A non-terrestrial network resource representation method and system based on a double-scale time-varying graph

Abstract

The application discloses a non-ground network resource representation method and system based on a double-scale time-varying graph, initializes a set of network nodes in a network, records all time windows capable of data transmission, and establishes a double-scale resource time-varying graph, wherein a large scale represents the change of the topological structure of the network, and a small scale represents the minimum time unit capable of resource allocation. Specifically, by constructing the double-scale resource time-varying graph, the non-ground network resource is described with different time scales from the double scale: the large scale is used to describe the real-time change of the topological structure of the network resource, and the small scale is used to represent the real-time nature of the network resource and the burstiness of the task, so that the resource management problem in the high dynamic network can be efficiently converted into a classical problem in graph theory. Therefore, by using the double-scale time-varying graph method, the complexity of the resource management problem in the network is greatly simplified, and the solving efficiency and quality of the problem are ensured.

Description

Technical Field

[0001] This invention belongs to the field of non-terrestrial network technology, specifically relating to a non-terrestrial network resource characterization method and system based on dual-scale time-varying graphs. Background Technology

[0002] Non-terrestrial networks are a crucial infrastructure in my country, supporting integrated air-space-ground communications and widely used in public safety, media and entertainment, e-health, finance, automotive, and agricultural production. However, network node resources, including satellites and ground stations, are expensive and scarce, making it difficult to efficiently handle massive and complex data transmission tasks. This has resulted in a long-standing situation of resource scarcity and supply shortage in my country's non-terrestrial networks. Therefore, research is needed on efficient resource management methods suitable for non-terrestrial networks to improve network resource utilization efficiency and alleviate the contradiction between resource scarcity and business development.

[0003] However, non-terrestrial network resource management methods face many challenges: First, non-terrestrial networks are multi-layered heterogeneous networks, with many network nodes, complex network structures, and large network spatial scales, making network resource optimization difficult; second, the high-speed movement of satellites causes rapid changes in network topology, resulting in time-varying network resources; finally, space mission requirements are time-varying, mission arrival is uncertain, and mission execution is complex, often requiring joint optimization of multi-dimensional network resources such as storage and transmission resources.

[0004] To address the aforementioned challenges, traditional non-terrestrial network resource management methods only consider designing efficient network resource allocation methods, neglecting to characterize the highly dynamic nature of non-terrestrial network resources, thus hindering the improvement of network resource efficiency. To solve this problem, some works have begun to focus on researching characterization methods for non-terrestrial network resources. This is because resource characterization models are fundamental to achieving efficient network resource management. Unfortunately, these works are based on time-varying graph models with equal time slot partitioning, resulting in high model construction complexity and significantly limiting their application scope. Therefore, there is an urgent need to propose a low-complexity network resource characterization method applicable to the characteristics of non-terrestrial networks, providing a guarantee for designing efficient non-terrestrial network resource management and control. Summary of the Invention

[0005] The technical problem to be solved by this invention is to address the shortcomings of the prior art by providing a non-terrestrial network resource characterization method and system based on dual-scale time-varying graphs. This method solves the current technical problem of being unable to efficiently characterize the dynamics of non-terrestrial network resources and the suddenness of tasks, thereby enabling joint characterization of the dynamics of network resources and the suddenness of tasks, efficiently depicting the transition and transformation relationships between multi-dimensional network resources at different time scales, and thus ensuring the efficient utilization of non-terrestrial network resources.

[0006] The present invention adopts the following technical solution:

[0007] A non-terrestrial network resource characterization method based on dual-scale time-varying graphs, characterized in that,

[0008] Calculate all communication time windows between network nodes based on satellite ephemeris, spacecraft trajectory parameters, and ground station latitude and longitude information;

[0009] Calculate the time axis sequence based on the communication time window, and construct a large-scale time slot set and a large-scale time slot scale set;

[0010] A dual-scale time-varying resource map representing storage and transmission resources in the network is constructed based on a large-scale time slot set and a large-scale time slot scale set.

[0011] A set of small-scale time slots is constructed, and each large-scale time slot in the dual-scale resource time-varying graph is further divided into small-scale time slots, thereby achieving real-time updates of network resources and task information without increasing the size of the time-varying graph.

[0012] Specifically, calculate all communication time windows (st) between network nodes. p ,et p ), st p et represents the start time of the time window. p The end time of the time window is given, and the communication time windows P between network nodes are obtained as follows:

[0013] P={(st1,et1),(st2,et2),...,(st P ,et P )}

[0014] Where P is the total number of time windows in the time window set.

[0015] Specifically, the construction of the large-scale time slot set and the large-scale time slot scale set is as follows:

[0016] S301. Define the time set Q as all start and end times within the time window index set P. After removing duplicates from all elements in the time set Q, sort them in ascending order to obtain the time set. Q is the total number of moments within set Q;

[0017] S302. Construct a large-scale time-slot set K;

[0018] S303. Define the large-scale time slot scale set T as the set of all time scales in the large-scale time slot set K, which is represented as T = {T0, T1, ..., T} in ascending chronological order. K}, the k-th large-scale time slot (st) in the large-scale time slot set K k,et k ) in st k =T k-1 et k =T k , k = 1, 2, ..., K.

[0019] Furthermore, step S302 specifically includes:

[0020] S3021. Define a large-scale time slot set K to represent all large-scale time slots, and use K to represent the number of time slots in the large-scale time slot set K. In the initial state, K = 0. Define a time number q to iterate through the time in the time set Q from smallest to largest to complete the construction of the large-scale time slot set K. Initialize the time number q = 1.

[0021] S3022. Increment the time number q from 1 to Q-1, traverse the time set Q, and when the time number q = 1, take the time from the set Q. and As the start and end times of the first large-scale time slot, the large-scale time slot is constructed. And add it to set K. When the time number q = 2, 3, ..., Q-1, take the time from set Q according to the value of the current time number q. and As the start and end times of the current large-scale time slot, construct the large-scale time slot. After the traversal is complete, the large-scale time slot set K is constructed, resulting in K = {(st1, et1), (st2, et2), ..., (st K ,et K )}.

[0022] Furthermore, in step S3022, large-scale time slots are... With the last large-scale time slot (st) of the large-scale time slot set K K ,et K If the network node topology connections are inconsistent, then the large-scale time slot (st) will be compared. K+1 ,et K+1 If a large-scale time slot is added to set K, it is added to set K; otherwise, it is merged. K ,et K ) changed to (st K ,et K+1 ).

[0023] Specifically, constructing a two-scale time-varying resource graph representing storage and transmission resources in the network involves:

[0024] S401. Initialize the dual-scale resource time-varying graph G;

[0025] S402. Construct a vertex set V of a two-scale time-varying resource graph G, wherein the vertex set V is composed of the relay satellite vertex set V. RS Low-Earth Orbit Satellite Vertex Set V LS Ground station vertex set V GS The set of spacecraft vertices V AS It consists of four parts;

[0026] S403. Construct the edge set E of the dual-scale time-varying resource graph G, and store the edge set E. R With the transmission edge set E T It consists of two parts.

[0027] Furthermore, step S402 specifically involves:

[0028] S4021. For all relay satellite antennas in the relay satellite antenna set RS, construct the corresponding relay satellite antenna vertex set V in the dual-scale resource time-varying graph G. RS ;

[0029] S4022. For all low-Earth orbit (LEO) satellites in the LEO satellite set LS, construct the corresponding LEO satellite vertex set V in the dual-scale resource time-varying graph G. LS ;

[0030] S4023. For all ground stations in the ground station set GS, construct their corresponding ground station vertex set V in the dual-scale resource time-varying graph G. GS ;

[0031] S4024. For all aircraft in the aircraft set AS, construct the corresponding aircraft vertex set V in the dual-scale resource time-varying graph G. AS .

[0032] Furthermore, step S403 specifically involves:

[0033] S4031. Construct the storage edge set E R , including the relay satellite antenna storage side set E RSR Low-Earth Orbit Satellite Storage Side Set E RSL Spacecraft storage edge set E RA and ground station storage edge set E RG ;

[0034] S4032, Construct the transmission edge set E T This includes low-Earth orbit satellite-relay satellite antenna transmission side set. Aircraft-Ground Station Transmission Side Collection Spacecraft-Low Orbit Satellite Transmission Side Collection Low Earth Orbit Satellite-Ground Station Transmission Side Collection

[0035] Furthermore, in step S4031, for each relay satellite antenna rs in the relay satellite antenna set RS... r A relay satellite antenna storage edge is constructed between every two adjacent large-scale time slots; for each low-Earth orbit satellite ls in the low-Earth orbit satellite set LS l A low-Earth orbit satellite storage edge is constructed between every two adjacent large-scale time slots; for each ground station gs in the ground station set GS n A ground station storage edge is constructed between every two adjacent large-scale time slots; for each aircraft as in the aircraft set AS w Spacecraft storage edges are constructed between every two adjacent large-scale time slots.

[0036] Secondly, embodiments of the present invention provide a non-terrestrial network resource characterization system based on dual-scale time-varying maps, comprising:

[0037] The window module calculates all communication time windows between network nodes based on satellite ephemeris, spacecraft trajectory parameters, and ground station latitude and longitude information;

[0038] The collection module calculates the time axis sequence based on the communication time window and constructs a large-scale time slot set and a large-scale time slot scale set.

[0039] The characterization module constructs a dual-scale time-varying resource map representing storage and transmission resources in the network based on a large-scale time slot set and a large-scale time slot scale set.

[0040] The output module constructs a set of small-scale time slots, further dividing each large-scale time slot in the dual-scale resource time-varying graph into small-scale time slots, thereby achieving real-time updates of network resources and task information without increasing the size of the time-varying graph.

[0041] Compared with the prior art, the present invention has at least the following beneficial effects:

[0042] A non-terrestrial network resource representation method based on dual-scale time-varying graphs is proposed. This method jointly represents the dynamics of network resources and the burstiness of tasks, efficiently and with low complexity depicting the transition relationships between multi-dimensional network resources at different time scales, thus ensuring the utilization efficiency of non-terrestrial network resources. Furthermore, STK is used to calculate the communication time windows between all network nodes, enabling accurate large-scale time slot division and real-time capture of dynamic changes in network topology.

[0043] Furthermore, by constructing a large-scale time slot set and a large-scale time slot scale set, the aim is to efficiently divide large-scale time slots to prevent the same network topology from appearing in two adjacent large-scale time slots, thereby greatly reducing the number of large-scale time slots and achieving the goal of further reducing the number of nodes and edges in the dual-scale resource time-varying graph.

[0044] Furthermore, by constructing the connection relationships between network nodes that evolve with large-scale time slots in the dual-scale resource time-varying graph, efficient representation of highly dynamic network resources can be achieved. Spatially, storage edges are constructed to realize network connectivity between pairs of adjacent large-scale time slots, thereby providing a guarantee for the subsequent use of the method of this invention to efficiently model the resource management problem in highly dynamic networks as a classic problem in graph theory.

[0045] It is understandable that the beneficial effects of the second aspect mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here.

[0046] In summary, this invention constructs large-scale time slots in a dual-scale resource time-varying graph using communication time window information, accurately characterizing the evolution of the network topology of non-terrestrial networks over time. By constructing a set of large-scale time slots and a set of large-scale time slot scales to further reduce the number of large-scale time slots, and by further constructing small-scale time slots within each large-scale time slot, real-time updates of network resources and spatial task information are achieved without increasing the number of nodes and edges in the time-varying graph. This significantly reduces the complexity of time-varying graph construction, lowers storage space consumption, and ensures efficient management of network resources.

[0047] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0048] Figure 1 This is a schematic diagram of a non-terrestrial network scenario used in this invention;

[0049] Figure 2 This is a graph showing the change of communication connection relationships between network nodes over time in one application scenario of the present invention;

[0050] Figure 3 This is a flowchart illustrating the overall implementation of the present invention;

[0051] Figure 4 This is a schematic diagram of the large-scale time slot construction of the dual-scale resource time-varying map of the present invention;

[0052] Figure 5 This is a schematic diagram of the vertex set construction of the dual-scale resource time-varying graph of the present invention;

[0053] Figure 6 This is a schematic diagram of the edge set construction of the dual-scale resource time-varying graph of the present invention;

[0054] Figure 7 This is the dual-scale time-varying resource map constructed in this invention;

[0055] Figure 8 A schematic diagram of a computer device provided in an embodiment of the present invention;

[0056] Figure 9 This is a block diagram of a chip provided according to an embodiment of the present invention. Detailed Implementation

[0057] The technical solutions of the embodiments of the present invention 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 the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0058] In the description of this invention, it should be understood that the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0059] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0060] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes such combinations. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. Additionally, the character " / " in this invention generally indicates that the preceding and following objects have an "or" relationship.

[0061] It should be understood that although terms such as first, second, third, etc., may be used in the embodiments of the present invention to describe the preset range, these preset ranges should not be limited to these terms. These terms are only used to distinguish the preset ranges from one another. For example, without departing from the scope of the embodiments of the present invention, the first preset range may also be referred to as the second preset range, and similarly, the second preset range may also be referred to as the first preset range.

[0062] Depending on the context, the word "if" as used here can be interpreted as "when," "when," "in response to determination," or "in response to detection." Similarly, depending on the context, the phrase "if determination" or "if detection (of the stated condition or event)" can be interpreted as "when determination," "in response to determination," "when detection (of the stated condition or event)," or "in response to detection (of the stated condition or event)."

[0063] The accompanying drawings illustrate various structural schematic diagrams according to embodiments disclosed in this invention. These drawings are not to scale, and some details have been enlarged for clarity, and some details may have been omitted. The shapes of the various regions and layers shown in the drawings, as well as their relative sizes and positional relationships, are merely exemplary and may deviate from reality due to manufacturing tolerances or technical limitations. Furthermore, those skilled in the art can design regions / layers with different shapes, sizes, and relative positions as needed.

[0064] This invention provides a non-terrestrial network resource representation method based on a dual-scale time-varying graph. It initializes the set of each network node in the network, records all time windows in which data can be transmitted, and establishes a dual-scale resource time-varying graph. The large scale represents the changes in the network topology, and the small scale represents the smallest time unit in which resources can be allocated.

[0065] Specifically, by constructing a dual-scale time-varying resource map, the inheritance relationship of non-terrestrial network resources at different scales is characterized from a dual-scale perspective:

[0066] By using a large scale to depict the real-time changes in the topology of network resources and a small scale to represent the real-time nature of network resources and the suddenness of tasks, the resource management problem in highly dynamic networks can be efficiently transformed into a classic problem in graph theory.

[0067] Therefore, this invention simplifies the complexity of resource management problems in networks, thereby ensuring the efficiency and quality of problem-solving.

[0068] Please see Figure 1 and Figure 2 These represent data transmission scenarios in an integrated air-space-ground network, as well as changes in the network topology between some satellites, aircraft, and ground stations within the data transmission scenario. These scenarios include two antennas of a relay satellite, two low-orbit satellites, an aircraft, and a ground station.

[0069] Please see Figure 3 This invention discloses a non-terrestrial network resource characterization method based on dual-scale time-varying maps, comprising the following steps:

[0070] S1. Initialize the set of satellites, ground stations, and observation points of the non-terrestrial network to be characterized;

[0071] Initialize the relay satellite antenna set RS = {rs1, rs2, ..., rs} of the network to be characterized. R The low-Earth orbit satellite set LS = {ls1, ls2, ..., ls} L The ground station set GS = {gs1, gs2, ..., gs} N} and the set of aircraft AS = {as1,as2,...,as W}

[0072] Among them, rs r This represents the r-th relay satellite antenna. There are a total of R relay satellite antennas. ls l This represents the l-th low-Earth orbit satellite. There are a total of L low-Earth orbit satellites. gs n This represents the nth ground station. There are N ground stations in total. w Let w represent the w-th aircraft. There are a total of W aircraft.

[0073] S2. Import the satellite ephemeris, spacecraft trajectory parameters, and ground station latitude and longitude information into the STK (Satellite Tool Kit) software, calculate all communication time windows between network nodes, and use a two-dimensional array (st p ,et p ) indicates that st p et represents the start time of the time window. p Let p represent the end time of the time window, p represent the time window number, and P represent the set of all time windows, i.e., P = {(st1, et1), (st2, et2), ..., (st...}. P ,et P )}, where P is the total number of time windows in the time window set;

[0074] Please see Figure 2 The time windows during which each network node can communicate are obtained, and the time window index set P is as follows:

[0075] P={(st1,et1),(st2,et2),(st3,et3),(st4,et4),(st5,et5)}={(T0,T1),(T1,T2),(T2,T3),(T3,T4),(T4,T5)}

[0076] S3. Construct a large-scale time slot set and a large-scale time slot scale set;

[0077] S301. Define the time set Q as all start and end times within the time window index set P, i.e., Q = {st1, st2, ..., st...}P}∪{et1,et2,…,et P}, after removing duplicates from all elements in the time set Q and sorting them in ascending order, we obtain the time set Q, denoted as} In the form of, Q is the total number of moments within set Q;

[0078] S302. Construct a large-scale time-slot set K;

[0079] S3021. Define a large-scale time slot set K, representing all large-scale time slots, and use K to represent the number of time slots in the large-scale time slot set K. The value of K is determined by the size of the set K. In the initial state, the set K is empty, so K = 0. Define a time number q, which is used to traverse the times in the time set Q in ascending order to complete the construction of the large-scale time slot set K. Initialize the time number q = 1, and q will be incremented during the traversal.

[0080] S3022. Increment the time number q from 1 to Q-1, traverse the time set Q, and when the time number q = 1, take the time from the set Q. and As the start and end times of the first large-scale time slot, the large-scale time slot is constructed. And add it to set K. When the time number q = 2, 3, ..., Q-1, take the time from set Q according to the value of the current time number q. and As the start and end times of the current large-scale time slot, construct the large-scale time slot. This large-scale time slot and the last large-scale time slot (st) of the large-scale time slot set K K ,et K If the network node topology connections of the two are inconsistent, then the large-scale time slot (st) will be compared. K+1 ,et K+1 If a large-scale time slot is added to set K, then it means that the two large-scale time slots have the same network topology and need to be merged. Therefore, the large-scale time slot (st) is added to set K. K ,et K ) changed to (st K ,et K+1 After traversing all the data, the large-scale time slot set K is constructed, resulting in K = {(st1, et1), (st2, et2), ..., (st...}. K ,et K Since adjacent large-scale time slots in the large-scale time slot set K are also temporally adjacent, the start and end times of large-scale time slots also have st k =et k-1The properties of k, k = 2, 3, ..., K.

[0081] S303. Define the large-scale time slot scale set T as the set of all time scales in the large-scale time slot set K, i.e., T = {st1, st2, ..., st...} K}∪{et K This set contains K+1 time points. For ease of writing, it is represented as T = {T0, T1, ..., T} in ascending chronological order. K According to this expression, the k-th large-scale time slot (st) in the large-scale time slot set K k ,et k ) in st k =T k-1 et k =T k , k = 1, 2, ..., K.

[0082] Please see Figure 2 Thus, T = {T0, T1, T2, T3, T4, T5}, and see [reference]. Figure 4 Construct large-scale time slots of a dual-scale resource time-varying graph G.

[0083] S4. Construct a two-scale resource time-varying graph G = (V, E), where V represents the set of vertices in the two-scale resource time-varying graph and E represents the set of edges in the two-scale resource time-varying graph, representing the storage and transmission resources in the network.

[0084] S401. Initialize the dual-scale resource time-varying graph G;

[0085] Based on the number of elements K in the large-scale time slot set K, the resource time-varying graph G is a K-layer directed graph. An empty K-layer directed graph G = {G1, G2, ..., G...} is initialized. K}, where G k Let be a directed graph of the k-th layer, representing the network topology connections within the k-th large-scale time slot of the network, where k = 1, 2, ..., K.

[0086] S402. Construct a vertex set V of a two-scale time-varying resource graph G, wherein the vertex set V is composed of the relay satellite vertex set V. RS Low-Earth Orbit Satellite Vertex Set V LS Ground station vertex set V GS The set of spacecraft vertices V AS It consists of four parts, namely V = V RS ∪V LS ∪V GS ∪V AS ;

[0087] S4021. For all relay satellite antennas in the relay satellite antenna set RS, construct the corresponding relay satellite antenna vertex set V in the dual-scale resource time-varying graph G. RS ;

[0088] Specifically, a vertex set is constructed within each large-scale time slot, for example, in the k-th large-scale time slot (st) of the large-scale time slot set K. k ,et k Construct the directed graph G at the k-th layer. k The corresponding vertex set Among the vertices rs represents the relay satellite antenna in the k-th large-scale time slot. r Relay satellite antenna vertex set V RS It is formed by merging the vertex sets within the aforementioned K large-scale time slots, i.e. This set represents all relay satellite antennas within all large time slot sets.

[0089] Please see Figure 5 ,have to: and Therefore, we can conclude that:

[0090] S4022. For all low-Earth orbit (LEO) satellites in the LEO satellite set LS, construct the corresponding LEO satellite vertex set V in the dual-scale resource time-varying graph G. LS ;

[0091] Specifically, a vertex set is constructed within each large-scale time slot, for example, in the k-th large-scale time slot (st) of the large-scale time slot set K. k ,et k Construct the directed graph G at the k-th layer. k The corresponding vertex set Among the vertices This represents the low-orbit satellite ls in the k-th large-scale time slot. l Low Earth Orbit Satellite Vertex Set V LS It is formed by merging the vertex sets within the aforementioned K large-scale time slots, i.e. This set represents all low-Earth orbit satellites within all large time slot sets.

[0092] Please see Figure 5 ,have to and Therefore, we can conclude that:

[0093] S4023. For all ground stations in the ground station set GS, construct their corresponding ground station vertex set V in the dual-scale resource time-varying graph G. GS ;

[0094] Specifically, a vertex set is constructed within each large-scale time slot, for example, in the k-th large-scale time slot (st) of the large-scale time slot set K. k ,et k Construct the k-th layer directed graph G within the graph. k The corresponding vertex set Among the vertices This represents the ground station gs in the k-th large-scale time slot. n Ground station vertex set V GS It is formed by merging the vertex sets within the aforementioned K large-scale time slots, i.e. This set represents all ground stations within all large time slot sets.

[0095] Please see Figure 5 ,have to and Therefore, we can conclude that:

[0096] S4024. For all aircraft in the aircraft set AS, construct the corresponding aircraft vertex set V in the dual-scale resource time-varying graph G. AS .

[0097] Specifically, a vertex set is constructed within each large-scale time slot, for example, in the k-th large-scale time slot (st) of the large-scale time slot set K. k ,et k Construct the k-th layer directed graph G within the graph. k The corresponding vertex set Among the vertices The spacecraft as in the k-th large-scale time slot w The set of spacecraft vertices V AS It is formed by merging the vertex sets within the aforementioned K large-scale time slots, i.e. This set represents all aircraft within all large time-slot sets, where the vertex set V = V of the dual-scale resource time-varying graph G. RS ∪V LS ∪V GS ∪V AS Construction complete.

[0098] Please see Figure 5 ,have to and Therefore, we can conclude that: Finally

[0099] S403. Construct the edge set E of the dual-scale time-varying resource graph G. This set is generated by storing the edge set E. R With the transmission edge set E T It consists of two parts, namely E = ER ∪E T ;

[0100] S4031. Construct the storage edge set E R , including the relay satellite antenna storage side set E RSR Low-Earth Orbit Satellite Storage Side Set E RSL Spacecraft storage edge set E RA and ground station storage edge set E RG E R =E RSR ∪E RSL ∪E RG ∪E RA ;

[0101] For each relay satellite antenna rs in the relay satellite antenna set RS r Relay satellite antenna storage edges are constructed between every two adjacent large-scale time slots.

[0102] Specifically, for the k-th large-scale time slot and the (k+1)-th large-scale time slot, numbered rs r The vertex corresponding to the relay satellite antenna is and Therefore, a relay satellite antenna storage edge is constructed in the two-scale resource time-varying graph G. Where rs r ∈RS, k=1,2,…,K-1, define the set of relay satellite antenna storage edges in the k-th layer. This represents all relay satellite antenna storage edges between the k-th large-scale time slot and the (k+1)-th large-scale time slot, i.e. Define the storage edge set for relay satellite antennas This represents the storage edge for all relay satellite antennas.

[0103] For each low-Earth orbit satellite ls in the low-Earth orbit satellite set LS l Low-Earth orbit satellite storage edges are constructed between every two adjacent large-scale time slots.

[0104] Specifically, for the k-th large-scale time slot and the (k+1)-th large-scale time slot, numbered ls l The vertex corresponding to the low-orbit satellite is and ls l ∈LS, k=1,2,...,K-1, define the set of low-Earth orbit satellite storage edges for the k-th layer. This represents all low-Earth orbit satellite storage edges between the k-th large-scale time slot and the (k+1)-th large-scale time slot, i.e. Define the storage edge set for low-Earth orbit satellites This indicates the storage edge for all low-Earth orbit satellites.

[0105] For each ground station gs in the ground station set GS n Ground station storage edges are constructed between every two adjacent large-scale time slots.

[0106] Specifically, for the k-th large-scale time slot and the (k+1)-th large-scale time slot, numbered gs n The vertex corresponding to the ground station is and Where gs n Let ∈GS, k=1,2,…,K-1, and define the set of ground station storage edges for the k-th layer. This represents all ground station storage edges between the k-th large-scale time slot and the (k+1)-th large-scale time slot, i.e. Define the ground station storage edge set This indicates all ground station storage edges.

[0107] For each aircraft as in the set of aircraft AS w Spacecraft storage edges are constructed between every two adjacent large-scale time slots.

[0108] Specifically, for the k-th large-scale time slot and the (k+1)-th large-scale time slot, numbered as w The vertex corresponding to the aircraft is and Where as w Let ∈AS, k=1,2,…,K-1, and define the set of spacecraft storage edges for the k-th layer. This represents all spacecraft storage edges between the k-th large-scale time slot and the (k+1)-th large-scale time slot, i.e. Define the spacecraft storage edge set This represents all the spacecraft storage edges.

[0109] At this time, the storage edge set E R =E RSR ∪E RSL ∪E RG ∪E RA The construction is complete, including the relay satellite antenna storage side. The capacity is defined as the size of the relay satellite storage space within the k-th large-scale time slot; the low-Earth orbit satellite storage edge The capacity is defined as the storage space size of the low-Earth orbit satellite within the k-th large-scale time slot; the ground station storage edge The capacity is defined as the size of the ground station storage space within the k-th large-scale time slot; the spacecraft storage edge The capacity is defined as the size of the spacecraft's storage space within the k-th large-scale time slot, where k = 1, 2, ..., K-1;

[0110] See Figure 6The constructed storage edge set E R =E RSR ∪E RSL ∪E RG ∪E RA Each subset is as follows:

[0111]

[0112]

[0113] as well as

[0114] S4032, Construct the transmission edge set E T This includes low-Earth orbit satellite-relay satellite antenna transmission side set. Aircraft-Ground Station Transmission Side Collection Spacecraft-Low Orbit Satellite Transmission Side Collection Low Earth Orbit Satellite-Ground Station Transmission Side Collection Right now

[0115] For each low-Earth orbit satellite ls in the low-Earth orbit satellite set LS l and each relay satellite antenna rs in the relay satellite antenna set RS r In the k-th time slot of the large-scale time slot set K, if the low-orbit satellite ls l In relay satellite antenna rs r Within the observation range, a low-Earth orbit satellite-relay satellite antenna transmission side is constructed in the k-th layer of the dual-scale resource time-varying map G. in This represents the low-orbit satellite ls within the k-th large-scale time slot. l , This represents the relay satellite antenna rs in the k-th large-scale time slot. r Low Earth Orbit Satellite-Relay Satellite Antenna Transmission Side Set It includes all low-Earth orbit satellite-relay satellite antenna transmission sides.

[0116] Please see Figure 2The low-Earth orbit (LEO) satellite-relay satellite antenna transmission edge exists in two scenarios: between u1 and v1, and between u2 and v2. In the (u1, v1) scenario, LEO satellite u1 can communicate with relay satellite antenna v1 in the first and second large-scale time slots. From the third time slot onwards, due to satellite motion, it leaves the communication range and can no longer communicate with v1. Similarly, in the (u2, v2) scenario, LEO satellite u2 can communicate with relay satellite antenna v2 in the second and third large-scale time slots. In the first time slot, satellite u2 is not yet within the communication range. From the third time slot onwards, satellite u2 leaves the communication range and therefore cannot communicate with v2. Based on the above analysis, the transmission edges that can be added to the dual-scale resource time-varying graph G are: and Specifically, such as Figure 6 As shown.

[0117] For each aircraft as in the set of aircraft AS w and each ground station GS in the ground station set GS n In the k-th time slot of the large-scale time slot set K, if the spacecraft as w At ground station GS n Within the observation range, a spacecraft-ground station transmission edge is constructed in the k-th layer of the two-scale resource time-varying map G. in The spacecraft as in the k-th large-scale time slot w , The ground station gs represents the time slot k on the large scale. n Spacecraft-Ground Station Transmission Side Collection It includes all the aircraft-ground station transmission edges.

[0118] Please see Figure 2 The spacecraft-ground station transmission edge exists between u3 and v1. During the first four large-scale time slots, aircraft u3 can communicate with the relay satellite's antenna v1. Therefore, as... Figure 6 The transmission edges added to the two-scale resource time-varying graph G are shown below: and

[0119] For each low-Earth orbit satellite ls in the low-Earth orbit satellite set LS l and each ground station GS in the ground station set GS n In the k-th time slot of the large-scale time slot set K, if the low-orbit satellite ls l At ground station GS n Within the observation range, a low-orbit satellite-ground station antenna transmission edge is constructed in the k-th layer of the two-scale resource time-varying map G. in This represents the low-orbit satellite ls within the k-th large-scale time slot. l , The ground station gs represents the time slot k on the large scale. n Low Earth Orbit Satellite-Ground Station Transmission Side Collection It includes all low-Earth orbit satellite-to-ground station transmission sides.

[0120] Please see Figure 2 The low-Earth orbit (LEO) satellite-to-ground station transmission edge exists in two cases: between u1 and v3, and between u2 and v3. Where (u1, v3) represents the case where LEO satellite u1 can communicate with ground station v3 in the 4th and 5th large-scale time slots, but not in the remaining time slots; and (u2, v3) represents the case where LEO satellite u2 can communicate with ground station v3 in the 4th large-scale time slot, but not in the remaining time slots. Therefore, if... Figure 6 The transmission edges added to the two-scale resource time-varying graph G are shown below: and

[0121] At this time, the transmission edge set Once constructed, for the k-th large-scale time slot (st k ,et k Define the large-scale time slot length τ. k For τ k =et k -st k =T k -T k-1 , representing the total time length of this large-scale time slot from start to finish, k = 1, 2, ..., K, where k represents the transmission length of the low-Earth orbit satellite-relay satellite antenna within this large-scale time slot. The capacity is defined as vsl l For low-orbit satellites ls l Data transmission rate, vrr r For relay satellite antennas RS r Data reception rate; spacecraft-ground station transmission side The capacity is defined as VSA w For aircraft as w Data transmission rate, VRG n For ground station GS n Data reception rate; spacecraft-low Earth orbit satellite transmission side The capacity is defined as vrl l For low-orbit satellites ls l Data reception rate; Low Earth Orbit satellite-to-ground station transmission side The capacity is defined as vsl l For low-orbit satellites ls n Data transmission rate, VRG n For ground station gl n Data reception rate.

[0122] S5. Construct a small-scale time slot set ST, and further divide each large-scale time slot in the dual-scale resource time-varying graph G into small-scale time slots, so as to realize real-time updates of network resources and task information without increasing the size of the time-varying graph.

[0123] The length of each small-scale time slot is no greater than δ, where δ is a constant representing the accuracy requirement of the small-scale time slot. The value of δ is determined by the specific problem. For the k-th large-scale time slot (st k ,et k ), k = 1, 2, ..., K, large-scale time slot length τ k =T k -T k-1 Define the set of small-scale time slot scales within this large-scale time slot as ST. k The number of small-scale time slots is Therefore ST k ={st k ,st k +δ,st k +2δ,…,et k See} Figure 7 It can be seen that: ST k ={st k ,st k +δ,st k +2δ,…,et k}

[0124] In another embodiment of the present invention, a non-terrestrial network resource characterization system based on a dual-scale time-varying graph is provided. This system can be used to implement the above-mentioned non-terrestrial network resource characterization method based on a dual-scale time-varying graph. Specifically, the non-terrestrial network resource characterization system based on a dual-scale time-varying graph includes a window module, a set module, a characterization module, and an output module.

[0125] The window module calculates all communication time windows between network nodes based on the satellite ephemeris, spacecraft trajectory parameters, and ground station latitude and longitude information.

[0126] The collection module calculates the time axis sequence based on the communication time window and constructs a large-scale time slot set and a large-scale time slot scale set.

[0127] The characterization module constructs a dual-scale time-varying resource map representing storage and transmission resources in the network based on a large-scale time slot set and a large-scale time slot scale set.

[0128] The output module constructs a set of small-scale time slots, further dividing each large-scale time slot in the dual-scale resource time-varying graph into small-scale time slots, thereby achieving real-time updates of network resources and task information without increasing the size of the time-varying graph.

[0129] In another embodiment of the present invention, a terminal device is provided, comprising a processor and a memory. The memory stores a computer program, the computer program including program instructions, and the processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions to achieve a corresponding method flow or corresponding function. The processor described in this embodiment of the present invention can be used for the operation of a non-terrestrial network resource characterization method based on a dual-scale time-varying map, including:

[0130] Based on the satellite ephemeris, spacecraft trajectory parameters, and ground station latitude and longitude information, calculate all communication time windows between network nodes; calculate the time axis sequence based on the communication time windows, and construct a large-scale time slot set and a large-scale time slot scale set; construct a dual-scale resource time-varying map representing the storage and transmission resources in the network based on the large-scale time slot set and the large-scale time slot scale set; construct a small-scale time slot set, and further divide each large-scale time slot in the dual-scale resource time-varying map into small-scale time slots.

[0131] Please see Figure 8The terminal device is a computer device. In this embodiment, the computer device 60 includes a processor 61, a memory 62, and a computer program 63 stored in the memory 62 and executable on the processor 61. When executed by the processor 61, the computer program 63 implements the fluid composition calculation method in the reservoir stimulation wellbore of this embodiment. To avoid repetition, details are omitted here. Alternatively, when executed by the processor 61, the computer program 63 implements the functions of each model / unit in the non-surface network resource characterization system based on dual-scale time-varying maps of this embodiment. To avoid repetition, details are omitted here.

[0132] Computer device 60 can be a desktop computer, laptop, handheld computer, cloud server, or other computing device. Computer device 60 may include, but is not limited to, a processor 61 and a memory 62. Those skilled in the art will understand that... Figure 8 This is merely an example of computer device 60 and does not constitute a limitation on computer device 60. It may include more or fewer components than shown, or combine certain components, or different components. For example, computer device may also include input / output devices, network access devices, buses, etc.

[0133] The processor 61 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0134] The memory 62 can be an internal storage unit of the computer device 60, such as a hard disk or RAM of the computer device 60. The memory 62 can also be an external storage device of the computer device 60, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., provided on the computer device 60.

[0135] Furthermore, the memory 62 may include both internal storage units of the computer device 60 and external storage devices. The memory 62 is used to store computer programs and other programs and data required by the computer device. The memory 62 can also be used to temporarily store data that has been output or will be output.

[0136] Please see Figure 9 The terminal device is a chip. In this embodiment, the chip 600 includes a processor 622, which may be one or more, and a memory 632 for storing computer programs executable by the processor 622. The computer program stored in the memory 632 may include one or more modules, each corresponding to a set of instructions. Furthermore, the processor 622 may be configured to execute the computer program to perform the aforementioned non-terrestrial network resource characterization method based on dual-scale time-varying maps.

[0137] Additionally, chip 600 may also include a power supply component 626 and a communication component 650. The power supply component 626 can be configured to perform power management of chip 600, and the communication component 650 can be configured to enable communication of chip 600, such as wired or wireless communication. Furthermore, chip 600 may also include an input / output (I / O) interface 658. Chip 600 can operate on an operating system stored in memory 632.

[0138] In another embodiment of the present invention, a storage medium is also provided, specifically a computer-readable storage medium (memory). This computer-readable storage medium is a memory device in a terminal device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the terminal device and extended storage media supported by the terminal device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device.

[0139] One or more instructions stored in a computer-readable storage medium can be loaded and executed by a processor to implement the corresponding steps of the non-terrestrial network resource characterization method based on dual-scale time-varying maps in the above embodiments; one or more instructions in the computer-readable storage medium are loaded and executed by the processor in the following steps:

[0140] Based on the satellite ephemeris, spacecraft trajectory parameters, and ground station latitude and longitude information, calculate all communication time windows between network nodes; calculate the time axis sequence based on the communication time windows, and construct a large-scale time slot set and a large-scale time slot scale set; construct a dual-scale resource time-varying map representing the storage and transmission resources in the network based on the large-scale time slot set and the large-scale time slot scale set; construct a small-scale time slot set, and further divide each large-scale time slot in the dual-scale resource time-varying map into small-scale time slots.

[0141] In summary, the non-terrestrial network resource characterization method and system based on dual-scale time-varying maps of the present invention has the following advantages:

[0142] 1) This invention accurately characterizes the evolution of the network topology of non-terrestrial networks over time by constructing large-scale time slots in a dual-scale resource time-varying graph. Compared with traditional time-varying graphs, this invention greatly reduces the scale of time-varying graph construction, reduces storage space consumption, and provides a guarantee for efficient management of network resources.

[0143] 2) This invention further constructs small-scale time slots in the dual-scale resource time-varying map to realize real-time updates of network resources and space mission information, thereby ensuring real-time access of space missions and greatly improving the efficiency of mission completion.

[0144] 3) This invention constructs a dual-scale time-varying graph of resources to characterize the connection relationship between multidimensional network resources at different time scales in an integrated air-space-ground network. This can efficiently transform the resource management problem in highly dynamic networks into a classic problem in graph theory, greatly simplifying the complexity of resource management in the network and improving the efficiency and quality of the solution.

[0145] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments 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. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0146] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0147] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed in this invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0148] In the embodiments provided by this invention, it should be understood that the disclosed devices / terminals and methods can be implemented in other ways. For example, the device / terminal 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 devices or units may be electrical, mechanical, or other forms.

[0149] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0150] Furthermore, the functional units in the various embodiments of the present invention 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.

[0151] If the integrated module / 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, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random-access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electrical carrier signals and telecommunication signals.

[0152] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0153] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0154] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0155] The above content is only for illustrating the technical concept of the present invention and should not be construed as limiting the scope of protection of the present invention. Any modifications made to the technical solution based on the technical concept proposed in this invention shall fall within the scope of protection of the claims of this invention.

Claims

1. A non-terrestrial network resource representation method based on dual-scale time-varying maps, characterized in that, Includes the following steps: Calculate all communication time windows between network nodes based on satellite ephemeris, spacecraft trajectory parameters, and ground station latitude and longitude information; The timeline sequence is calculated based on the communication time window, and a large-scale time slot set and a large-scale time slot scale set are constructed, specifically as follows: S301, Define the time set Represents the set of time window indices Set all start and end times within the time frame. After removing duplicates from all elements and sorting them in ascending order, we obtain the time set. , , For set The total number of time intervals within a given period; S302, Constructing large-scale time-slot assemblies ; S303, Define a large-scale time slot scale set Large-scale time slot collection The set of all time scales, arranged in ascending chronological order, is represented as: Large-scale time-slot collection The first in Large-scale time slots middle , , ; A dual-scale time-varying resource map representing storage and transmission resources in the network is constructed based on a large-scale time slot set and a large-scale time slot scale set, specifically as follows: S401. Initialize the dual-scale resource time-varying graph. ; S402. Constructing a dual-scale time-varying graph of resources. vertex set Vertex set Set of relay satellite vertices Low-Earth Orbit Satellite Vertex Set Ground station vertex set , Set of aircraft vertices It consists of four parts; S403. Construct the edge set of a two-scale time-varying resource graph G. , by storing edge set With transmission edge set It consists of two parts; A set of small-scale time slots is constructed, and each large-scale time slot in the dual-scale resource time-varying graph is further divided into small-scale time slots, thereby achieving real-time updates of network resources and task information without increasing the size of the time-varying graph.

2. The non-terrestrial network resource characterization method based on dual-scale time-varying maps according to claim 1, characterized in that, Calculate all communication time windows between network nodes , Indicates the start time of the time window. This indicates the end time of the time window, and yields all communication time windows between network nodes. as follows: in, This represents the total number of time windows within the time window set.

3. The non-terrestrial network resource characterization method based on dual-scale time-varying maps according to claim 1, characterized in that, Step S302 specifically includes: S3021. Define large-scale time slot sets. Representing all large-scale time slots, and using Represents a large-scale time slot set The number of internal time slots, in the initial state Define time number Used for time sets The time slots are traversed sequentially from smallest to largest to complete a large-scale time slot set. Construction, initialization time number ; S3022, Number the time. from Towards Increasing, for the set of times Perform traversal and time numbering. When, take the set The moment in and As the start and end times of the first large-scale time slot, the large-scale time slot is constructed. and add to the set In the middle, the time number At that time, according to the current number The value is taken from the set. The moment in and As the start and end times of the current large-scale time slot, construct the large-scale time slot. After the traversal is complete, a large-scale time slot set is finished. The construction, obtained .

4. The non-terrestrial network resource characterization method based on dual-scale time-varying maps according to claim 3, characterized in that, In step S3022, large-scale time slots are... With large-scale time slot sets The last large-scale time slot If the network node topology connections are inconsistent, then large-scale time slots will be compared. Add to collection Otherwise, merge them to create large-scale time slots. Modified to .

5. The non-terrestrial network resource characterization method based on dual-scale time-varying maps according to claim 1, characterized in that, Step S402 is as follows: S4021, For relay satellite antenna assemblies Construct a two-scale resource time-varying map of all relay satellite antennas. The corresponding set of relay satellite antenna vertices ; S4022, For low-Earth orbit satellite ensembles Construct a two-scale time-varying map of resources for all low-Earth orbit satellites. The corresponding set of low-orbit satellite vertices ; S4023, Regarding ground station assembly For all ground stations, construct their time-varying maps in a two-scale resource format. The corresponding set of ground station vertices ; S4024, Regarding aircraft collections For all the spacecraft, construct their time-varying graphs in a two-scale resource environment. The corresponding set of spacecraft vertices .

6. The non-terrestrial network resource characterization method based on dual-scale time-varying maps according to claim 1, characterized in that, Step S403 is as follows: S4031. Construct the storage edge set , including relay satellite antenna storage side set Low-Earth Orbit Satellite Storage Side Collection Aircraft storage edge set and ground station storage edge set ; S4032, Construct the transmission edge set This includes low-Earth orbit satellite-relay satellite antenna transmission side set. Spacecraft-Ground Station Transmission Side Collection Spacecraft-Low Orbit Satellite Transmission Side Collection Low-Earth Orbit Satellite-Ground Station Transmission Side Collection .

7. The non-terrestrial network resource characterization method based on dual-scale time-varying maps according to claim 6, characterized in that, In step S4031, for the relay satellite antenna set Each relay satellite antenna in A relay satellite antenna storage edge is constructed between every two adjacent large-scale time slots; for low-Earth orbit satellite ensembles Each low-Earth orbit satellite Low-Earth orbit satellite storage edges are constructed between every two adjacent large-scale time slots; for ground station ensembles Each ground station Ground station storage edges are constructed between every two adjacent large-scale time slots; for the aircraft ensemble Each aircraft in Spacecraft storage edges are constructed between every two adjacent large-scale time slots.

8. A non-terrestrial network resource representation system based on dual-scale time-varying maps, characterized in that, include: The window module calculates all communication time windows between network nodes based on satellite ephemeris, spacecraft trajectory parameters, and ground station latitude and longitude information; The set module calculates the timeline sequence based on the communication time window, and constructs a large-scale time slot set and a large-scale time slot scale set, specifically as follows: Define the set of times Represents the set of time window indices Set all start and end times within the time frame. After removing duplicates from all elements and sorting them in ascending order, we obtain the time set. , , For set The total number of intra-time moments; constructing a large-scale time slot set. Define a large-scale time slot scale set. Large-scale time slot collection The set of all time scales, arranged in ascending chronological order, is represented as: Large-scale time-slot collection The first in Large-scale time slots middle , , ; The characterization module constructs a dual-scale time-varying resource map representing storage and transmission resources in the network based on a large-scale time slot set and a large-scale time slot scale set. Specifically: Initialize dual-scale resource time-varying graph Constructing a two-scale time-varying map of resources vertex set Vertex set Set of relay satellite vertices Low-Earth Orbit Satellite Vertex Set Ground station vertex set , Set of aircraft vertices It consists of four parts; constructing the edge set of a two-scale time-varying resource graph G. , by storing edge set With transmission edge set It consists of two parts; The output module constructs a set of small-scale time slots, further dividing each large-scale time slot in the dual-scale resource time-varying graph into small-scale time slots, thereby achieving real-time updates of network resources and task information without increasing the size of the time-varying graph.

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