Beidou short message emergency disaster relief communication resource hierarchical scheduling method and device, equipment and medium

Abstract

The present disclosure provides a Beidou short message emergency disaster relief communication resource hierarchical scheduling method, device, equipment and medium, comprising: selecting a scheduling satellite group from a plurality of geosynchronous orbit satellites based on the coverage intensity of each geosynchronous orbit satellite on the disaster area; determining a set of users to be scheduled based on the geographic location of the disaster area reported by each user; for each user terminal in the set of users to be scheduled, jointly calculating the corresponding comprehensive urgency score from the dimensions of identity attribute and spatial position; based on the comprehensive urgency score corresponding to each user terminal, dividing the set of users to be scheduled into three target scheduling groups; using an adaptive genetic algorithm as the core optimization engine, under the constraints of inbound channel capacity, parameter monotonicity, and outbound link capacity, searching for the optimal control parameter combination corresponding to the three target scheduling groups; and respectively issuing the corresponding optimal control parameter combination to the three target scheduling groups. Thus, the resource coordination efficiency between multiple users is effectively improved.

Description

Technical Field

[0001] The embodiments disclosed herein relate to the field of satellite communication resource management, and more specifically, to a method, apparatus, equipment, and medium for hierarchical scheduling of BeiDou short message emergency disaster relief communication resources. Background Technology

[0002] The BeiDou-3 Global Navigation Satellite System possesses regional short message communication capabilities, with a maximum message length of 1000 Chinese characters. It is the only one of the four major global navigation satellite systems to offer two-way message communication. In emergency disaster relief scenarios, BeiDou short messages often become the only reliable means of communication between disaster areas and the outside world. When natural disasters occur, terrestrial communication networks are frequently disrupted, making BeiDou short messages a vital lifeline for disaster areas. At such times, demand surges, with rescue workers and affected residents sending numerous messages within the disaster area, and ordinary users outside also continuously sending information, resulting in inbound demand far exceeding normal levels. However, inbound channel capacity and outbound link bandwidth are fixed limits and cannot be expanded to accommodate the surge in demand. Severe inbound message conflicts prevent the timely transmission of critical distress messages and command and dispatch instructions. Outbound link congestion leads to command feedback failures, weakening the closed-loop capability of command and dispatch.

[0003] In related technologies, resource scheduling is mainly achieved through terminal-side concurrent control, such as managing the transmission timing of different types of uplink requests through multi-level controllers. However, this method is still limited to transmission scheduling within a single terminal and is difficult to achieve resource coordination among multiple users. Summary of the Invention

[0004] The embodiments described herein provide a method, apparatus, equipment, and medium for hierarchical scheduling of BeiDou short message emergency disaster relief communication resources, overcoming the aforementioned problems.

[0005] Firstly, based on the content of this disclosure, a hierarchical scheduling method for BeiDou short message emergency disaster relief communication resources is provided, including: Based on the coverage intensity of each geostationary orbit satellite to the disaster area, a scheduling satellite group is selected from multiple geostationary orbit satellites; the scheduling satellite group includes one of the geostationary orbit satellites or at least two of the geostationary orbit satellites. Based on the geographical locations of the disaster areas reported by each user, a set of users to be scheduled that are located within the coverage area of ​​the scheduling satellite constellation is determined. For each user terminal in the set of users to be scheduled, a comprehensive urgency score is jointly calculated from the dimensions of identity attributes and spatial location. Based on the comprehensive urgency score corresponding to each user terminal, the set of users to be scheduled is divided into three target scheduling groups; An adaptive genetic algorithm is used as the core optimization engine to search for the optimal combination of control parameters for the three target scheduling groups under the constraints of inbound channel capacity, parameter monotonicity, and outbound link capacity. The corresponding optimal control parameter combinations are issued to the three target scheduling groups respectively.

[0006] Secondly, based on the content of this disclosure, a hierarchical scheduling device for BeiDou short message emergency disaster relief communication resources is provided, comprising: The selection module is used to select a scheduling satellite group from multiple geostationary orbit satellites based on the coverage intensity of each geostationary orbit satellite over the disaster area; the scheduling satellite group includes one of the geostationary orbit satellites or at least two of the geostationary orbit satellites. The determination module is used to determine the set of users to be scheduled within the coverage area of ​​the scheduling satellite constellation based on the geographical location of the disaster area reported by each user. The calculation module is used to jointly calculate the corresponding comprehensive urgency score for each user terminal in the set of users to be scheduled from the dimensions of identity attributes and spatial location. The partitioning module is used to divide the set of users to be scheduled into three target scheduling groups based on the comprehensive urgency score corresponding to each user terminal. The search module is used to search for the optimal combination of control parameters for the three target scheduling groups under the constraints of inbound channel capacity, parameter monotonicity, and outbound link capacity, using an adaptive genetic algorithm as the core optimization engine. The distribution module is used to distribute the corresponding optimal control parameter combinations to the three target scheduling groups respectively.

[0007] Thirdly, a computer device is provided, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the steps of the hierarchical scheduling method for BeiDou short message emergency disaster relief communication resources as described in any of the above embodiments.

[0008] Fourthly, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the hierarchical scheduling method for Beidou short message emergency disaster relief communication resources as described in any of the above embodiments.

[0009] The BeiDou short message emergency disaster relief communication resource hierarchical scheduling method provided in this application selects a scheduling satellite group from multiple geostationary orbit satellites based on the coverage intensity of each geostationary orbit satellite over the disaster area. The scheduling satellite group includes one or at least two geostationary orbit satellites. Based on the geographical location of the disaster area reported by each user, a set of users to be scheduled within the coverage area of ​​the scheduling satellite group is determined. For each user terminal in the set of users to be scheduled, a corresponding comprehensive urgency score is jointly calculated from the dimensions of identity attributes and spatial location. Based on the comprehensive urgency score corresponding to each user terminal, the set of users to be scheduled is divided into three target scheduling groups. An adaptive genetic algorithm is used as the core optimization engine to search for the corresponding optimal control parameter combination for the three target scheduling groups under the constraints of inbound channel capacity, parameter monotonicity, and outbound link capacity. The corresponding optimal control parameter combination is then issued to the three target scheduling groups respectively. In this way, by coordinating the communication parameters between the satellite group and user terminals, differentiated resource allocation is achieved for user groups with different urgency levels, effectively improving the resource coordination efficiency among multiple users.

[0010] The above description is merely an overview of the technical solutions of the embodiments of this application. In order to better understand the technical means of the embodiments of this application and to implement them in accordance with the contents of the specification, and to make the above and other objects, features and advantages of the embodiments of this application more obvious and understandable, specific implementation methods of this application are described below. Attached Figure Description

[0011] To more clearly illustrate the technical solutions of the embodiments of this disclosure, the accompanying drawings of the embodiments will be briefly described below. It should be understood that the drawings described below only relate to some embodiments of this disclosure and are not intended to limit this disclosure, wherein: Figure 1 This is a flowchart illustrating a hierarchical scheduling method for emergency disaster relief communication resources using BeiDou short messages, as disclosed in this publication.

[0012] Figure 2 This is a schematic diagram of a position decay weight function curve provided in this disclosure.

[0013] Figure 3 This is a schematic diagram of the structure of a Beidou short message emergency disaster relief communication resource hierarchical scheduling device provided in this publication.

[0014] Figure 4 This is a schematic diagram of the structure of a computer device provided in this disclosure.

[0015] It should be noted that the elements in the attached diagram are schematic and not drawn to scale. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of the embodiments of this disclosure clearer, the technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this disclosure. All other embodiments obtained by those skilled in the art based on the described embodiments of this disclosure without creative effort are also within the scope of protection of this disclosure.

[0017] Unless otherwise defined, all terms used herein (including technical and scientific terms) shall have the same meaning as commonly understood by one of ordinary skill in the art to which this subject matter pertains. It will be further understood that terms such as those defined in commonly used dictionaries shall be interpreted as having the meaning consistent with their meaning in the context of the specification and in the relevant art, and shall not be interpreted in an idealized or overly formal form unless otherwise explicitly defined herein. As used herein, the statement of “connecting” or “coupling” two or more parts together shall mean that these parts are directly joined together or joined through one or more intermediate components.

[0018] The term "embodiment" as used herein means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of the phrase "embodiment" in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0019] In this document, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can mean: A exists, A and B exist simultaneously, or B exists. Additionally, the character " / " generally indicates that the preceding and following related objects have an "or" relationship. Terms such as "first" and "second" are only used to distinguish one component (or part of a component) from another component (or another part of a component).

[0020] In the description of this application, unless otherwise stated, "multiple" means two or more (including two), and similarly, "multiple groups" means two or more (including two groups).

[0021] This embodiment adopts a four-layer progressive architecture: satellite-optimized coverage adaptation, user screening and scale reduction, cluster analysis for intelligent grouping, and genetic evolution optimization and scheduling. The first layer is the satellite optimization layer. Since the BeiDou-3 regional short message service is provided by multiple GEO (Geostationary Earth Orbit) satellites, the coverage range of each satellite beam varies, while the geographical location of the disaster area is dynamically changing. The master control station first quantitatively calculates the coverage intensity of each satellite for the disaster area based on the intersection area between the real-time disaster area geofence and the coverage area of ​​each satellite beam, and selects the satellite with the highest coverage intensity as the guaranteed satellite for the scheduling cycle. The second layer is the user screening layer. Within the coverage area of ​​the guaranteed satellite, the master control station only includes users whose geographical location is within the coverage area in the scheduling management, while users outside the coverage area maintain their original communication parameters. This screening step reduces the scale of the global optimization problem from the total number of users in the entire system. N Reduced to a subset of users directly related to the disaster area N ’ The third layer is the intelligent clustering grouping layer. This embodiment abandons the traditional approach of dividing groups using fixed thresholds and adopts an adaptive grouping method based on the K-means clustering algorithm. First, a comprehensive urgency score is constructed based on the user's registered identity and real-time geographical location. Then, the urgency score is used as a one-dimensional feature input to the K-means clusterer, automatically grouping users into three natural clusters, corresponding to high, medium, and low urgency groups, respectively. The division boundary of this method is determined by the distribution characteristics of the data itself, without relying on any manually set thresholds, and has good scene adaptability. The fourth layer is the genetic optimization adjustment layer. Taking the group as the basic decision unit, the service frequency level and message length level as decision variables, the inbound channel capacity and parameter monotonicity as constraints, and the goal of maximizing the weighted communication guarantee benefits, a combinatorial optimization model is established. An adaptive genetic algorithm (AGA) is used to intelligently search for the globally optimal combination of control parameters in the discrete decision space. The solution process of this method achieves intelligent search through evolutionary operators, and has good scalability and global search capabilities.

[0022] In addition, this embodiment also utilizes two auxiliary mechanisms, namely outbound Internet diversion and adaptive adjustment of scheduling cycle, to form a complete intelligent control closed loop from three dimensions: inbound flow restriction, outbound load reduction and response frequency.

[0023] For ease of subsequent mathematical description, this embodiment first defines the following system symbols and parameters: Let the set of GEO satellites in the BeiDou-3 regional short message system be denoted as . The set of all user terminals in the system is denoted as ,in N This represents the total number of users. The disaster area geofence (polygon region) for the current scheduling period is denoted as... The fence is dynamically updated based on disaster remote sensing data and information reported by ground sensors. The scheduling cycle length is denoted as... T (Unit: seconds) T It can adaptively adjust according to the system congestion level. (User) u i The real-time geographic location coordinates are as follows The user's basic priority is denoted as Based on their registered identity, the service frequency tiers are preset. gear The corresponding shortest transmission interval is denoted as (Unit: seconds), satisfying The set of message length increments is denoted as... gear The corresponding maximum allowed number of characters is denoted as ,satisfy Inbound channels in each scheduling cycle T The maximum number of messages that can be processed internally is denoted as R max The capacity limit of the satellite outbound link within each scheduling period $T$ is denoted as... O max .

[0024] In this embodiment, the service frequency level and message length level are user communication parameters that the master control station can directly adjust through background commands. Together, they constitute the basic variables for control decisions.

[0025] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

[0026] Figure 1 This is a flowchart illustrating a hierarchical scheduling method for BeiDou short message emergency disaster relief communication resources provided in an embodiment of this disclosure. Figure 1 As shown, the specific process of the BeiDou short message emergency disaster relief communication resource hierarchical scheduling method includes: S110. Based on the coverage intensity of each geostationary orbit satellite over the disaster area, select and schedule a satellite constellation from multiple geostationary orbit satellites.

[0027] The satellite constellation includes one geostationary orbit satellite or at least two geostationary orbit satellites.

[0028] geostationary orbit satellites The coverage intensity of the disaster area is the current geographical fence of the disaster area. Beam coverage area function of each GEO satellite The ratio of the geographical area of ​​intersection to the total area of ​​the disaster area (this function is a known constant, determined by the Beidou system ephemeris and beam parameters) is shown in the following formula (1).

[0029] (1) In formula (1), This is a function to calculate the area of ​​a polygon; the coverage strength ranges from [0,1], and the closer the value is to 1, the higher the proportion of the disaster area covered by the satellite beam.

[0030] In some embodiments, a satellite constellation is selected from multiple geostationary orbit satellites for scheduling, based on the coverage intensity of each geostationary orbit satellite over the disaster area, including: From multiple geostationary orbit satellites, select the geostationary orbit satellite with the largest coverage intensity to form a scheduling satellite group; or, if the difference between the maximum coverage intensity and the second largest coverage intensity is less than a preset threshold, select at least two geostationary orbit satellites from multiple geostationary orbit satellites in descending order of coverage intensity to form a scheduling satellite group.

[0031] The master control station can select the satellite with the strongest coverage as the backup satellite for the current scheduling cycle by traversing all GEO satellites. In order to build a satellite constellation for scheduling.

[0032] Considering that in real-world scenarios, disaster areas may be located in overlapping coverage areas of multiple satellites, if the difference between the maximum and second-highest coverage intensity is less than a preset threshold (typically 0.05), then 2 to 3 satellites with the highest coverage intensity can be selected to form a joint support set to create a scheduling satellite group. The coverage areas of each satellite can then be merged to form a unified service coverage range, thereby enhancing the redundancy and reliability of the communication link.

[0033] S120. Based on the geographical locations of the disaster areas reported by each user, determine the set of users to be scheduled that are within the coverage area of ​​the scheduling satellite constellation.

[0034] Among them, the master control station selects and supports satellites (and schedules the satellite constellation). Then, based on the real-time geographical location reported by each user, users located in User terminals within the coverage area form a set of users to be scheduled: Not here Users within the specified range, unable to establish effective communication links via satellite, will have their communication parameters maintained at their original configuration and will not be included in the decision-making process for this scheduling cycle. This screening step reduces the variable size of the optimization problem from... N Reduced to (generally This significantly reduces the computational scale of subsequent combinatorial optimizations, while avoiding the waste of outbound resources caused by issuing control commands to invalid users.

[0035] S130. For each user terminal in the set of users to be scheduled, calculate the corresponding comprehensive urgency score from the dimensions of identity attribute and spatial location.

[0036] Among them, for each user terminal after screening In this embodiment, the overall urgency score is calculated from two dimensions: identity attribute and spatial location.

[0037] In some embodiments, for each user terminal in the set of users to be scheduled, a corresponding comprehensive urgency score is jointly calculated from the dimensions of identity attributes and spatial location, including: For each user terminal in the set of users to be scheduled, a basic priority is determined based on the corresponding identity attribute; and a corresponding location attenuation weight is determined based on the shortest Euclidean distance from the spatial location of each user terminal to the geographical fence of the disaster area; the basic priority and location attenuation weight of each user terminal are weighted and fused to obtain the comprehensive urgency score of each user terminal.

[0038] Among them, basic priority The system can be preset with five levels of quantitative values ​​based on the identity category registered in the user's registration information: 1.00 for disaster relief command centers and front-line command posts, 0.85 for professional rescue teams and medical teams, 0.60 for disaster area residents (including disaster area staff), 0.30 for emergency-related personnel in non-disaster areas, and 0.10 for ordinary users in non-disaster areas. This system can effectively reflect the inherent importance of user identity in the emergency response system.

[0039] Spatial location of user terminal p i Geographical fencing in the disaster area Shortest Euclidean distance d i for: , Denotes the Euclidean norm. q This refers to any point on the boundary of the disaster area fence. This embodiment uses a hyperbolic tangent smoothing function to construct the location attenuation weight. As shown in formula (2) below. The position decay weight function curve is as follows. Figure 2 As shown.

[0040] (2) In formula (2), D 0 indicates the attenuation start distance parameter (typical value is 5 km); This represents the steepness parameter (typically 2 km). The property of this function is: when the user is located within or very close to the disaster area (… )hour, When users are far from the disaster area ( )hour, ;exist place, The curve exhibits a continuous and smooth S-shaped transition, avoiding the priority jump problem caused by the hard boundary of the traditional binary classification "disaster area / non-disaster area", allowing users on the edge of the disaster area to also obtain a progressive level of protection.

[0041] Overall urgency score S i The result is obtained by weighted fusion of basic priority and position decay weight, as shown in the following formula (3).

[0042] (3) In formula (3), This represents the weight adjustment parameter.

[0043] In emergency rescue scenarios, location information better reflects the urgency of a user's impact from a disaster; therefore, this embodiment takes... This allows location weight to become dominant. When user location information is missing, the system can... ,at this time It degenerates into a static priority based entirely on identity presets.

[0044] S140. Based on the comprehensive urgency score corresponding to each user terminal, the set of users to be scheduled is divided into three target scheduling groups.

[0045] The K-means clustering algorithm can be used to adaptively partition the user group, with the urgency scores of all users to be scheduled as input. The output consists of three groups: G1, G2, and G3.

[0046] K-means is a classic unsupervised clustering algorithm whose goal is to classify clusters into smaller, more manageable clusters. n The samples were divided into K The goal is to find clusters that maximize the similarity of samples within the same cluster and minimize the similarity of samples between different clusters. For one-dimensional data, the objective function is: , For the first k Clusters, For the first k Cluster centers of each cluster.

[0047] To avoid local optima caused by random initialization, this embodiment adopts the following deterministic initialization method: Sort in ascending order; divide into 3 equal groups, each group containing approximately 100 samples; the median of each group is taken as the initial cluster center. , , ;according to Rearrange the cluster centers so that they correspond to the urgency levels. C 1 corresponds to the highest level of urgency. C 3 corresponds to the lowest urgency level. This ensures that cluster centers cover the entire data range and correspond semantically to high / medium / low urgency levels.

[0048] In the iterative clustering process, let the current iteration number be . t Cluster center is , , Allocation steps: For each S i Calculate its distance to the three cluster centers. Assign it to the nearest cluster: Update steps: Recalculate the mean of each cluster as the new cluster center: Repeat the above two steps until the cluster centers no longer change. For all k It is established, or the maximum number of iterations has been reached.

[0049] Population generation: After clustering convergence, based on cluster centers... Determine the correspondence between groups: .in, C 1 represents the cluster with the largest cluster center (high urgency). C Cluster 3 represents the cluster with the smallest cluster center (low urgency). The number of users in each group is denoted as... , , .

[0050] Automatic boundary determination: After clustering is completed, the population partition boundary is automatically determined as the midpoint of the adjacent cluster centers. The urgency score ranges for these three groups are as follows: Boundary values , It is completely data-driven and requires no manual settings.

[0051] The time complexity of K-means clustering is... ,in For the number of users, The maximum number of iterations, This represents the number of clusters. In a typical scenario... The calculation time is much less than 1 second, which meets the real-time requirements of engineering.

[0052] This embodiment uses the K-means clustering algorithm instead of the fixed threshold division method, allowing the group boundary to be determined by the distribution characteristics of the data itself, thus possessing scene adaptability. Regardless of which interval the users' urgency scores are concentrated in, the algorithm can automatically find a reasonable division boundary.

[0053] S150 employs an adaptive genetic algorithm as its core optimization engine to search for the optimal combination of control parameters for three target scheduling groups under constraints of inbound channel capacity, parameter monotonicity, and outbound link capacity.

[0054] Among them, an adaptive genetic algorithm is used as the core optimization engine. Under the constraints of inbound channel capacity, parameter monotonicity, and outbound link capacity, the optimal service frequency level and message length level are searched for the three groups respectively.

[0055] For problem modeling, the decision variables are: let the service frequency levels of the three groups be respectively... The message length levels are respectively Quality of Service (QoS) function: In this embodiment, the QoS of a single user is defined as the quality of communication service obtained when the parameters are configured. for: . This indicates the highest service frequency tier ( The normalized transmission frequency is based on the shortest interval. Indicates the longest report document length ( The normalized message length is based on (). The larger the value, the higher the quality of communication service received by the user. This function is monotonic. Q about f Strictly monotonically decreasing (the larger the value, the longer the sending interval and the worse the service quality), regarding l Strictly monotonically increasing (the larger the value, the longer the message can be, and the better the service quality).

[0056] Objective function: With the goal of maximizing the system's weighted communication guarantee benefits, the objective function is defined as the sum of the products of the number of users in each group, the urgency weight, and the service quality function. . The group urgency weighting coefficient satisfies Typical value , , The physical meaning of this objective function is: in resource allocation, the benefit contributed by the improvement of service quality per unit in the high-urgency group is 5 times that of the low-urgency group, thereby guiding the optimization algorithm to prioritize the allocation of high-quality communication parameters (high frequency, long message) to the group.

[0057] Inbound capacity constraint: Within each scheduling cycle, the total load of inbound messages generated by the three groups must not exceed the channel capacity limit. ; This is the floor function, representing the rounding down operation for each user within a cycle. T The maximum number of messages that can be sent. This constraint ensures that the overall inbound traffic after regulation does not exceed the physical channel capacity, which is the fundamental guarantee for alleviating congestion at its source. Parameter monotonicity constraint: To ensure that the regulation results conform to the urgency ranking principle, high-urgency groups should receive a service quality no lower than that of low-urgency groups. The rationale for this constraint is that a smaller frequency tier indicates a shorter transmission interval (better), while a larger length tier indicates a longer allowed message (better). Therefore, the constraint ensures that the parameters of G1 are not inferior to those of G2, and the parameters of G2 are not inferior to those of G3. Outbound link capacity constraint: Considering that the bandwidth of the satellite outbound link is also limited, a capacity constraint after outbound traffic splitting is introduced. Let... If the proportion of users in the G3 group with terrestrial internet communication capabilities is considered, then the number of messages that still need to be sent out via satellite in the G3 group shall not exceed the satellite outbound capacity: This constraint reflects the design features of coordinated control between inbound suppression and outbound diversion, ensuring that the outbound link is not blocked by response messages from low-urgency users and guaranteeing the real-time transmission of commands from high-urgency users.

[0058] For chromosome coding, each individual is encoded as an integer chromosome of length 6: .in , Each gene locus directly corresponds to a regulatory parameter of a population.

[0059] For population initialization, the initial population size is: P Each individual is generated as follows: randomly generated. And sort them in ascending order to ensure Randomly generated And sort them in descending order to ensure Check inbound capacity constraints If the conditions are not met, the individual is regenerated. Through this method, all individuals in the initial population naturally satisfy the monotonicity and capacity constraints.

[0060] For the fitness function, the objective function is directly used as the fitness function: A higher fitness value indicates a better control scheme. For individuals that violate the outbound capacity constraint, a penalty term is applied to the fitness function: .in For satellite outbound payload, This is the penalty coefficient.

[0061] For the selection operator, a tournament selection strategy is used to generate the next generation population: randomly select from the current population. k 1. Select the individual with the highest fitness to proceed to the next generation; repeat. p Next, a complete next-generation population is generated. The advantage of tournament selection is that it does not require calculating the global selection probability and can effectively maintain population diversity, avoiding premature convergence.

[0062] For the crossover operator, with crossover probability Decide whether to perform crossover: Randomly select two parent individuals from the population; randomly select two crossover points (two integers between 1 and 5); swap the gene segments of the two parent individuals between the crossover points. After crossover, check the monotonicity constraint; if... or Then f Genes are reordered in ascending order; if or Then l The genes were rearranged in descending order.

[0063] For the mutation operator, the mutation probability is... Determine whether each gene locus has mutated: Iterate through every gene locus in the chromosome; if the gene locus is selected to mutate, randomly replace it with... A different value in the variable; after mutation, check the monotonicity constraint, and if it is not satisfied, perform the same repair strategy as after crossover; check the inbound capacity constraint, and if it is violated, regenerate the individual or revert to the state before mutation.

[0064] For adaptive parameter adjustment, an adaptive mechanism is used to dynamically adjust the crossover probability. and mutation probability To balance global search and local development capabilities: ; .in, The average fitness of the current population. The maximum fitness of the current population. , , , , α and β is the adjustment coefficient. The physical meaning of this adaptive mechanism is: when the population tends to converge and approaches 1, the crossover probability is reduced and the mutation probability is increased to increase population diversity and prevent getting trapped in local optima; when the population is relatively dispersed, the crossover probability is increased and the mutation probability is reduced to accelerate convergence.

[0065] The algorithm terminates under any of the following conditions: the maximum number of iterations is reached. ;continuous If the improvement in fitness is less than a preset threshold, the algorithm terminates and outputs the individual with the highest fitness in the current population as the optimal combination of control parameters for the current scheduling cycle. .

[0066] Genetic algorithms require evaluation in each generation. P The fitness of each individual, with a total of [number] assessments. Each fitness evaluation involves only constant-level operations, with a total computation time of less than 1 second, fully meeting the real-time requirements of engineering projects.

[0067] S160: Distribute the corresponding optimal control parameter combinations to the three target scheduling groups respectively.

[0068] After obtaining the optimal combination of control parameters, the master control station broadcasts the corresponding parameter configuration instructions to the three groups respectively.

[0069] In some embodiments, the target scheduling group includes: a first scheduling group G1, a second scheduling group G2, and a third scheduling group G3, wherein the scheduling urgency of the first scheduling group is greater than that of the second scheduling group, and the scheduling urgency of the second scheduling group is greater than that of the third scheduling group.

[0070] The optimal control parameter combinations are distributed to the three target scheduling groups respectively, including: The system sends the corresponding optimal control parameter combination to the first scheduling group via the satellite outbound link; for user terminals in the second and third scheduling groups located in areas with normal terrestrial internet coverage, it pushes the corresponding optimal control parameter combination to the BeiDou terrestrial internet service platform so that the BeiDou terrestrial internet service platform can send the corresponding optimal control parameter combination to the corresponding user terminals; and sends the corresponding optimal control parameter combination to other user terminals in the second and third scheduling groups via the satellite outbound link.

[0071] For users in the G2 and G3 groups whose real-time location is confirmed to be within areas with normal terrestrial internet coverage, the master control station marks their outbound packets as prioritizing internet access. These users' outbound packets are no longer sent via the satellite outbound link but are instead pushed to the BeiDou terrestrial internet service platform, where the terrestrial network handles the final delivery. This diversion strategy effectively frees up limited satellite outbound bandwidth, allowing it to focus on transmitting instructions back to users in disaster areas. After receiving control instructions, users switch their inbound communication parameters to the new configuration in the next scheduling cycle, and this new configuration remains effective in subsequent communications until they receive new control instructions or the system restores its default configuration.

[0072] This embodiment alleviates satellite channel pressure from both inbound and outbound directions by simultaneously adjusting service frequency and message length, and by utilizing the Internet to divert outbound traffic from users in non-disaster areas.

[0073] In some embodiments, the method further includes: determining the system congestion level based on the inbound channel status in the previous scheduling period; and adjusting the resource scheduling frequency based on the system congestion level.

[0074] The length of the scheduling period directly affects the timeliness of the control response and the system overhead. This embodiment proposes a dynamic periodic adjustment mechanism based on congestion level feedback, whose adjustment function is: . and These are the preset minimum and maximum scheduling periods, respectively. The attenuation coefficient is... C This represents the overall congestion level at the current moment. The characteristic of this exponential adjustment function is: when... C When it is small, the exponential term Approaching 1, The master control station performs scheduling at a lower frequency, reducing unnecessary computation and signaling overhead; when C When it is large, the exponent term Approaching 0, The main control station automatically increases the scheduling frequency to achieve precise and rapid control response.

[0075] In some embodiments, determining the system congestion level based on the inbound channel state in the previous scheduling period includes: The status of the inbound channel during the previous scheduling cycle is continuously monitored, and the inbound channel occupancy rate and message collision rate are collected. The inbound channel occupancy rate and message collision rate are weighted and fused to obtain the system congestion level.

[0076] Among them, the master control station continuously monitors the inbound channel status during the previous scheduling cycle and collects two core indicators: inbound channel occupancy rate. (i.e., the proportion of inbound time slots actually used) and message collision rate (That is, the proportion of conflicting messages out of the total number of messages sent). The two are weighted and combined into a comprehensive congestion level: The weighting coefficients satisfy... Typical configuration , Overall congestion level C Similarly, the value is in the range [0,1], and the higher the value, the heavier the system load.

[0077] Furthermore, C Mapped to four discrete congestion level states: Normal state: This indicates that channel resources are sufficient and no suppression is required; Warning status: This indicates that the load is approaching the capacity limit, and initial suppression of low-urgency groups is required; Congestion status: This indicates that the system is already significantly congested, requiring deep suppression for groups with low to medium urgency; severe congestion state: This indicates that the channel is close to saturation, and extreme control measures need to be implemented for low-urgency groups (configured as the longest transmission interval and the shortest message length).

[0078] In some embodiments, the method further includes: for user terminals in the first scheduling group, dynamically allocating a dedicated inbound time slot for each user terminal based on the corresponding service type and real-time communication requirements; and prohibiting access from other scheduling groups within the dedicated inbound time slot.

[0079] The service types can include one or more of emergency command, medical rescue, and disaster reporting. Real-time communication needs can be quantified by the amount of service data reported by user terminals and the update frequency. The allocation cycle of dedicated inbound time slots can be based on the overall system congestion level. C Dynamic adjustment, when C In normal conditions, the allocation granularity is at the millisecond level. C When entering an alert or higher state, the allocation granularity is tightened to the microsecond level to ensure low-latency access for high-urgency services.

[0080] In this embodiment, a scheduling satellite constellation is selected from multiple geostationary orbit satellites based on the coverage intensity of the disaster area by each geostationary orbit satellite. The scheduling satellite constellation includes one or at least two geostationary orbit satellites. Based on the geographical location of the disaster area reported by each user, a set of users to be scheduled within the coverage area of ​​the scheduling satellite constellation is determined. For each user terminal in the set of users to be scheduled, a comprehensive urgency score is jointly calculated from the dimensions of identity attributes and spatial location. Based on the comprehensive urgency score corresponding to each user terminal, the set of users to be scheduled is divided into three target scheduling groups. An adaptive genetic algorithm is used as the core optimization engine to search for the optimal control parameter combination for the three target scheduling groups under the constraints of inbound channel capacity, parameter monotonicity, and outbound link capacity. The corresponding optimal control parameter combination is then issued to the three target scheduling groups. Thus, by coordinating the communication parameters between the satellite constellation and user terminals, differentiated resource allocation is achieved for user groups with different urgency levels, effectively improving the resource coordination efficiency among multiple users.

[0081] In summary, in this embodiment, the master control station can adjust the service frequency level for specific users or user groups via background commands. Increasing the level and extending the interval can reduce the number of inbound messages sent by that user per unit time, thereby alleviating inbound channel pressure. The master control station can also adjust the message length level for specific users or user groups via background commands. Decreasing the level and allowing fewer characters can reduce the time a single message occupies the channel, further reducing the inbound channel load at the same frequency. For users outside the disaster area with uninterrupted terrestrial internet access, the master control station can switch their outbound messages to be sent via the terrestrial network, releasing satellite outbound link resources and ensuring the reception of outbound commands for users in the disaster area. The system can automatically adjust the control strategy according to changes in the disaster area and the system congestion level without manual intervention; the scheduling cycle is dynamically adjusted according to the congestion level, achieving "fine-grained control during busy periods and reduced overhead during idle periods"; the crossover and mutation probabilities of the genetic algorithm are adaptively adjusted according to the population convergence degree, balancing global search and local development capabilities. An adaptive genetic algorithm is used to achieve intelligent search of the solution space. The adaptive parameter adjustment mechanism effectively prevents premature convergence. While ensuring the quality of the solution, it has good scalability and can adapt to future needs such as parameter space expansion.

[0082] In addition, this embodiment provides a specific earthquake disaster scenario for illustration. Assume a magnitude 6.5 earthquake occurs in a certain area, ground communication is interrupted, and the disaster area is... The area is defined as a 10 km radius region centered on the epicenter. The main control station performs scheduling every hour. (BeiDou-3 GEO satellite) The coverage area is known. The overlap area between the three satellites and the disaster area is calculated, and the result is obtained. , , Selected as the support satellite. The reported location is obtained. S The coverage area includes 2000 users. This includes 2 command center terminals, 50 rescue team terminals, 800 terminals for residents in disaster areas, 150 emergency terminals in non-disaster areas, and 998 ordinary terminals in non-disaster areas. Urgency rating: [Incomplete sentence] , km, km. Typical user calculation results: rescue team , km, , People in the disaster area , km, , Ordinary users outside disaster areas , km, , All S iInputting a K-means clusterer, after initialization, the initial values ​​of the three cluster centers are approximately , , After 5 iterations, the cluster converged, and the final cluster centers were: , , The boundary is automatically determined. , Clustering results: G1 approximately 52 people (cluster centers 0.91), G2 approximately 810 people (cluster centers 0.58), G3 approximately 1138 people (cluster centers 0.06).

[0083] Congestion awareness: In the previous scheduling period, the inbound channel occupancy rate was monitored to be 0.78, and the collision rate was 0.25. Calculations show... The system is currently under alert. An adaptive genetic algorithm is used to solve the problem, with the following parameters configured: population size... P =50, maximum number of iterations Crossover probability Adaptive adjustment, mutation probability Adaptive adjustment, tournament scale k =3, the algorithm converges after running for about 0.5 seconds, and outputs the optimal individual. , , Specifically, G1 maintains the highest frequency (10 seconds / time) and the longest message length (1000 Chinese characters); G2 frequency is reduced to 60 seconds / time, with a message limit of 200 Chinese characters; G3 frequency is reduced to 300 seconds / time, with a message limit of 100 Chinese characters. For users in G2 and G3 whose location is confirmed to be in an area with uninterrupted internet access, all outgoing messages are forwarded to the BeiDou terrestrial internet service platform. The master control station sends parameter configuration instructions to user terminals via broadcast. Monitoring in the next scheduling cycle shows that the inbound channel occupancy rate decreased from 0.78 to 0.52, the collision rate decreased from 0.25 to 0.12, and the success rate of sending critical information in disaster areas increased from approximately 82% to over 99%. Outgoing messages for users outside disaster areas are entirely completed through the terrestrial internet, and the satellite outgoing link occupancy rate decreased by approximately 60%. Cycle adjustment: Current C =0.515, scheduling cycle in seconds This means that the next scheduling will be triggered approximately 102 seconds later, which is significantly shorter than the normal cycle.

[0084] Furthermore, to verify the advantages of the clustering method in this embodiment, a comparative experiment was set up. If a fixed threshold is used... , The initial clustering yielded approximately 52, 748, and 1200 individuals. However, the K-means clustering of this invention yielded approximately 52 individuals for G1, 810 for G2, and 1138 for G3. The main difference lies at the boundaries of the low- and middle-income groups: a fixed threshold will result in a large number of individuals being clustered. S i Users with a urgency level near 0.3 were grouped into a low-urgency group, while the clustering algorithm divided the data based on natural gaps in the distribution, resulting in G2 containing more users with a urgency level close to medium, making the grouping more reasonable. If aftershocks cause the disaster area to expand to a radius of 20 km, the main control station will recalculate after user location reports. and S i The distance between some non-disaster area emergency users, previously located on the edge of the disaster area, and the disaster area has been reduced from 10 km to 5 km. It rose from about 0.20 to about 0.50. S i The K-means clustering algorithm improved from approximately 0.26 to approximately 0.38. It automatically detected the data distribution change in the next scheduling cycle, and the cluster centers shifted from... Adaptive adjustment Some users who migrated from G3 to G2 automatically received higher communication assurance parameters without requiring manual intervention to adjust thresholds. If a disaster causes the inbound channel occupancy rate to reach 0.92 and the collision rate to reach 0.45, It is in a state of congestion. The parameters retrieved from the decision table are: , , In other words, group G3 uses the longest transmission interval (600 seconds / transmission) and the shortest message length (50 words) to minimize its inbound load, which is equivalent to suspending inbound traffic when the channel is extremely congested. Under these parameters, communication for low-urgency groups is compressed to the limit, and most of the inbound channel resources are allocated to high-urgency and medium-urgency groups.

[0085] Figure 3 This is a schematic diagram of a hierarchical scheduling device for BeiDou short message emergency disaster relief communication resources provided in this embodiment. The BeiDou short message emergency disaster relief communication resource hierarchical scheduling device may include: The selection module 310 is used to select a scheduling satellite group from multiple geostationary orbit satellites based on the coverage intensity of each geostationary orbit satellite over the disaster area; the scheduling satellite group includes one geostationary orbit satellite or at least two geostationary orbit satellites.

[0086] The determination module 320 is used to determine the set of users to be scheduled within the coverage area of ​​the scheduling satellite constellation based on the geographical location of the disaster area reported by each user.

[0087] The calculation module 330 is used to jointly calculate the corresponding comprehensive urgency score for each user terminal in the set of users to be scheduled, from the dimensions of identity attributes and spatial location.

[0088] The partitioning module 340 is used to divide the set of users to be scheduled into three target scheduling groups based on the comprehensive urgency score corresponding to each user terminal.

[0089] The search module 350 is used to search for the optimal combination of control parameters for three target scheduling groups under the constraints of inbound channel capacity, parameter monotonicity, and outbound link capacity, using an adaptive genetic algorithm as the core optimization engine.

[0090] The distribution module 360 ​​is used to distribute the corresponding optimal control parameter combinations to the three target scheduling groups respectively.

[0091] In some embodiments, module 310 is selected and is specifically used for: From multiple geostationary orbit satellites, select the geostationary orbit satellite with the largest coverage intensity to form a scheduling satellite group; or, if the difference between the maximum coverage intensity and the second largest coverage intensity is less than a preset threshold, select at least two geostationary orbit satellites from multiple geostationary orbit satellites in descending order of coverage intensity to form a scheduling satellite group.

[0092] In some embodiments, the calculation module 330 is specifically used for: For each user terminal in the set of users to be scheduled, a basic priority is determined based on the corresponding identity attribute; and a corresponding location attenuation weight is determined based on the shortest Euclidean distance from the spatial location of each user terminal to the geographical fence of the disaster area; the basic priority and location attenuation weight of each user terminal are weighted and fused to obtain the comprehensive urgency score of each user terminal.

[0093] In some embodiments, the target scheduling group includes: a first scheduling group, a second scheduling group, and a third scheduling group, wherein the scheduling urgency of the first scheduling group is greater than that of the second scheduling group, and the scheduling urgency of the second scheduling group is greater than that of the third scheduling group.

[0094] The 360 ​​distribution module is specifically used for: The system sends the corresponding optimal control parameter combination to the first scheduling group via the satellite outbound link; for user terminals in the second and third scheduling groups located in areas with normal terrestrial internet coverage, it pushes the corresponding optimal control parameter combination to the BeiDou terrestrial internet service platform so that the BeiDou terrestrial internet service platform can send the corresponding optimal control parameter combination to the corresponding user terminals; and sends the corresponding optimal control parameter combination to other user terminals in the second and third scheduling groups via the satellite outbound link.

[0095] In some embodiments, an adjustment module is also included.

[0096] The adjustment module is used to determine the system congestion level based on the inbound channel status in the previous scheduling period, and to adjust the resource scheduling frequency based on the system congestion level.

[0097] In some embodiments, the adjustment module is specifically used for: The status of the inbound channel during the previous scheduling cycle is continuously monitored, and the inbound channel occupancy rate and message collision rate are collected. The inbound channel occupancy rate and message collision rate are weighted and fused to obtain the system congestion level.

[0098] In some embodiments, an allocation module is also included.

[0099] The allocation module is used to dynamically allocate a dedicated inbound time slot for each user terminal in the first scheduling group based on the corresponding service type and real-time communication requirements; and to prohibit access from other scheduling groups within the dedicated inbound time slot.

[0100] The BeiDou short message emergency disaster relief communication resource hierarchical scheduling device provided in this disclosure can execute the above method embodiments. Its specific implementation principle and technical effects can be found in the above method embodiments, and will not be repeated here.

[0101] This application also provides a computer device. Please refer to the following for details. Figure 4 , Figure 4 This is a basic structural block diagram of the computer device in this embodiment.

[0102] The computer device includes a memory 410 and a processor 420 that are interconnected via a system bus. It should be noted that only a computer device with memory 410 and processor 420 is shown in the figure; however, it should be understood that it is not required to implement all the components shown, and more or fewer components may be implemented alternatively. Those skilled in the art will understand that the computer device described herein is a device capable of automatically performing numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes, but is not limited to, microprocessors, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0103] Computer devices can include desktop computers, laptops, handheld computers, and cloud servers. These devices allow for human-computer interaction with users through keyboards, mice, remote controls, touchpads, or voice-activated devices.

[0104] The memory 410 includes at least one type of readable storage medium, including non-volatile memory or volatile memory, such as flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, optical disk, etc. RAM may include static RAM or dynamic RAM. In some embodiments, the memory 410 may be an internal storage unit of a computer device, such as the hard disk or memory of the computer device. In other embodiments, the memory 410 may also be an external storage device of the computer device, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, or flash card equipped on the computer device. Of course, the memory 410 may include both internal storage units and external storage devices of the computer device. In this embodiment, the memory 410 is typically used to store the operating system and various application software installed on the computer device, such as the program code of the method described above. In addition, the memory 410 may also be used to temporarily store various types of data that have been output or will be output.

[0105] Processor 420 is typically used to perform overall operations of a computer device. In this embodiment, memory 410 is used to store program code or instructions, including computer operation instructions, and processor 420 is used to execute the program code or instructions stored in memory 410 or process data, such as program code that runs the methods described above.

[0106] In this article, the bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. This bus system can be divided into address bus, data bus, control bus, etc. For ease of illustration, only one thick line is used to represent it in the diagram, but this does not mean that there is only one bus or one type of bus.

[0107] Another embodiment of this application also provides a computer-readable medium, which may be a computer-readable signal medium or a computer-readable medium. A processor in a computer reads computer-readable program code stored in the computer-readable medium, enabling the processor to execute the functional actions specified in each step or combination of steps in the above method; and to generate means for implementing the functional actions specified in each block or combination of blocks in the block diagram.

[0108] Computer-readable media include, but are not limited to, electronic, magnetic, optical, electromagnetic, infrared memory or semiconductor systems, devices or apparatuses, or any suitable combination thereof, wherein the memory is used to store program code or instructions, the program code including computer operation instructions, and the processor is used to execute the program code or instructions of the above-described methods stored in the memory.

[0109] The definitions of memory and processor can be found in the description of the foregoing computer device embodiments, and will not be repeated here.

[0110] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0111] In the various embodiments of this application, the functional units or modules can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0112] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0113] In the claims, any reference signs placed between parentheses should not be construed as limiting the claims. The word "comprising" as described in this application does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. This application can be implemented by means of hardware comprising several different elements and by means of a suitably programmed computer. In the unit claims listing several means, several units of these means may be embodied by the same item of hardware. The use of "first," "second," and "third," etc., does not indicate any order and these words should be interpreted as names. Unless otherwise specified, the steps in the above embodiments should not be construed as limiting the order of execution.

[0114] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A hierarchical scheduling method for BeiDou short message emergency disaster relief communication resources, characterized in that, include: Based on the coverage strength of each geostationary orbit satellite to the disaster area, a scheduling satellite group was selected from multiple geostationary orbit satellites; The scheduling satellite constellation includes one geostationary orbit satellite or at least two geostationary orbit satellites; Based on the geographical locations of the disaster areas reported by each user, a set of users to be scheduled that are located within the coverage area of ​​the scheduling satellite constellation is determined; For each user terminal in the set of users to be scheduled, a comprehensive urgency score is jointly calculated from the dimensions of identity attributes and spatial location. Based on the comprehensive urgency score corresponding to each user terminal, the set of users to be scheduled is divided into three target scheduling groups; An adaptive genetic algorithm is used as the core optimization engine to search for the optimal combination of control parameters for the three target scheduling groups under the constraints of inbound channel capacity, parameter monotonicity, and outbound link capacity. The corresponding optimal control parameter combinations are issued to the three target scheduling groups respectively.

2. The method according to claim 1, characterized in that, Based on the coverage intensity of each geostationary orbit satellite over the disaster area, a scheduling satellite constellation was selected from multiple geostationary orbit satellites, including: From multiple geostationary orbit satellites, select the geostationary orbit satellite with the strongest coverage to form a scheduling satellite constellation; Alternatively, if the difference between the maximum coverage intensity and the second maximum coverage intensity is less than a preset threshold, then at least two geostationary orbit satellites are selected from multiple geostationary orbit satellites in descending order of coverage intensity to form a scheduling satellite constellation.

3. The method according to claim 1, characterized in that, For each user terminal in the set of users to be scheduled, a comprehensive urgency score is jointly calculated from the dimensions of identity attributes and spatial location, including: For each user terminal in the set of users to be scheduled, a basic priority is determined based on the corresponding identity attribute; and a corresponding location attenuation weight is determined based on the shortest Euclidean distance from the spatial location of each user terminal to the disaster area geofence. The basic priority and location attenuation weight of each user terminal are weighted and fused to obtain the comprehensive urgency score of each user terminal.

4. The method according to claim 1, characterized in that, The target scheduling group includes: a first scheduling group, a second scheduling group, and a third scheduling group, wherein the scheduling urgency of the first scheduling group is greater than that of the second scheduling group, and the scheduling urgency of the second scheduling group is greater than that of the third scheduling group. The corresponding optimal control parameter combinations are distributed to the three target scheduling groups respectively, including: The corresponding optimal control parameter combination is sent to the first scheduling group via the satellite outbound link; For user terminals in the second and third scheduling groups located in areas with normal terrestrial internet coverage, the corresponding optimal control parameter combination is pushed to the BeiDou terrestrial internet service platform so that the BeiDou terrestrial internet service platform can send the corresponding optimal control parameter combination to the corresponding user terminal. The optimal control parameter combination is sent to other user terminals in the second and third scheduling groups via the satellite outbound link.

5. The method according to claim 1, characterized in that, Also includes: Based on the inbound channel status in the previous scheduling period, the system congestion level is determined; and the resource scheduling frequency is adjusted based on the system congestion level.

6. The method according to claim 5, characterized in that, Based on the inbound channel status in the previous scheduling period, the system congestion level is determined by: Continuously monitor the status of the inbound channel in the previous scheduling cycle, and collect the inbound channel occupancy rate and message collision rate; The system congestion level is obtained by weighted fusion of the inbound channel occupancy rate and the message collision rate.

7. The method according to claim 4, characterized in that, Also includes: For user terminals in the first scheduling group, a dedicated inbound time slot is dynamically allocated for each user terminal based on the corresponding service type and real-time communication requirements; and access from other scheduling groups is prohibited within the dedicated inbound time slot.

8. A hierarchical scheduling device for BeiDou short message emergency disaster relief communication resources, characterized in that, include: The selection module is used to select and schedule a satellite constellation from multiple geostationary orbit satellites based on the coverage intensity of each geostationary orbit satellite over the disaster area. The scheduling satellite constellation includes one geostationary orbit satellite or at least two geostationary orbit satellites; The determination module is used to determine the set of users to be scheduled within the coverage area of ​​the scheduling satellite constellation based on the geographical location of the disaster area reported by each user. The calculation module is used to jointly calculate the corresponding comprehensive urgency score for each user terminal in the set of users to be scheduled from the dimensions of identity attributes and spatial location. The partitioning module is used to divide the set of users to be scheduled into three target scheduling groups based on the comprehensive urgency score corresponding to each user terminal. The search module is used to search for the optimal combination of control parameters for the three target scheduling groups under the constraints of inbound channel capacity, parameter monotonicity, and outbound link capacity, using an adaptive genetic algorithm as the core optimization engine. The distribution module is used to distribute the corresponding optimal control parameter combinations to the three target scheduling groups respectively.

9. A computer device, characterized in that, It includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the hierarchical scheduling method for Beidou short message emergency disaster relief communication resources as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the hierarchical scheduling method for BeiDou short message emergency disaster relief communication resources as described in any one of claims 1 to 7.

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