the task to be allocated into the satellite task sequence managed by the target satellite management agency with the highest expected value.

[0080] Furthermore, the task allocation module 202 is specifically used to obtain the original revenue value of the candidate satellite control agency in the nuclear alliance under static scenarios for the tasks to be allocated; based on the relationship between the Shapley value and the original revenue value, the candidate satellite control agency with bidding qualifications in the candidate alliance is selected as the target satellite control agency.

[0081] Furthermore, the task allocation module 202 is specifically used to determine the priority weight of the candidate satellite control agency based on the difference between the Shapley value and the original benefit value of the candidate satellite control agency in the nuclear alliance under static scenario; update the quantity based on the priority weight; and calculate the quotient of the updated quantity and the total number of effective visible time windows of the candidate alliance for the assigned tasks as the expected value.

[0082] Furthermore, the core constraints include: Individual rational constraints are expressed as: ; Alliance rational constraints are expressed as: ; The task scheduling model is also configured with basic constraints, which include: The matching constraint between mission payload requirements and satellite payload type is expressed as: ; The maximum power-on time constraint per satellite orbit is expressed as: ; The uniqueness constraint of mission observations is expressed as: ; The observation time constraint is expressed as: , , , ; The satellite's conversion time constraint is expressed as: , =1, , , ; The maximum power-on time constraint for each satellite orbit is expressed as: ; In the formula, This indicates the satellite control agency after task allocation. k The benefits; f k This indicates that the nuclear alliance satellite control agency k The benefits; v ( S ) indicates alliance S The benefits; Indicates alliance S Tasks to be assigned; This indicates a nuclear alliance; R S Indicates alliance S Satellites that can be used to perform missions; T i Indicates satellite i Observable tasks; Indicates satellitei In the u A time window for the task j Decision variables; Z j Indicates task j Load requirement related parameters; Q io Indicates satellite i Maximum operating time per lap; b Indicates the start time of observation; e Indicates the end time of the observation; t Indicates the duration of mission observation; l Indicates the duration of task observation; Indicates satellite i For the task j In the u The visible time window of a time window; θ Indicates the minimum operating time of the satellite; g Indicates the conversion time; q il Indicates task l Following the mission j Decision variables to be observed; τ This indicates the maximum operating time for each satellite orbit.

[0083] Furthermore, the relaxation insertion criterion includes basic constraints and upper and lower bound constraints on the revenue of the satellite control agency.

[0084] Furthermore, the task allocation module 202 is also used to calculate the Shapley value based on the marginal contribution and occurrence probability of the candidate satellite management agency for the task to be allocated.

[0085] Specific limitations regarding the task scheduling device for heterogeneous constellations in dynamic scenarios can be found in the limitations of the task scheduling method for heterogeneous constellations in dynamic scenarios described above, and will not be repeated here. Each module in the aforementioned task scheduling device for heterogeneous constellations in dynamic scenarios can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0086] Based on the above, Figure 1 Accordingly, embodiments of this application also provide a readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described method. Figure 1 The task scheduling method for heterogeneous constellations in the dynamic scenario shown.

[0087] Based on this understanding, the technical solution of this application can be embodied in the form of a software product. The software product can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, or portable hard drive), and includes several instructions to cause a computer device (such as a personal computer, server, or network device) to execute the methods described in the various implementation scenarios of this application.

[0088] Based on the above, Figure 1 The method shown, and Figure 2 The virtual device embodiment shown is designed to achieve the above objectives, such as... Figure 5 As shown in the figure, this application embodiment also provides a computer device 400, which includes a processor 401 and a memory 402. The memory 402 stores a program or instructions that can run on the processor 401. When the program or instructions are executed by the processor 401, they implement the above-mentioned... Figure 1 The task scheduling method for heterogeneous constellations in the dynamic scenario shown.

[0089] The memory 402 can be used to store software programs and various data. The memory 402 may primarily include a first storage area for storing programs or instructions and a second storage area for storing data. The first storage area may store the operating system, application programs or instructions required for at least one function (such as sound playback, image playback, etc.). Furthermore, the memory 402 may include volatile memory or non-volatile memory, or both. The non-volatile memory may be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory can be random access memory (RAM), static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct memory bus RAM (DRRAM). The memory 402 in this embodiment includes, but is not limited to, these and any other suitable types of memory.

[0090] Processor 401 may include one or more processing units; optionally, processor 401 integrates an application processor and a modem processor, wherein the application processor mainly handles operations involving the operating system, user interface, and applications, and the modem processor mainly handles wireless communication signals, such as a baseband processor. It is understood that the aforementioned modem processor may also not be integrated into processor 401.

[0091] Computer equipment can specifically include personal computers, servers, network devices, etc.

[0092] Optionally, the computer device may also include a user interface, a network interface, a camera, radio frequency (RF) circuitry, sensors, audio circuitry, a Wi-Fi module, etc. The user interface may include a display screen, input units such as a keyboard, etc., and optional user interfaces may also include USB ports, card reader ports, etc. The network interface may optionally include standard wired interfaces, wireless interfaces (such as Bluetooth interfaces, Wi-Fi interfaces), etc.

[0093] Those skilled in the art will understand that the computer device structure provided in this embodiment does not constitute a limitation on the computer device, and may include more or fewer components, or combine certain components, or have different component arrangements.

[0094] Through the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented using software plus necessary general-purpose hardware platforms, or it can be implemented using hardware to maximize the benefits of heterogeneous constellations. A task scheduling model for heterogeneous constellations in dynamic scenarios is constructed based on core constraints, where the core constraints are used to reduce alliance disturbances and protect individual benefits during task allocation. Based on the task scheduling model, candidate alliances capable of accepting assigned tasks are determined, where the tasks to be assigned are generated by dynamic disturbances of the heterogeneous constellation, and the candidate alliances include at least one candidate satellite management agency. Based on the Shapley value of the tasks to be assigned and the number of effective visible time windows of the candidate satellite management agencies, the tasks to be assigned are allocated to the target satellite management agency in the candidate alliance, where the effective visible time windows satisfy the relaxed insertion principle. This application embodiment can deeply analyze the impact mechanism of temporary task changes on the alliance structure and individual benefits of satellite management agencies, and construct a task scheduling model. This approach optimizes resource utilization and task allocation holistically, ensuring that the allocation scheme for newly added tasks output by the task scheduling model protects the benefits available to any satellite management agency. This reduces the risk of internal disruptions within the alliance, effectively preventing alliance disintegration or reorganization due to uneven benefit distribution, and promoting long-term alliance stability during task scheduling. Furthermore, by modeling tasks as auction items and fully considering satellite time resource constraints, the Shapley value is used to meticulously measure the contribution of each candidate satellite management agency to the assigned tasks. This allows agencies with higher contribution to task benefits to undertake more tasks, ensuring that agencies with higher marginal contributions receive reasonable benefits, thereby improving overall benefits. Ultimately, this maximizes the execution quality and success rate of assigned tasks, improving the overall task execution performance and service level of the heterogeneous constellation in dynamic scenarios.

[0095] Those skilled in the art will understand that the accompanying drawings are merely schematic diagrams of a preferred embodiment, and the modules or processes shown in the drawings are not necessarily essential for implementing this application. Those skilled in the art will understand that the modules in the apparatus of the embodiment can be distributed within the apparatus of the embodiment as described, or can be modified to be located in one or more apparatuses different from this embodiment. The modules of the above-described embodiment can be combined into one module, or further divided into multiple sub-modules.

[0096] The serial numbers in this application are for descriptive purposes only and do not represent the superiority or inferiority of any particular implementation scenario. The above disclosures are merely a few specific implementation scenarios of this application; however, this application is not limited thereto, and any variations conceived by those skilled in the art should fall within the protection scope of this application.

Claims

1. A task scheduling method for heterogeneous star clusters in dynamic scenarios, characterized in that, The method includes: With the goal of maximizing the benefits of heterogeneous constellations, a task scheduling model for heterogeneous constellations in dynamic scenarios is constructed based on core constraints. The core constraints are used to reduce coalition disturbances and protect individual benefits during task allocation. Based on the task scheduling model, candidate alliances capable of undertaking and assigning tasks are determined, wherein the tasks to be assigned are generated by the dynamic perturbation of heterogeneous constellations, and the candidate alliances include at least one candidate satellite management agency. Based on the Shapley value of the task to be assigned and the number of effective visible time windows for the candidate satellite management agencies, the task to be assigned is assigned to the target satellite management agency in the candidate alliance, wherein the effective visible time windows satisfy the relaxed insertion principle.

2. The task scheduling method for heterogeneous constellations in dynamic scenarios according to claim 1, characterized in that, The process of assigning tasks to target satellite management agencies within the candidate consortium based on the Shapley value and the number of effective visible time windows of the tasks to be assigned by the candidate satellite management agencies includes: The target satellite control agency is selected from the candidate consortium based on the Shapley value; Based on the Shapley value and the number of effective visible time windows, the target satellite control agency calculates the expected value of the task to be assigned. The task to be assigned is inserted into the satellite mission sequence managed by the target satellite control agency with the highest expected value.

3. The task scheduling method for heterogeneous constellations in dynamic scenarios according to claim 2, characterized in that, The process of selecting the target satellite control agency from the candidate consortium based on the Shapley value includes: Obtain the original revenue value of the candidate satellite management agency for the task to be assigned in a nuclear alliance under static scenarios; Based on the relationship between the Shapley value and the original revenue value, the candidate satellite management agency in the candidate alliance that is qualified to bid is selected as the target satellite management agency.

4. The task scheduling method for heterogeneous constellations in dynamic scenarios according to claim 2, characterized in that, The step of calculating the target satellite control agency's expected value for the task to be assigned, based on the Shapley value and the quantity, includes: The priority weight of the candidate satellite management agency is determined based on the difference between the Shapley value and the original benefit value of the candidate satellite management agency for the task to be assigned in a nuclear alliance under static scenarios. The quantity is updated based on the priority weight; The expected value is calculated as the quotient of the updated quantity and the total number of valid visible time windows for the candidate alliance to the task to be assigned.

5. The task scheduling method for heterogeneous constellations in dynamic scenarios according to claim 1, characterized in that, The core constraints include: Individual rational constraints are expressed as: ; Alliance rational constraints are expressed as: ; The task scheduling model is also configured with basic constraints, which include: The matching constraint between mission payload requirements and satellite payload type is expressed as: ; The maximum power-on time constraint per satellite orbit is expressed as: ; The uniqueness constraint of mission observations is expressed as: ; The observation time constraint is expressed as: , , , ; The satellite's conversion time constraint is expressed as: , =1, , , ; The maximum power-on time constraint for each satellite orbit is expressed as: ; In the formula, This indicates the satellite control agency after task allocation. k The benefits; f k This indicates that the nuclear alliance satellite control agency k The benefits; v ( S ) indicates alliance S The benefits; Indicates alliance S Tasks to be assigned; This indicates a nuclear alliance; R S Indicates alliance S Satellites that can be used to perform missions; T i Indicates satellite i Observable tasks; Indicates satellite i In the u A time window for the task j Decision variables; Z j Indicates task j Load requirement related parameters; Q io Indicates satellite i Maximum startup time per lap; b Indicates the start time of observation; e Indicates the end time of the observation; t Indicates the duration of mission observation; l Indicates the duration of task observation; Indicates satellite i For the task j In the u The visible time window of a time window; θ Indicates the minimum operating time of the satellite; g Indicates the conversion time; q il Indicates task l Following the mission j Decision variables to be observed; τ This indicates the maximum operating time for each satellite orbit.

6. The task scheduling method for heterogeneous constellations in dynamic scenarios according to claim 5, characterized in that, The relaxation insertion criterion includes the basic constraints and the upper and lower limits of the revenue constraints for the satellite control agency.

7. The task scheduling method for heterogeneous constellations in dynamic scenarios according to claim 1, characterized in that, The method further includes: The Shapley value is calculated based on the marginal contribution and occurrence probability of the candidate satellite management agency for the assigned task.

8. A task scheduling device for heterogeneous star clusters in dynamic scenarios, characterized in that, The device includes: The module is used to construct a task scheduling model for heterogeneous constellations in a dynamic scenario with the goal of maximizing the benefits of heterogeneous constellations, based on core constraints. The core constraints are used to reduce coalition disturbances and protect individual benefits during the task allocation process. A task allocation module is used to determine candidate alliances capable of undertaking task allocation based on the task scheduling model, wherein the tasks to be allocated are generated by dynamic perturbations of heterogeneous satellite constellations, and the candidate alliances include at least one candidate satellite management organization; and, Based on the Shapley value of the task to be assigned and the number of effective visible time windows for the candidate satellite management agencies, the task to be assigned is assigned to the target satellite management agency in the candidate alliance, wherein the effective visible time windows satisfy the relaxed insertion principle.

9. A readable storage medium having a program or instructions stored thereon, characterized in that, When the program or instructions are executed by the processor, they implement the task scheduling method for heterogeneous constellations in dynamic scenarios as described in any one of claims 1 to 7.

10. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the task scheduling method for heterogeneous constellations in dynamic scenarios as described in any one of claims 1 to 7.

Images