CN117200870A

CN117200870A - Online data unloading method and system for space-air-ground integrated network

Info

Publication number: CN117200870A
Application number: CN202311322399.0A
Authority: CN
Inventors: 何立军; 贾子晔; 贺亮; 王丽
Original assignee: Northwestern Polytechnical University
Current assignee: Northwestern Polytechnical University
Priority date: 2023-10-12
Filing date: 2023-10-12
Publication date: 2023-12-08

Abstract

The invention discloses an on-line data unloading method and system for an air-ground integrated network, which accurately characterizes the dynamic property of the air-ground integrated network from different time scales by constructing a double-scale resource time-varying graph, namely, characterizes the rapid change of network topology from a large-scale time slot, and updates the information of tasks and network resources from a small-scale time slot in real time; and then, in each small-scale time slot, the improvement of the utilization rate of network resources is realized by jointly optimizing power distribution and data unloading. Specifically, by utilizing the characteristics of the communication links of the space-earth integrated network, an optimal power distribution method is designed, a weighted two-part graph is constructed to be matched with an optimal ground station or relay satellite for each low-orbit user satellite, the complex problem of combined optimization of space data unloading and power control is integrally converted into a classical two-part graph matching problem in graph theory, the solving complexity of the data unloading problem is greatly reduced, and the data unloading efficiency of the space-earth integrated network is effectively improved.

Description

Online data unloading method and system for space-air-ground integrated network

Technical Field

The invention belongs to the technical field of space information, and particularly relates to an on-line data unloading method and system for an air-space-ground integrated network.

Background

The ground network is limited by service coverage, and is mainly used for providing networking service for areas with high population density, and is difficult to cover in areas with sparse population such as mountain areas, oceans, deserts and the like. Non-terrestrial networks including low-orbit, medium-orbit, high-orbit satellites, space platforms, and unmanned aerial vehicles are receiving increasing attention due to their large coverage area, large transmission capacity, strong survivability, etc. In order to relieve the service load and expand the service range, the ground network and the non-ground network are fused together to form an air-ground integrated network, and service continuity, service universality and service scalability are realized through complementary advantages of the ground network and the non-ground network. Therefore, the air-space-ground integrated network provides integrated information service in the global scope for application in the fields of aerospace, aviation, navigation, emergency and the like. With the wide application of the space-to-ground integrated network in various fields, spatial data presents an unprecedented 'blowout' growth potential.

The amount of climate change data in non-terrestrial networks alone will increase to 350 beats of bytes by 2030 as predicted by the national aerospace agency (NASA). At the same time, the amount of data in the surface network grows exponentially. Ericsson mobile reporting predicts that by the end of 2024 the number of smartphones in the ground network will reach 72 gigabytes, with an average consumption of over 21 gigabytes per month. In this case, a large amount of non-critical data will be transmitted over the non-terrestrial network, thereby greatly reducing congestion of the terrestrial network. Thus, there is an urgent need to offload huge spatial data from non-terrestrial networks to the ground. In fact, network resources of non-terrestrial networks are expensive and scarce. Therefore, it is imperative to study how to efficiently allocate space-world integrated network resources to offload as much of the space data as possible from a non-terrestrial network to a terrestrial network.

However, data offloading of an aerospace-ground integrated network faces the following challenges:

1) The low orbit satellite node in the space-earth integrated network has high moving speed, so that the network topology has high dynamic property, and the data unloading process has the characteristic of intermittent on-off, which brings great challenges to the design of a data unloading strategy;

2) Uncertainty of spatial data arrival. Spatial data arrival is uncertain and unpredictable due to uneven traffic distribution, uneven user behavior, diverse data types, and the like. Thus, the difficulty is how to design an efficient data offloading strategy to accommodate the uncertainty of data arrival.

3) The energy is limited. Network nodes in non-terrestrial networks (such as satellites, space platforms and drones) are battery powered and therefore energy limited. Furthermore, excessive energy consumption may significantly reduce the lifetime of the network node. Therefore, the energy consumption is one of main bottlenecks for restricting the improvement of the data unloading efficiency of the space-time integrated network.

In order to address the above challenges, it is desirable to design an efficient data offloading and power control online joint optimization method to accommodate real-time offloading of data and energy online control. In the data offloading study of the prior air-ground integrated network, most of the study work assumes that the task information is known or pre-known in advance, and aims to design a static data offloading and power control strategy. The method ignores the uncertainty of space data arrival, and cannot solve the problem of online efficient matching of network resources and space data in a high-dynamic space environment, so that the space resource utilization efficiency is reduced, and the space-to-ground integrated network data unloading capacity is difficult to improve.

Disclosure of Invention

The invention aims to solve the technical problems of providing an on-line data unloading method and system for an air-space integrated network, which are used for solving the technical problem of low on-line unloading efficiency of massive space data and can be used for network resource management and scheduling of the air-space integrated network.

The invention adopts the following technical scheme:

an on-line data unloading method for an aerospace-earth integrated network comprises the following steps:

s1, calculating the topological relation of an air-space-earth integrated network according to the ephemeris of a low-orbit user satellite and a relay satellite and the longitude and latitude information of a ground station, recording the moment point of each topological relation change, constructing a large-scale time slot set, uniformly dividing each large-scale time slot into a plurality of small-scale time slots with the same size to construct a small-scale time slot set, and further constructing a double-scale resource time-varying diagram;

s2, respectively constructing a data unloading queue and an energy consumption queue for each vertex of the low-orbit user satellite data transmitting antenna in the double-scale resource time-varying diagram obtained in the step S1, and initializing all queue lengths;

s3, when the time slot t is equal to 1, constructing a weighted bipartite graph based on the initialized queue length of the data unloading queue and the energy consumption queue obtained in the step S2, and when the time slot t is not equal to 1, constructing a weighted bipartite graph based on the queue length of the data unloading queue and the energy consumption queue obtained in the step S5;

S4, solving the maximum matching of the weighted bipartite graph obtained in the step S3 by using a classical algorithm Kuhn-Munkres in graph theory, and distributing a data receiving antenna and transmitting power of a relay satellite or a ground station for each low-orbit user satellite to generate a data unloading scheme and a power distribution scheme;

s5, respectively updating a data unloading queue and an energy consumption queue based on the data unloading scheme and the power allocation scheme obtained in the step S4, and updating a time slot index t=t+1 and returning to the step S3 if the termination condition is not met; otherwise, the process is terminated.

Specifically, the construction of the double-scale resource time-varying graph specifically comprises the following steps:

s101, calculating the topological relation between the low-orbit user satellite and the relay satellite as well as the ground station according to the ephemeris of the low-orbit user satellite and the relay satellite and the longitude and latitude information of the ground station, recording the changed I K time points, dividing a time axis into I K time periods, recording each time period as a large-scale time slot, and using (T) _k ，T _k+1 ) Representing the kth large-scale time slot, obtaining an index set K= {0,1, …, |K| -1};

s102, constructing a subgraph G in each large-scale time slot K epsilon K _k (V(G _k )，E(G _k ) The vertex set of the subgraph is V (G) _k ) U.U.U.S.U.U.U is the data transmitting antenna set of the low orbit user satellite, S is the data receiving antenna set of the ground station, R is the data receiving antenna set of the relay satellite, E (G) _k ) Representing subgraph G _k Each side represents a communication window between a data transmitting antenna and a data receiving antenna;

s103, sequentially finding sub-graphs G of adjacent large-scale time slots K and large-scale time slots k+1 respectively corresponding to the large-scale time slots k=0 from the beginning of the large-scale time slots k=0 to the end of k= |K| -1 _k (V(G _k )，E(G _k ) Sum subgraph G) _k+1 (V(G _k+1 )，E(G _k+1 ) Adding a storage edge between the same vertexes in the two subgraphs, and constructing a storage edge set SE;

s104, uniformly dividing each large-scale time slot K into a plurality of small-scale time slots with equal size from the large-scale time slot k=0 to the k= |K| -1 to construct a small-scale time slot set ζ _k With two groups(s) _t ，e _t ) Representing each small scale time slot t e ζ _k ，s _t E is the starting time of the small-scale time slot t _t The sigma is the time slot length of the small-scale time slot t at the end time of the small-scale time slot t;

s105, constructing vertex set v=v (G) in the two-scale resource time-varying graph G (V, E) ₀ )∪V(G ₁ )∪…V(G _|K|-1 ) Sum edge set e=e (G ₀ )∪E(G ₁ )∪…E(G _|K|-1 )∪SE。

Specifically, the data offloading queues of the low-orbit user satellite u in the small-scale time slot t+1 need to be updated in the small-scale time slot t are as follows:

Q _u (t+1)＝max{Q _u (t)-b _u (t)，0}+a _u (t)

wherein a is _u (t) and b _u (t) and the newly generated and offloaded data amount respectively for low-orbit user satellite u in small-scale time slot t, Q _u (t+1) and Q _u (t) are respectively low railsUser satellite u is in the data offloading queues in small scale slots t+1 and t.

Specifically, the energy consumption queue of the low-orbit user satellite u in the small-scale time slot t+1 needs to be updated in the small-scale time slot t as follows:

wherein,maximum energy allowed to be consumed per time slot for low-orbit user satellite u, E _u (t) is the energy consumed by the low-orbit user satellite u in the small-scale time slot t, z _u (t+1) and z _u (t) is the energy consumption queue of low-orbit user satellite u in small-scale time slots t+1 and t, respectively.

Specifically, the construction of the weighted bipartite graph specifically includes:

finding out a large-scale time slot T where a small-scale time slot T is located in a double-scale resource time-varying graph G (V, E) _k Constructing weighted bipartite graph G _bi Vertex set V (G) _bi )＝V(G _k ) Edge set E (G) _bi )＝{l _u ，u∈U}，l _u Is subgraph G _k Edge set E (G) _k ) A set of edges comprising low-orbit user satellite u;

solving for edge set E (G) in small scale time slot t _bi ) Distributed optimal powerFor allocation to links (u, v) E (G) in small scale time slots t _bi ) Upper optimum power,/->The allocated power range of (2) isAnd->The maximum transmitting power and the minimum transmitting power of the low orbit user satellite u are respectively;

constructing a set of weight values Is the weight value of the link (u, v).

Further, for any link (u, v) εE (G _bi ) Optimal power allocated in small-scale time slot t according to whether vertex v type is data receiving antenna of relay satellite or data receiving antenna of ground station

Case 1: if v epsilon R is the data receiving antenna with the vertex being the relay satellite, calculating the inter-satellite link power thresholdAnd judge->And power range->The size relation between the two;

case 2: if v epsilon S is the data receiving antenna with the vertex being the ground station, calculating the satellite-ground link power thresholdAnd judge->And power range->And the size relation between the two.

Further, case 1 is specifically as follows:

if it isIn the power range +.>The inner random assignment of a value to +.>If it isThen->Definition of the function w _u，b (P _u，v (t)) is w _u，b (P _u，v (t))＝(V+|Q _u (t)|)C _u，v (t)d _u，v (t)-|z _u (t)|P _u，v (t)d _u，v (t), V is a positive integer, Q _u (t) | is queue Q _u Length of (t), C _u，v (t) is the data offloading rate of the communication link (u, v) in the small-scale time slot t, d _u，v (t) represents the length of time that low-orbit user satellite u offloads data over communication link (u, v) in small-scale time slot t, |Z _u (t) | is queue Z _u Length of (t), P _u，v (t) is the power allocated to the link (u, v) in the small-scale time slot t,the value of (2) is within the power range->Inner random distribution->The numerical assignment of (2) is as follows:

wherein, The link (u, v) between the low-orbit user satellite and the relay satellite corresponds to the channel gain in the small-scale time slot t;

if it isThen->The numerical assignment of (2) is as follows:

further, case 2 is specifically as follows:

if it isThen->The numerical assignment of (2) is as follows:

wherein phi (alpha) _u，v (t)) means the expression for the variable alpha _u，v Function of (t), f ₁ (P _u，v (t)) means the power P _u，v A function of (t) the function of,for the link between the low-orbit user satellite and the ground station (u,v) corresponds to the channel gain in the small-scale time slot t,/or->Is a function phi (alpha) _u，v (t)) zero point;

if it isThen->Wherein the method comprises the steps ofAnd->The numerical assignment of (2) is as follows:

wherein,threshold power allocated for the link (u, v);

if it isThen->The numerical assignment of (2) is as follows:

further, links (u, v)Weight valueThe calculation is as follows:

wherein, |Q _u (t) | is queue Q _u Length of (t), C _u，v (t) is the data offloading rate of the communication link (u, v) in the small-scale time slot t, d _u，v (t) represents the length of time, |z, that the low-orbit user satellite u has been offloading data over the communication link (u, v) during the small-scale time slot t _u (t) | is queue z _u Length of (t).

In a second aspect, an embodiment of the present invention provides an online data offloading system for an air-space integrated network, including:

The construction module calculates the topological relation of the space-earth integrated network according to the ephemeris of the low-orbit user satellite and the relay satellite and the longitude and latitude information of the ground station, records the moment point of each topological relation change, constructs a large-scale time slot set, uniformly divides each large-scale time slot into a plurality of small-scale time slots with the same size to construct a small-scale time slot set, and further constructs a double-scale resource time-varying diagram;

the queue module is used for respectively constructing a data unloading queue and an energy consumption queue for each vertex of the low-orbit user satellite data transmitting antenna in the double-scale resource time-varying graph obtained by the construction module, and initializing all queue lengths;

the construction module is used for constructing a weighted bipartite graph based on the initialized queue length of the data unloading queue and the energy consumption queue obtained by the queue module when the time slot t is equal to 1, and constructing a weighted bipartite graph based on the queue length of the data unloading queue and the energy consumption queue obtained by the unloading module when the time slot t is not equal to 1;

the unloading module is used for utilizing the maximum matching of the weighted bipartite graph obtained by the classical algorithm Kuhn-Munkres solving construction module in the graph theory to allocate a data receiving antenna and transmitting power of a relay satellite or a ground station for each low-orbit user satellite, and a data unloading scheme and a power allocation scheme are generated;

The updating module is used for respectively updating the data unloading queue and the energy consumption queue based on the data unloading scheme and the power distribution scheme which are obtained by the unloading module, and updating the time slot index t=t+1 and returning to the construction module if the termination condition is not reached; otherwise, the process is terminated.

Compared with the prior art, the invention has at least the following beneficial effects:

an on-line data unloading method for an air-space integrated network is characterized by constructing a double-scale resource time-varying graph to describe the high dynamic property of network topology of the air-space integrated network on a large time scale, rapidly changing network resources and space data information on a small time scale, constructing a data unloading queue and an energy consumption queue on each vertex in the graph to ensure the on-line unloading of space data, then constructing a weighted bipartite graph to efficiently convert the problem of joint optimization of power control and data unloading into a weighted bipartite graph matching problem, and fully ensuring the on-line data unloading efficiency suitable for the air-space integrated network.

Furthermore, by constructing the double-scale resource time-varying graph, the characteristics of the high-dynamic space-earth integrated network can be adapted to the rapid change of the network topology from the large-scale time slot, and the network resource can be updated in real time and the randomness achieved for the space data can be captured in real time from the small-scale time slot, so that the execution efficiency of an online data unloading mechanism is ensured.

Furthermore, the real-time requirement of space data unloading can be ensured by constructing a data unloading queue on each low-orbit user satellite and updating according to the small-scale time slot.

Furthermore, the real-time updating and statistics of the network resource state information can be ensured by constructing an energy consumption queue for each low-orbit user satellite and updating according to the small-scale time slot.

Furthermore, by means of the problem of transmitting power distribution of the low-orbit user satellite and the problem of optimal matching with a data receiving antenna of a ground station or a relay satellite, the problem of matching of classical weighted bipartite graphs in graph theory is efficiently and uniformly converted through weighted bipartite graph construction, so that the problem solving complexity can be greatly reduced, and the online data unloading efficiency of the space-earth integrated network is greatly improved.

Furthermore, by analyzing different characteristics of the inter-satellite link and the inter-satellite link of the space-earth integrated network, optimal power distribution is obtained according to the link type, and the capacity of on-line unloading of network data is greatly improved.

It will be appreciated that the advantages of the second aspect may be found in the relevant description of the first aspect, and will not be described in detail herein.

In summary, the method for constructing the double-scale resource time-varying map efficiently characterizes the network resource high dynamic property and the space data uncertainty of the space-to-ground integrated network from different time scales, and based on the method, a weighted bipartite map is constructed by analyzing the network link characteristics, so that the power control and data unloading joint optimization problem is converted into a weighted bipartite map matching problem, the efficiency of on-line data unloading is greatly improved, and the data unloading capacity of the space-to-ground integrated network is ensured.

The technical scheme of the invention is further described in detail through the drawings and the embodiments.

Drawings

FIG. 1 is a general flow chart of an implementation of the present invention;

FIG. 2 is a time-varying graph of a dual-scale resource in the present invention, wherein (a) is an air-space integrated network and (b) is a time-varying graph of a dual-scale resource;

FIG. 3 is a weighted bipartite graph of the present invention;

FIG. 4 is a graph of simulated comparison of total data throughput versus maximum power level obtained using the present invention and prior art comparison schemes;

FIG. 5 is a graph of simulated versus maximum data size achieved in each small scale time slot for the total data throughput obtained with the present invention and prior art comparison schemes;

FIG. 6 is a schematic diagram of a computer device according to an embodiment of the present invention;

Fig. 7 is a block diagram of a chip according to an embodiment of the present invention.

Detailed Description

The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

In the description of the present invention, it will be understood that the terms "comprises" and "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

It is also to be understood that the terminology used in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of 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 as well, unless the context clearly indicates otherwise.

It should be further understood that the term "and/or" as used in the present specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations, e.g., a and/or B, may represent: a exists alone, A and B exist together, and B exists alone. In the present invention, the character "/" generally indicates that the front and rear related objects are an or relationship.

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

Depending on the context, the word "if" as used herein may be interpreted as "at … …" or "at … …" or "in response to a determination" or "in response to detection". Similarly, the phrase "if determined" or "if detected (stated condition or event)" may be interpreted as "when determined" or "in response to determination" or "when detected (stated condition or event)" or "in response to detection (stated condition or event), depending on the context.

Various structural schematic diagrams according to the disclosed embodiments of the present invention are shown in the accompanying drawings. The figures are not drawn to scale, wherein certain details are exaggerated for clarity of presentation and may have been omitted. The shapes of the various regions, layers and their relative sizes, positional relationships shown in the drawings are merely exemplary, may in practice deviate due to manufacturing tolerances or technical limitations, and one skilled in the art may additionally design regions/layers having different shapes, sizes, relative positions as actually required.

The invention provides an on-line data unloading method for an air-space-earth integrated network, which is characterized in that a double-scale resource time-varying graph is constructed, rapid changes of network topology are depicted from a large-scale time slot, and task information and network resources are updated from a small-scale time slot in real time, so that the dynamics of the air-space-earth integrated network are accurately depicted from different time scales, and a guarantee is provided for efficient data unloading; and then, in each small-scale time slot, the improvement of the utilization rate of network resources is realized by jointly optimizing power distribution and data unloading. Specifically, an optimal power distribution method is designed by utilizing the characteristics of a communication link of the space-earth integrated network, a weighted two-part graph is constructed on the basis of the optimal power distribution method to be matched with an optimal ground station or a relay satellite for each satellite, and then the complex spatial data unloading and power control combined optimization problem is converted into a classical two-part graph matching problem in graph theory, so that the solving complexity of the data unloading problem is greatly reduced, and the data unloading efficiency of the space-earth integrated network is effectively improved.

The implementation of the present invention will be described below with reference to the relay satellite and ground station in an integrated space-time network providing data offloading services for low-orbit user satellites.

The space-earth integrated network consists of N data relay satellites positioned in a geosynchronous orbit, M ground stations and I low-orbit user satellites. Wherein, each relay satellite has H data receiving antennas to provide data unloading service for low-orbit user satellites, each ground station is provided with a data receiving antenna, and each low-orbit user satellite is provided with a data transmitting antenna.

In each time slot, the improvement of the utilization rate of network resources is realized by jointly optimizing power distribution and data unloading; by utilizing the characteristics of communication links of the space-earth integrated network, an optimal power distribution method is designed, and a weighted bipartite graph is constructed on the basis of the optimal power distribution method to match an optimal ground station or relay satellite for each satellite, so that the problem of complex spatial data unloading and power control combined optimization is uniformly converted into a classical bipartite graph matching problem in graph theory.

Referring to fig. 1, the on-line data unloading method for the space-to-earth integrated network of the invention comprises the following steps:

S1, constructing a double-scale resource time-varying graph;

the method comprises the steps of importing ephemeris of a low-orbit user satellite and a relay satellite and longitude and latitude information of a ground station into satellite tool kit (Satellite Tool Kit, STK) software to calculate a topological relation of a network, recording a moment point of each topological relation change, constructing a large-scale time slot set, uniformly dividing each large-scale time slot into a plurality of small-scale time slots with equal size to construct a small-scale time slot set, and further constructing a double-scale resource time-varying graph G (V, E), wherein V and E respectively represent a vertex set and a side set in the graph G (V, E), the vertex in the double-scale resource time-varying graph represents a data transmitting antenna of the low-orbit user satellite and a data receiving antenna of the relay satellite and the ground station, and the side in the double-scale resource time-varying graph represents a topological connection relation among the vertices.

S101, according to the low railThe satellite and relay satellite ephemeris and ground station longitude and latitude information are used to calculate the topology relationship between low orbit user satellite and relay satellite and ground station by STK software, and record the changed K time points, so dividing the time axis into K time periods, each time period is marked as a large-scale time slot, and using (T) _k ，T _k+1 ) Representing the kth large-scale time slot, and further obtaining an index set K= {0,1, …, |K| -1};

referring to fig. 2, a time point when a network topology relationship of the air-space-ground integrated network changes is T ₀ ，T ₁ ，T ₂ ，T ₃ ，T ₄ And T ₅ The 5 large-scale time slots that can be constructed are therefore: (T) ₀ ，T ₁ )，(T ₁ ，T ₂ )，(T ₂ ，T ₃ )，(T ₃ ，T ₄ ) (T) ₄ ，T ₅ ) The corresponding large-scale slot index set k= {0,1, …,4}.

S102, constructing a subgraph G in each large-scale time slot K epsilon K _k (V(G _k )，E(G _k ) With vertex set V (G) _k ) =u.u.s.u.r, where U is the data transmitting antenna set of the low orbit user satellite, S is the data receiving antenna set of the ground station, R is the data receiving antenna set of the relay satellite, E (G) _k ) Representing subgraph G _k Each side represents that a communication window exists between the data transmitting antenna and the data receiving antenna (namely, topology has a connection relation);

referring to fig. 2, in a large-scale time slot k=0, a corresponding sub-graph G ₀ (V(G ₀ )，E(G ₀ ) Where the vertex set is V (G) ₀ )＝{u ₁ ，u ₂ }∪{v ₁ ，v ₂ }∪{v ₃ Edge set E (G) ₀ )＝{(u ₁ ，v ₁ )，(u ₁ ，v ₂ )}。

S103, sequentially finding sub-graphs G of adjacent large-scale time slots K and large-scale time slots k+1 respectively corresponding to the large-scale time slots k=0 from the beginning of the large-scale time slots k=0 to the end of k= |K| -1 _k (V(G _k )，E(G _k ) Sum of (d)Subgraph G _k+1 (V(G _k+1 )，E(G _k+1 ) Adding a storage edge between the same vertexes in the two subgraphs, and further constructing a storage edge set SE;

Referring to FIG. 2, for example, in subgraph G ₀ (V(G ₀ )，E(G ₀ ) Sum subgraph G) ₁ (V(G ₁ )，E(G ₁ ) A) the added storage edges are: { (u) ₁ ，u ₁ )，(u ₂ ，u ₂ )，(v ₁ ，v ₁ )，(v ₂ ，v ₂ )，(v ₃ ，v ₃ )}。

S104, uniformly dividing each large-scale time slot K into a plurality of small-scale time slots with equal size from the large-scale time slot k=0 to the k= |K| -1, and further constructing a small-scale time slot set ζ _k With two groups(s) _t ，e _t ) Representing each small scale time slot t e ζ _k WhereinFor the start time of the small-scale time slot t, +.>The sigma is the time slot length of the small-scale time slot t at the end time of the small-scale time slot t;

s105, constructing vertex set v=v (G) in time-varying graph G (V, E) ₀ )∪V(G ₁ )∪…V(G _|K|-1 ) Sum edge set e=e (G ₀ )∪E(G ₁ )∪…E(G _|K|-1 )∪SE。

S2, constructing a data unloading queue and an energy consumption queue and initializing the queues;

according to the dual-scale resource time-varying graph obtained in the step S1, each vertex of a data transmitting antenna representing a low-orbit user satellite in the graph is respectively a data unloading queue and an energy consumption queue. Respectively using Q (t) = { Q _u (t), u.epsilon.U } and z (t) = { z _u (t), U e U } represents all data offloading queues and energy consumption queues, where U is the low-orbit user satellite index set, t is the small-scale slot index, Q _u (t) and z _u (t) is respectively corresponding toData offloading and energy consuming queues of user satellite u at small scale time slot t and initializing queue Q (1) = { Q within small scale time slot t=1 _u (1) U e U and z (1) = { z _u (1) U e U, which is a positive number given to each of the data offloading queue and the energy consumption queue when the small-scale slot t=1, and calculates the queue length.

S3, constructing a weighted bipartite graph;

judging whether the time slot t is equal to 1, if so, constructing a weighted bipartite graph based on the initialized queue lengths of the data unloading queue and the energy consumption queue obtained in the step S2, otherwise, constructing a weighted bipartite graph G based on the queue lengths of the data unloading queue and the energy consumption queue obtained in the step S5 in each small-scale time slot t _bi (V(G _bi )，E(G _bi )，W(G _bi ) And) wherein V (G _bi ) For vertex set of graph, E (G _bi ) For edge sets of the graph, W (G _bi ) Is a set of weight values for the graph.

S301, finding a large-scale time slot T where a small-scale time slot T is located in a double-scale resource time-varying graph G (V, E) _k Constructing weighted bipartite graph G _bi Vertex set of (a)Edge set E (G) _bi )＝{l _u u.epsilon.U }, where

S302, solving the edge set E (G _bi ) Distributed optimal powerAccording toIt can be known from the definition of (a) that it is allocated to the link (u, v) E (G) _bi ) Upper optimum power,/->Is +.>And->The specific allocation strategy is as follows:

E (G) for any link (u, v) _bi ) The distribution link (u, v) E (G) is carried out in the small-scale time slot t according to the two situations that the vertex v type is the data receiving antenna of the relay satellite or the data receiving antenna of the ground station _bi ) Optimum power on

Case 1: if v epsilon R is the data receiving antenna with the vertex being the relay satellite, calculating the inter-satellite link power thresholdWherein |Q _u (t) | is queue Q _u Length of (t), ->The link (u, v) between the low-orbit user satellite and the relay satellite corresponds to the channel gain in the small-scale time slot t; and judge->And power range->The size relation is as follows:

if it isThen in the power range->The interior is randomly assigned a value>

If it isThen->Wherein the function w _u，v (P _u，v (t)) is defined as w _u，v (P _u，v (t))＝(V+|Q _u (t)|)C _u，v (t)d _u，v (t)-|Z _u (t)|P _u，v (t)d _u，v (t)，P _u，v (t) is the power allocated to the link (u, V) in the small-scale time slot t, V is the control parameter which can be set as a positive integer, C _u,v (t) is the data offloading rate of the communication link (u, v) in the small-scale time slot t, and can be calculated specifically by the following formula:

wherein,for the link (u, v) between the low-orbit user satellite and the ground station to correspond to the channel gain in the small-scale time slot t, B _c For the bandwidth of the communication link d _u，v (t) represents the length of time that the low-orbit user satellite u has been off-loaded on the communication link (u, v) during the small-scale time slot t, which can be calculated by the following formula:

Wherein z _u (t) | is queue z _u The length of (t) is set,the value of (2) is within the power range->Inner random distribution->The numerical assignment of (2) is as follows:

if it isThen->The numerical assignment of (2) is as follows:

case 2: if v epsilon S is the data receiving antenna with the vertex being the ground station, calculating the satellite-ground link power thresholdAnd judge->And power range->The size relation is as follows:

if it isThen->The numerical assignment of (2) is as follows:

wherein,equation +.>Solving to obtain; if->Then->Wherein->And->The numerical assignment of (2) is as follows:

if it isThen->The numerical assignment of (2) is as follows:

wherein,

s303, forming a weight value setThe weight value of the edge (u, v) is calculated as follows:

s4, generating a data unloading scheme.

And in each small-scale time slot t, solving the maximum matching of the weighted two-part graph by utilizing a classical algorithm Kuhn-Munkres in graph theory, distributing a data receiving antenna of a relay satellite or a ground station and distributing transmitting power for each low-orbit user satellite, and generating a data unloading scheme and a power distribution scheme, so that the data receiving antenna of the relay satellite or the data receiving antenna of the ground station directs to a designated low-orbit user satellite for data unloading at the time slot, and each low-orbit user satellite transmits data according to the distributed transmitting power.

Specifically, x is _u，v (t) ∈ {0,1} represents a data offload decision variable: x is x _u，v (t) =1 means that the low-orbit user satellite u selects the communication link (u, v) for data offloading in the small-scale time slot t, otherwise x _u，v (t) =0. Within each small-scale time slot t, a weighted bipartite graph G is obtained by utilizing a classical algorithm Kuhn-Munkres in graph theory _bi (V(G _bi )，E(G _bi )，W(G _bi ) Solving for the maximum weight perfectionMatching M (t), for any edge (u, v) ε M (t), then give decision variable x _u，v (t) assigning a value of 1 and obtaining the optimal power assigned on edge (u, v)Otherwise, a value of 0 is allocated, so that a data offloading scheme and a power allocation scheme in each small-scale slot t can be obtained.

S5, updating the data queue and the energy consumption queue.

S501 task pretreatment: and in each small-scale time slot t, the data unloading control center receives the data unloading request of each low-orbit user satellite in real time and preprocesses the task.

S50101, receiving a task request and acquiring basic information of a data unloading task:

task _j ＝(type _j ，a _j ，d _j ，D _j ，id _j )

where j represents a task number, type _j Indicating the task type, a _j Indicating the arrival time of a task, d _j Represents the deadline of the task, D _j Data quantity, id, representing task _j Satellite space numbering for the requested mission;

s50102, preprocessing the task, specifically analyzing the basic information of the data unloading task, judging whether the task meets the unloading condition, extracting the task information if the task meets the unloading condition, and rejecting the task request if the task meets the unloading condition.

S501021 determining the deadline d of any task j _j Whether or not it is greater than the start time s of the small-scale time slot t _t : if yes, accept the task request, go to step S501022; otherwise, rejecting the task request;

s501022 judging arrival time a of any task j _j Whether or not the condition s is satisfied _t-1 ＜a _j ≤s _t : if so, extracting the satellite number id of the task _j And data volume D _j Step S501023; otherwise, rejecting the task;

s501023 according to satellite spaceflightNumber id _j Acquiring satellite index u and updating newly generated data quantity a of user satellite u in small-scale time slot t _u (t)＝a _u (t)+D _j 。

S502, calculating the data quantity and the consumed energy of each low-orbit user satellite unloaded in the small-scale time slot t according to the data unloading scheme obtained in the step S4.

S50201, calculating the data quantity b unloaded by the low-orbit user satellite u in the small-scale time slot t _u (t) the following:

s50202, calculating the energy E consumed by the low-orbit user satellite u in the small-scale time slot t _u (t) the following:

s503, updating the queue Q of each low-orbit user satellite u in the next small-scale time slot t+1 _u (t+1) and z _u (t+1)。

S50301, in a small-scale time slot t, a queue update rule of a data unloading queue of any low-orbit user satellite u in the small-scale time slot t+1 is as follows:

Q _u (t+1)＝max{Q _u (t)-b _u (t)，)}+a _u (t)

S50302, in the small-scale time slot t, a queue update rule of the energy consumption queue of any low-orbit user satellite u in the small-scale time slot t+1 is as follows:

wherein,maximum energy allowed to be consumed per small scale time slot for low orbit user satellite u。

S504, judging termination conditions: if the current small-scale time slot T is larger than the maximum time slot number T, the method is terminated, otherwise, the method returns to the step S3 and updates the time slot index t=t+1.

In still another embodiment of the present invention, an air-space integrated network oriented online data unloading system is provided, where the system can be used to implement the above air-space integrated network oriented online data unloading method, and in particular, the air-space integrated network oriented online data unloading system includes a building module, a queue module, a building module, an unloading module, and an updating module.

In yet another embodiment of the present invention, a terminal device is provided, the terminal device including a processor and a memory, the memory for storing a computer program, the computer program including program instructions, the processor for executing the program instructions stored by the computer storage medium. The processor may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processor, digital signal processor (Digital Signal Processor, DSP), application specific integrated circuit (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, etc., which are the computational core and control core of the terminal adapted to implement one or more instructions, in particular to load and execute one or more instructions to implement the corresponding method flow or corresponding functions; the processor of the embodiment of the invention can be used for the operation of an online data unloading method for an aerospace-earth integrated network, and comprises the following steps:

Calculating the topology relation of the space-earth integrated network according to the ephemeris of the low-orbit user satellite and the relay satellite and the longitude and latitude information of the ground station, recording the moment point of each topology relation change, constructing a large-scale time slot set, uniformly dividing each large-scale time slot into a plurality of small-scale time slots with the same size to construct a small-scale time slot set, and further constructing a double-scale resource time-varying diagram; respectively constructing a data unloading queue and an energy consumption queue for each vertex of a satellite data transmitting antenna of a low-orbit user represented in a double-scale resource time-varying diagram, and initializing all queue lengths; when the time slot t is equal to 1, constructing a weighted bipartite graph based on the initialized queue lengths of the data unloading queue and the energy consumption queue, and when the time slot t is not equal to 1, constructing a weighted bipartite graph based on the queue lengths of the data unloading queue and the energy consumption queue; utilizing the maximum matching of the weighted bipartite graph obtained by solving the classical algorithm Kuhn-Munkres in the graph theory, distributing a data receiving antenna and transmitting power of a relay satellite or a ground station for each low-orbit user satellite, and generating a data unloading scheme and a power distribution scheme; respectively updating a data unloading queue and an energy consumption queue based on the obtained data unloading scheme and power allocation scheme, and if the termination condition is not met, updating a time slot index t=t+1 and returning to construct a weighted bipartite graph; otherwise, the process is terminated.

Referring to fig. 6, the terminal device is a computer device, and the computer device 60 of this embodiment includes: a processor 61, a memory 62, and a computer program 63 stored in the memory 62 and executable on the processor 61, the computer program 63 when executed by the processor 61 implements the reservoir inversion wellbore fluid composition calculation method of the embodiment, and is not described in detail herein to avoid repetition. Alternatively, the computer program 63, when executed by the processor 61, implements the functions of each model/unit in the online data unloading system of the air-to-ground integrated network according to the embodiment, and is not described herein in detail for avoiding repetition.

The computer device 60 may be a desktop computer, a notebook computer, a palm top computer, a cloud server, or the like. Computer device 60 may include, but is not limited to, a processor 61, a memory 62. It will be appreciated by those skilled in the art that fig. 6 is merely an example of a computer device 60 and is not intended to be limiting of the computer device 60, and may include more or fewer components than shown, or may combine certain components, or different components, e.g., a computer device may also include an input-output device, a network access device, a bus, etc.

The processor 61 may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), field programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

The memory 62 may be an internal storage unit of the computer device 60, such as a hard disk or memory of the computer device 60. The memory 62 may also be an external storage device of the computer device 60, such as a plug-in hard disk provided on the computer device 60, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), or the like.

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

Referring to fig. 7, the terminal device is a chip, and the chip 600 of this embodiment includes a processor 622, which may be one or more in number, and a memory 632 for storing a computer program executable by the processor 622. The computer program stored in memory 632 may include one or more modules each corresponding to a set of instructions. Further, the processor 622 may be configured to execute the computer program to perform the above-described method of on-line data offloading for an air-to-ground integrated network.

In addition, chip 600 may further include a power supply component 626 and a communication component 650, where power supply component 626 may be configured to perform power management of chip 600, and communication component 650 may be configured to enable communication of chip 600, e.g., wired or wireless communication. In addition, the chip 600 may also include an input/output (I/O) interface 658. Chip 600 may operate based on an operating system stored in memory 632.

In a further embodiment of the present invention, the present invention also provides a storage medium, in particular, a computer readable storage medium (Memory), which is a Memory device in a terminal device, for storing programs and data. It will be appreciated that the computer readable storage medium herein may include both a built-in storage medium in the terminal device and an extended storage medium supported by the terminal device. The computer-readable storage medium provides a storage space storing an operating system of the terminal. Also stored in the memory space are one or more instructions, which may be one or more computer programs (including program code), adapted to be loaded and executed by the processor. The computer readable storage medium may be a high-speed RAM Memory or a Non-Volatile Memory (Non-Volatile Memory), such as at least one magnetic disk Memory.

One or more instructions stored in a computer-readable storage medium may be loaded and executed by a processor to implement the corresponding steps of the above-described embodiments with respect to an on-line data offloading method for an air-to-ground integrated network; one or more instructions in a computer-readable storage medium are loaded by a processor and perform the steps of:

For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. The components of the embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the invention, as presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

The technical effects of the present invention can be further illustrated by the following simulation.

Simulation conditions

Setting a Walker constellation consisting of 50 satellites for low-orbit user satellites, uniformly distributing the Walker constellation on 10 track surfaces, and setting simulation time length to be 7 days for 5 satellites on each track surface; one relay satellite is located above longitude and latitude (275 degrees, 0 degrees); 84 ground stations are distributed globally; a, a _u (t) is in the range of [0, a _max ]Random values within the range, a _max Is the maximum amount of data generated within each small-scale time slot. Setting the minimum transmitting power corresponding to any low orbit user satellite u asSet up in simulation 1By varying P _max To study the power impact on the performance of the invention; in simulation 2, the maximum transmit power corresponding to any low-orbit user satellite u is set to +.>

The data offloading scheme for performance comparison used for simulation was 5:

first is UBO scheme: counting total data amount reached within 7 days;

secondly, the DSNGA-II scheme is proposed in "An automated task scheduling model using non-dominated sorting genetic algorithm II for fog-closed systems";

thirdly, a power random allocation scheme;

fourth, the TPTS scheme proposed by 'Two-phase task scheduling in data relay satellite systems';

fifth is the RND scheme, i.e. randomly allocating power and communication links.

Simulation content and results

Simulation 1, performance comparison with this scheme using the above UBO scheme, results are shown in fig. 4. As the power increases, the total amount of data offloaded by the present invention gradually increases, eventually very close to the amount of data offloaded by the UBO scheme. In particular, the performance of the present scheme versus the UBO scheme is above 98%, which fully demonstrates the effectiveness of the present scheme.

Simulation 2, further performance comparisons were made using the five comparison schemes described above, the results of which are shown in fig. 5. With the increase of the maximum data quantity, the performance of the invention obviously exceeds the DSNGA-II, the power random distribution, the TPTS and the RND, and is close to more than 98% of the performance of the UBO scheme, which again shows that the scheme has higher data unloading efficiency in the space-air-ground integrated network.

In summary, the on-line data unloading method and system for the space-to-earth integrated network have the following advantages:

1) By constructing a double-scale resource time-varying graph, rapid change of network topology is depicted from a large-scale time slot, and task information and network resources are updated from a small-scale time slot in real time, so that dynamics of an air-space integrated network are accurately depicted from different time scales, and guarantee is provided for efficient data unloading.

2) In each small-scale time slot, an optimal power scheme for each communication link distribution is obtained under the condition of energy limitation, and the subsequent power distribution and data unloading combined optimization efficiency is greatly improved.

3) In each small-scale time slot, the data unloading and power control combined optimization strategy is uniformly modeled into a weighted bipartite graph, and then the problem is converted into the maximum matching problem of the weighted bipartite graph, so that the complexity of solving the problem is greatly simplified, and the data unloading efficiency of the space-sky-ground integrated network is greatly improved.

It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions. The functional units and modules in the embodiment may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit, where the integrated units may be implemented in a form of hardware or a form of a software functional unit. In addition, the specific names of the functional units and modules are only for distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working process of the units and modules in the above system may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.

In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.

Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.

In the embodiments provided in the present invention, it should be understood that the disclosed apparatus/terminal and method may be implemented in other manners. For example, the apparatus/terminal embodiments described above are merely illustrative, e.g., the division of the modules or units is merely a logical function division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection via interfaces, devices or units, which may be in electrical, mechanical or other forms.

The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.

The integrated modules/units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the present invention may implement all or part of the flow of the method of the above embodiment, or may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the computer program may implement the steps of each of the method embodiments described above. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a usb disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a Random-Access Memory (RAM), an electrical carrier wave signal, a telecommunications signal, a software distribution medium, etc., it should be noted that the content of the computer readable medium may be appropriately increased or decreased according to the requirements of legislation and patent practice in jurisdictions, such as in some jurisdictions, according to the legislation and patent practice, the computer readable medium does not include electrical carrier wave signals and telecommunications signals.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may 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, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

The above is only for illustrating the technical idea of the present invention, and the protection scope of the present invention is not limited by this, and any modification made on the basis of the technical scheme according to the technical idea of the present invention falls within the protection scope of the claims of the present invention.

Claims

1. An on-line data unloading method for an aerospace-earth integrated network is characterized by comprising the following steps of:

2. The method for unloading data on line for an air-space integrated network according to claim 1, wherein the constructing of the double-scale resource time-varying graph is specifically:

S101, calculating the topological relation between the low-orbit user satellite and the relay satellite as well as the ground station according to the ephemeris of the low-orbit user satellite and the relay satellite and the longitude and latitude information of the ground station, recording the changed I K time points, dividing a time axis into I K time periods, recording each time period as a large-scale time slot, and using (T) _k ，T _k+1 ) Representing the kth large-scale slot, obtaining an index set k= {0,1,.+ -. K| -1} for the large-scale slot;

s105, constructing doubleVertex set v=v (G) in scale resource time-varying graph G (V, E) ₀ )∪V(G ₁ )∪...V(G _|K|-1 ) Sum edge set e=e (G _b )∪E(G ₁ )∪...E(G _|K|-1 )∪SE。

3. The method for on-line data offloading for an air-space integrated network according to claim 1, wherein the data offloading queues of the low-orbit user satellite u in the small-scale time slot t+1 are required to be updated in the small-scale time slot t as follows:

Q _u (t+1)＝max{Q _u (t)-b _u (t)，0}+a _u (t)

wherein a is _u (t) and b _u (t) and the newly generated and offloaded data amount respectively for low-orbit user satellite u in small-scale time slot t, Q _u (t+1) and Q _u (t) is a data offloading queue for low-orbit user satellite u in small-scale time slots t+1 and t, respectively.

4. The method for unloading data on-line for an integrated space-time network according to claim 1, wherein the energy consumption queue of the low-orbit user satellite u in the small-scale time slot t+1 is required to be updated in the small-scale time slot t as follows:

5. The method for unloading data on line for an aerospace-earth integrated network according to claim 1, wherein the constructing of the weighted bipartite graph is specifically:

solving for edge set E (G) in small scale time slot t _bi ) Distributed optimal powerFor allocation to links (u, v) E (G) in small scale time slots t _bi ) Upper optimum power,/->Is +.> And->The maximum transmitting power and the minimum transmitting power of the low orbit user satellite u are respectively;

constructing a set of weight valuesIs the weight value of the link (u, v).

6. The method for on-line data offloading for an air-space integrated network of claim 5, wherein for any link (u, v) E (G _bi ) Two kinds of data receiving antennas of relay satellite or ground station according to vertex v type in small scale time slot tOptimal power for situation allocation

7. The method for on-line data offloading for an air-space integrated network according to claim 6, wherein case 1 specifically comprises:

if it isIn the power range +.>The inner random assignment of a value to +.>If it isThen->Definition of the function w _u,v (P _u,v (t)) is w _u，v (P _u,v (t))＝(V+|Q _u (t)|)C _u，v (t)d _u,v (t)-|Z _u (t)|P _u，v (t)d _u，v (t), V is a positive integer, Q _u (t) | is queue Q _u Length of (t), C _u，v (t) is the data offloading rate of the communication link (u, v) in the small-scale time slot t, d _u，v (t) represents the length of time, |z, that the low-orbit user satellite u has been offloading data over the communication link (u, v) during the small-scale time slot t _u (t) | is queue z _u Length of (t), P _u,v (t) is the power allocated to the link (u, v) in the small-scale time slot t,the value of (2) is within the power range->Inner random distribution->The numerical assignment of (2) is as follows:

wherein,for the link (u, v) between the low-orbit user satellite and the relay satelliteCorresponding to the channel gain in the small-scale time slot t;

If it isThen->The numerical assignment of (2) is as follows:

8. the method for on-line data offloading for an air-space integrated network according to claim 6, wherein case 2 specifically comprises:

if it isThen->The numerical assignment of (2) is as follows:

wherein phi (alpha) _u,v (t)) means the expression for the variable alpha _u，v Function of (t), f ₁ (P _u，v (t)) means the power P _u，v A function of (t) the function of,for the link (u, v) between the low-orbit user satellite and the ground station to correspond to the channel gain in the small-scale time slot t,is a function phi (alpha) _u,v (t)) zero point;

if it isThen->Wherein->Andthe numerical assignment of (2) is as follows:

wherein,threshold power allocated for the link (u, v);

if it isThen->The numerical assignment of (2) is as follows:

9. the space-oriented integrated network online data offloading of claim 5The method is characterized in that the weight value of the link (u, v)The calculation is as follows:

10. An on-line data offloading system for an aerospace-earth integrated network, comprising: