A task offloading method based on a medium-low earth orbit hybrid satellite network

Abstract

The application claims a task offloading method based on a medium-low orbit hybrid satellite network, and belongs to the field of communication technology. In view of the problem that high time variability of low-orbit inter-satellite links may cause low utilization of low-orbit satellite network resources, unbalanced business load, and further deteriorated task offloading performance, a task offloading method based on a medium-low orbit hybrid satellite network is provided. According to the location of the ground user, the best low-orbit access satellite and medium-orbit cooperative satellite are selected, and according to the type and data volume of each sub-task in the task request and the resource state of the low-orbit satellite, the corresponding low-orbit offloading satellite is selected, the task offloading decision is constructed and optimized, so as to maximize the resource utilization and task completion rate of the network, and effectively reduce the unit task offloading delay of the system.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of communication, and particularly relates to a task offloading method based on a middle-low orbit hybrid satellite network. BACKGROUND

[0002] With the rapid development of satellite networks, using satellites to directly provide edge computing services for ground terminals has become an important direction for future network development. Using low earth orbit (LEO) satellite networks to achieve wide ground coverage can provide good communication and edge computing services for areas with weak network facilities. However, due to the high-speed operation of LEO satellites, the inter-satellite link state of the LEO satellite network changes constantly, which may cause frequent interruption of routing during task offloading, and thus cause task failure and reduce task offloading performance.

[0003] To solve the above problems, the application provides a task offloading method based on a middle-low orbit hybrid double-layer satellite network. The method introduces middle earth orbit (MEO) satellites to assist task offloading in the LEO satellite network, and realizes task scheduling and resource allocation. First, the best low-orbit access satellite and the middle-orbit cooperative satellite are selected according to the location of the ground user and the current satellite network state. The middle-orbit cooperative satellite constructs a candidate low-orbit offloading satellite set according to the type and data volume of each sub-task in the task offloading request and the resource state distribution of the satellite network, and optimizes the task offloading decision through a differential evolution algorithm, thereby improving the utilization rate of satellite network resources, maximizing the task completion rate and reducing the unit task offloading delay. SUMMARY

[0004] The application aims to solve the problems of the prior art. A task offloading method based on a middle-low orbit hybrid satellite network is provided. The technical scheme of the application is as follows:

[0005] A task offloading method based on a middle-low orbit hybrid satellite network includes the following steps:

[0006] 101、Set the task offloading request J={j} of the user i on the ground, where j is a parallel sub-task, and initialize the candidate middle-orbit cooperative satellite set candidate low-orbit satellite set

[0007] 102、According to the location of the user i and the current satellite network state, obtain the best low-orbit access satellite s a If successful, jump to step 103, otherwise, jump to step 109;

[0008] 103、Add the middle-orbit satellite s a that has an inter-satellite link to the set S cand according to the inter-satellite link distance of the access satellite s a to the inter-satellite link distance of the candidate medium-orbit cooperative satellite set S c in ascending order.

[0009] 104, if the first medium-orbit satellite s in the set S c is taken out, let the medium-orbit cooperative satellite s c =s, all low-orbit satellites that have an inter-satellite link with s c are added to the candidate low-orbit satellite set S o , and according to the inter-satellite link distance of s c to the low-orbit satellite, the elements in the set S o are arranged in ascending order, jump to step 105, otherwise, jump to step 109.

[0010] 105, let the temporary set J'=J, if jump to step 106, otherwise, jump to step 104.

[0011] 106, if the first element j in the set J' is taken out, jump to step 107, otherwise, jump to step 108.

[0012] 107, according to the candidate low-orbit cooperative satellite set S o , the task amount m j and the task type v j of the subtask j, the candidate low-orbit offload satellite set S j is constructed for the subtask j, if successful, jump to step 106, otherwise, jump to step 104.

[0013] 108, according to the candidate low-orbit offload satellite set S j of each subtask j, the optimal task offload decision n * is constructed for the task offload request J based on the differential evolution algorithm, if successful, output the offload decision n * , jump to step 109, otherwise, jump to step 104.

[0014] 109, the step ends.

[0015] Further, the method for obtaining the best low-orbit access satellite s a in step 102 includes the following steps:

[0016] 1) initialize the candidate low-orbit access satellite set S

[0017] 2) add the low-orbit satellite that meets the access condition of the user i to the set S a , if go to step

[0018] 3), otherwise, go to step 6);

[0019] 3) according to the set S a , the remaining computing resources of each satellite s , the elements in S a are arranged in descending order, the distance d a between the user i and the low-orbit satellite s in the set S i,s is calculated i,s , and the same satellites are arranged in ascending order according to the value of d ;

[0020] 4) Take the first low-orbit satellite s in the set S a , let the low-orbit access satellite s a =s, and output s a ;

[0021] 5) The step ends.

[0022] Further, in the step 2), the method of adding the low-orbit satellite satisfying the user i access condition to the set S a specifically includes:

[0023] The elevation angle γ i,s of the ground user i to the low-orbit satellite s is greater than or equal to the minimum elevation angle γ min of satellite-ground communication, and the remaining coverage time t i,s of the low-orbit satellite s to the ground user i is greater than or equal to the task tolerance delay of the ground user i The low-orbit satellite s is added to the set S a , wherein the calculation method of the elevation angle γ i,s of the ground user i to the low-orbit satellite s is shown in formula (1);

[0024]

[0025] In formula (1), Δφ=φ i -φ s , φ i and respectively represent the longitude and latitude of the ground user i, φ s and φ s respectively represent the longitude and latitude of the low-orbit satellite s, R represents the radius of the earth, and h represents the orbit height of the low-orbit satellite.

[0026] Further, in the step 3), the calculation method of the distance d i,s between the user i and the low-orbit satellite s in the set S a is shown in formula (2):

[0027]

[0028] In formula (2), R represents the radius of the earth, h represents the orbit height of the low-orbit satellite, θ i,s represents the geocentric angle of the ground user i to the low-orbit satellite s, θ i,s is calculated as shown in formula (3), wherein γ i,s represents the elevation angle of the ground user i to the low-orbit satellite s.

[0029] Further, the method for constructing the candidate low-orbit offloading satellite set S j for the subtask j in the step 107 includes the following steps:

[0030] 6) Let the candidate low-orbit satellite set S j of the subtask j be S o , and the temporary set S j ' be S j ;

[0031] 7) If , take out the first satellite in the set S j ', and calculate the computing resource z j required for the satellite s to process the subtask j according to the data volume m max of the subtask j and the task tolerance time delay t j,s , and jump to step 8), otherwise, jump to step 10);

[0032] 8) If the satellite s has no virtual network function VNF instance of type v j , let z j,s = z j,s + z0, wherein z0 is the basic computing resource required for VNF instantiation, and jump to step 9), otherwise, jump to step 9);

[0033] 9) If the remaining computing resource on the satellite s is less than z j,s , remove the satellite s from the set S j , and jump to step 7), otherwise, jump to step 7);

[0034] 10) The step ends.

[0035] Further, the calculation method of the computing resource z j,s required for the satellite s to process the subtask j in the step 7) is shown in formula (4):

[0036]

[0037] In formula (4), m j and o jrespectively represent the task data volume and the task complexity of the subtask j in the task offloading request J, t max represents the task tolerance delay of the task offloading request J, represents the uplink transmission delay of the subtask j in the task offloading request J, and is calculated as shown in formula (5), represents the uplink and downlink propagation delay of the subtask j in the task offloading request J, and is calculated as shown in formula (6);

[0038]

[0039] In formula (5), R i,s represents the transmission rate between the ground user i and the low-orbit satellite s, is a binary variable, representing whether the subtask j is forwarded via the medium-orbit cooperative satellite s, if the subtask j is forwarded via the medium-orbit cooperative satellite s, let Otherwise, let R e represents the inter-satellite transmission rate, in formula (6), c is the speed of light, and d e represents the inter-satellite distance.

[0040] Further, the method of constructing the optimal task offloading decision n * for the task offloading request J based on the differential evolution algorithm in the step 108 includes the following steps:

[0041] 11) Set the population as a set N = {n}, where the population individual n = {nj | j ∈J} is the offloading satellite of the subtask j in the set J, and the candidate low-orbit offloading satellite set S j Randomly initialize n j , calculate the objective function value t n of n * , let the optimal objective function value t n = min{t n∈N} The maximum number of iterations is C, and the iteration count variable c = 0;

[0042] 12) Let c = c + 1, if c ≤ C, let the temporary set N' = N, jump to step 13), otherwise, jump to step 16);

[0043] 13) If Take the first element n in the set N', calculate the objective function value t n , perform mutation and crossover operations on n to obtain the mutated and crossed individual n cross , calculate the objective function value Jump to step 14), otherwise, jump to step 12);

[0044] 14) If Let n = n cross , go to step 15), otherwise, go to step 13);

[0045] 15) If t n ≤ t * , let t * = t n , n * = n, go to step 13), otherwise, go to step 13);

[0046] 16) Output the optimal offloading decision n * , and the step ends.

[0047] Further, the calculation method of the objective function value t n of n in step 11) is shown in formula (7):

[0048]

[0049] In formula (7), t j represents the offloading completion delay of subtask j, which is calculated as shown in formula (8):

[0050]

[0051] In formula (8), t represents the calculation delay of subtask j, which is calculated as shown in formula (9):

[0052]

[0053] In formula (9), z represents the calculation resource allocated by low-orbit satellite s for subtask j, which is calculated as shown in formula (10):

[0054]

[0055] In formula (10), z represents the remaining available calculation resource of satellite s, and z j,s represents the required calculation resource of subtask j for completing the task at satellite s.

[0056] Further, the method of mutation and crossover operation on n in step 13) specifically includes:

[0057] (1) Mutation operation: mutation processing is performed on each n j in individuals n respectively through formula (11), to obtain , so as to obtain the mutated individual

[0058]

[0059] In formula (11), rand(0,1) represents a random number in the numerical interval [0,1), and a2∈[0,1] represents a mutation probability. represents a floor function, and e1, e2, e3 represent random integers in the numerical interval [1, S j ], and e1≠e2≠e3, a1∈[0,1] represents a mutation scaling factor.

[0060] (2) Cross operation: each of the individuals n in the individual n is cross-processed by formula (12) to obtain j , thereby obtaining the individuals after cross.

[0061]

[0062] In formula (12), rand(0,1) represents a random number in the numerical interval [0,1), and a2∈[0,1] represents a cross probability.

[0063] The advantages and beneficial effects of the present application are as follows:

[0064] The present application discloses a task offloading method based on a medium-low orbit hybrid satellite network. Existing research on satellite network task offloading mostly only considers implementing task offloading of ground users in a single-layer satellite network, such as a LEO low-orbit network, while the high time variability of the LEO inter-satellite link can cause great challenges to the continuity and stability of the task offloading route, thereby reducing the resource utilization rate of the satellite network and causing the problem of deteriorated task offloading performance. In view of this problem, the present application proposes a task offloading method based on a medium-low orbit hybrid double-layer satellite network, which provides cross-layer cooperation by introducing MEO medium-orbit satellites to assist the LEO network in making decisions on task scheduling and resource allocation. The method first selects the best low-orbit access satellite and medium-orbit cooperative satellite according to the location of the ground user, constructs a candidate low-orbit offloading satellite set according to the types and computing resource requirements of each sub-task in the offloading request by the medium-orbit cooperative satellite, and optimizes the task offloading decision by a differential evolution algorithm, thereby improving the resource utilization rate of the satellite network, maximizing the task completion rate, and reducing the system unit task offloading delay. BRIEF DESCRIPTION OF DRAWINGS

[0065] Figure 1 is a flow chart of the task offloading method based on a medium-low orbit hybrid satellite network provided by the present application. DETAILED DESCRIPTION

[0066] The technical solutions in the embodiments of the present application will be described clearly and in detail below with reference to the drawings in the embodiments of the present application. The described embodiments are only some of the embodiments of the present application.​

[0067] The technical scheme of the present application to solve the above technical problems is:

[0068] The concepts and models involved in the present application are as follows:

[0069] The present application assumes that the medium and low orbit satellite network is composed of a plurality of low orbit LEO satellites and a plurality of medium orbit MEO satellites, and the satellites can communicate through line-of-sight link. The ground user accesses the satellite network through the LEO satellite, and selects a medium orbit satellite as a task scheduling cooperation satellite by the LEO access satellite. The medium orbit cooperation satellite selects a low orbit offload satellite for each sub-task of the user according to the resource state distribution and link connection of the satellite network. Each sub-task can only have one offload satellite, and each satellite can execute multiple sub-tasks. Considering that the result data returned from each offload satellite is small, the task offload delay only calculates the downlink propagation delay of the result data return, and ignores the transmission delay.

[0070] The technical scheme of the present application is described as follows:

[0071] 1. The elevation angle γ of the ground user i to the low orbit satellite s i,s , calculated as formula (1):

[0072]

[0073] In formula (1), Δφ = φ i -φ s , φ i and respectively represent the longitude and latitude of the ground user i, φ s and respectively represent the longitude and latitude of the low orbit satellite s, R represents the earth radius, and h represents the low orbit satellite orbit height.

[0074] 2. The distance d a between the user i and the low orbit satellite s in the set S i,s , calculated as formula (2):

[0075]

[0076] In formula (2), R represents the earth radius, h represents the low orbit satellite orbit height, and θ i,s represents the central angle of the ground user i to the low orbit satellite s.

[0077] 3. The central angle θ i,s between the ground user i and the low orbit satellite s, calculated as formula (3):

[0078]

[0079] 4. The computing resource z required by the satellite s to process the subtask j j,s , the calculation is as shown in formula (4):

[0080]

[0081] In formula (4), m j and o j respectively represent the task data volume and the task complexity of the subtask j in the task offloading request J, t max represents the task tolerance delay of the task offloading request J, represents the uplink transmission delay of the subtask j in the task offloading request J, represents the uplink and downlink propagation delay of the subtask j in the task offloading request J;

[0082] 5. The uplink transmission delay of the subtask j offloaded to the satellite s The calculation method is shown in formula (5):

[0083]

[0084] In formula (5), R i,s represents the transmission rate between the ground user i and the low-orbit satellite s, is a binary variable, which represents whether the subtask j is forwarded via the medium-orbit cooperative satellite s, if the subtask j is forwarded via the medium-orbit cooperative satellite s, let otherwise, let R e represents the inter-satellite transmission rate;

[0085] 6. The uplink and downlink propagation delay of the subtask j offloaded to the satellite s The calculation method is shown in formula (6):

[0086]

[0087] In formula (6), c is the speed of light, d e represents the inter-satellite distance;

[0088] 7. The objective function value t n of the population individual n, the calculation method is shown in formula (7):

[0089]

[0090] 8. The offloading completion delay t j of the subtask j, the calculation is shown in formula (8):

[0091]

[0092] 9. The computing delay of the subtask j The calculation is shown as formula (9):

[0093]

[0094] 10. The low-orbit satellite s assigns the computing resource for the subtask j The calculation is shown as formula (10):

[0095]

[0096] In formula (10), represents the remaining available computing resource of the satellite s, z j,s represents the required computing resource of the subtask j for completing the task at the satellite s;

[0097] 11. The method for performing mutation and crossover operations on the population individuals n

[0098] (1) Mutation operation: each of the individuals n in the population is processed by formula (11) for mutation, to obtain j Thus, the mutated individual is obtained

[0099]

[0100] In formula (11), represents the floor function, ε1, ε2, and ε3 represent random integers in the numerical interval [1, S j ], and ε1≠ε2≠ε3, represents the mutation scaling factor;

[0101] (2) Crossover operation: each of the individuals n in the population is processed by formula (12) for crossover, to obtain j Thus, the crossed individual is obtained

[0102]

[0103] In formula (12), rand(0, 1) represents a random number in the numerical interval [0, 1), and α2∈[0, 1] represents the crossover probability;

[0104] 13. Sub-algorithm 1: Obtain the best low-orbit access satellite s a

[0105] Step 1: Initialize the candidate low-orbit access satellite set

[0106] Step 2: Add the low-orbit satellite satisfying the access condition of the user i to the set S a if ​​Skip to step 3; otherwise, skip to step 5.

[0107] Step 3: Based on set S a Remaining computing resources for each satellite s For S a Sort the elements in descending order and calculate the relationship between user i and set S. a The distance d between medium and low Earth orbit satellites s i,s According to d i,s value pairs The same satellites are arranged in ascending order;

[0108] Step 4: Retrieve set S a The first low-Earth orbit satellite s in the series, enabling low-Earth orbit access satellite s a =s, and output s a ;

[0109] Step 5: End of steps.

[0110] 14. Sub-algorithm 2: Construct a candidate set S of low-Earth orbit offloading satellites for subtask j. j

[0111] Step 1: Let the candidate low-Earth orbit satellite set S for subtask j be determined. j =S o Temporary set S j ′=S j ;

[0112] Step 2: If Take out set S j The first satellite in the series, based on the data volume m of sub-task j. j and task tolerance latency t max Calculate the computing resources z required by satellite s to process subtask j. j,s If yes, proceed to step 3; otherwise, proceed to step 5.

[0113] Step 3: If satellite s has no v j Type of Virtual Network Function (VNF) instance, let z j,s =z j,s +z0, where z0 is the basic computing resources required for VNF instantiation, then jump to step 4; otherwise, jump to step 4.

[0114] Step 4: If the remaining computing resources on satellite s Less than z j,s , remove satellite s from set S j Remove from step 1 and proceed to step 2; otherwise, proceed to step 2.

[0115] Step 5: End of steps.

[0116] 15. Sub-algorithm 3: constructing the optimal task offloading decision n for the task offloading request J based on the differential evolution algorithm *

[0117] Step 1: Set the population as a set N = {n}, where the population individual n = {nj | j ∈J} is an offloading decision vector, and n j is the offloading satellite of the subtask j in the set J, and the candidate low-orbit offloading satellite set S j is randomly initialized j , the objective function value t n of n is calculated * , the optimal objective function value t n = min {t n∈N | n} is set, and the optimal individual n The maximum number of iterations is C, and the iteration count variable c = 0.

[0118] Step 2: Set c = c + 1, if c ≤ C, set the temporary set N' = N, jump to step 3, otherwise, jump to step 6.

[0119] Step 3: If Take the first element n in the set N', calculate the objective function value t n , perform mutation and crossover operations on n to obtain the mutated and crossed individual n cross , calculate the objective function value Jump to step 4, otherwise, jump to step 2.

[0120] Step 4: If Set n = n cross , jump to step 5, otherwise, jump to step 3.

[0121] Step 5: If t n ≤ t * , set t * = t n , n * = n, jump to step 3, otherwise, jump to step 3.

[0122] Step 6: Output the optimal offloading decision n * , and the step ends.

[0123] A task offloading method based on a medium-low-orbit hybrid satellite network, the specific implementation method comprising the following steps:

[0124] Step 1: Set the task offloading request J = {j} of the user i on the ground, where j is a parallel subtask, initialize the candidate medium-orbit cooperative satellite set The candidate low-orbit satellite set

[0125] Step 2: According to the location of user i and the current star network state, call sub-algorithm 1 to obtain the best low-orbit access satellite s a If successful, jump to step 3, otherwise, jump to step 9;

[0126] Step 3: Add all low-orbit satellites that have inter-satellite links with low-orbit access satellite s a to the set S c , and according to the inter-satellite link distance between s a and the low-orbit satellites, sort the elements in set S c in ascending order;

[0127] Step 4: If take the first medium-orbit satellite s in set S c , let medium-orbit cooperative satellite s c =s, add all low-orbit satellites that have inter-satellite links with s c to the candidate low-orbit satellite set S o , and according to the inter-satellite link distance between s c and the low-orbit satellites, sort the elements in set S o in ascending order, jump to step 5, otherwise, jump to step 9;

[0128] Step 5: Let temporary set J' = J, if jump to step 6, otherwise, jump to step 4;

[0129] Step 6: If take the first element j in set J', jump to step 7, otherwise, jump to step 8;

[0130] Step 7: According to the candidate low-orbit satellite set S o , the task amount m j and task type v j of sub-task j, call sub-algorithm 2 to construct the candidate low-orbit offload satellite set S j for sub-task j, if successful, jump to step 6, otherwise, jump to step 4;

[0131] Step 8: According to the candidate low-orbit offload satellite set S j of each sub-task j, call sub-algorithm 3 to construct the optimal task offload decision n * for task offload request J based on the differential evolution algorithm, if successful, output offload decision n * , jump to step 9, otherwise, jump to step 4;

[0132] Step 9: End of step.

[0133] The systems, apparatuses, modules or units disclosed in the above examples can be implemented by computer chips or entities, or by products with certain functions.

[0134] It should also be noted that the terms "comprising", "containing", or any other variant thereof, are intended to cover a non-exclusive inclusion, such that processes, methods, articles, or apparatuses that comprise a list of elements are not limited to those elements, but can also include other elements not expressly listed or inherent to such processes, methods, articles, or apparatuses. Without further limitation, an element defined by the phrase "comprising a" does not exclude the existence of additional identical elements in the process, method, article, or apparatus that includes the element.

[0135] The above examples are to be understood as merely illustrative of the application and not a limitation thereof. After reading the description of the present application, those skilled in the art can make various changes or modifications to the application, and these equivalent changes and modifications also fall within the scope of the application defined by the claims.

Claims

1. A task offloading method based on a low-middle earth orbit hybrid satellite network, characterized in that, The steps include: 101、Set the user i's task offloading request J = {j} on the ground, where j is a parallel subtask, initialize the candidate medium-orbit cooperative satellite set candidate low-orbit satellite set 102. Acquire the best low-orbit access satellite s according to the position of user i and the current constellation state a If successful, jump to step 103, otherwise, jump to step 109; 103、The low orbit access satellite s a The medium orbit satellite with inter-satellite link joins the set S c According to the access satellite s a The elements in the candidate medium orbit cooperative satellite set S c are arranged in ascending order according to the distance of the inter-satellite link with the medium orbit satellite. 104、If Take out the first medium orbit satellite s in the set S c , let the medium orbit cooperative satellite s c = s, add all low orbit satellites that have inter-satellite links with s c to the candidate low orbit satellite set S o , and arrange the elements in the set S c in ascending order according to the inter-satellite link distance of s o with low orbit satellites, jump to step 105, otherwise, jump to step 109; 105. Let the temporary set J' = J, if Go to step 106, otherwise go to step 104; 106. If Take the first element j from the set J' and go to step 107, otherwise go to step 108; 107. From the set of candidate low earth orbit cooperative satellites S o , the amount of tasks m of subtask j j and the task type v j , build the set of candidate low earth orbit offload satellites S for subtask j j if successful, jump to step 106, otherwise, jump to step 104; 108、According to each subtask j, the candidate low-orbit offloading satellite set S j , based on the differential evolution algorithm, constructing the optimal task offloading decision n for the task offloading request J * , if successful, output the offloading decision n * , jump to step 109, otherwise, jump to step 104; 109、End of the step.

2. The task offloading method based on a medium-low earth orbit hybrid satellite network according to claim 1, characterized in that, The method of the step 102 of acquiring the best low orbit access satellite s a includes the following steps: 1) initialize a set of candidate low earth orbit access satellite 2) Add to the set S the low earth orbit satellites that satisfy the user i access condition a If Go to step 3), otherwise go to step 6); 3) According to set S a Remaining computing resources for each satellite s For S a Sort the elements in descending order and calculate the relationship between user i and set S. a The distance d between medium and low Earth orbit satellites s i,s According to d i,s value pairs The same satellites are arranged in ascending order; 4) take the first low orbit satellite s in the set S a , let the low orbit access satellite s a = s, and output s a ; 5) End of the step.

3. The task offloading method based on a medium-low earth orbit hybrid satellite network according to claim 2, characterized in that, In step 2), the low earth orbit satellite satisfying the user i access condition is added to the set S a The method specifically comprises: The elevation angle γ of the ground user i to the low-orbit satellite s i,s greater than or equal to the minimum elevation angle γ of the satellite-ground communication min , and the residual coverage time t of the low-orbit satellite s to the ground user i i,s greater than or equal to the task tolerance delay of the ground user i The low-orbit satellite s that meets the condition is added to the set S a Wherein, the elevation angle γ of the ground user i to the low-orbit satellite s i,s The calculation method is shown in formula (1); In Equation (1), Δφ = φ i - φ s , φ i and respectively represent the longitude and latitude of the ground user i, φ s and respectively represent the longitude and latitude of the low earth orbit satellite s, R represents the earth radius, and h represents the low earth orbit satellite orbit height.

4. The task offloading method based on a medium-low earth orbit hybrid satellite network according to claim 2, characterized in that, In the step 3), the user i and the set S a The distance d between the medium-low orbit satellite s i,s The calculation method of the distance d is shown as formula (2): In Equation (2), R represents the Earth radius, h represents the low orbit satellite orbit height, and θ i,s represents the geocentric angle of the ground user i to the low orbit satellite s. θ i,s is calculated as shown in Equation (3), where γ i,s represents the elevation angle of the ground user i to the low orbit satellite s.

5. The task offloading method based on a medium-low earth orbit hybrid satellite network according to claim 1, characterized in that, The step 107 of constructing a candidate set S of low earth orbit offload satellites for subtask j j The method comprises the following steps: 6) Let Sj be the candidate LEO satellite set for subtask j j = S o , temporary set S j ' = S j ; 7) if Take the first satellite in the set S j , according to the data volume m j and the task tolerance time delay t max , calculate the computing resources z j,s required for the satellite s to process the subtask j, jump to step 8), otherwise, jump to step 10); 8) if satellite s has no v j a virtual network function, VNF, instance of type z j,s = z j,s + z0, where z0 is the underlying computing resources required for the VNF instantiation, go to step 9), otherwise, go to step 9); 9) If the remaining computing resources on satellite s are less than z j,s , remove satellite s from the set S j , go to step 7), otherwise, go to step 7); 10) End of the step.

6. The task offloading method based on a medium-low earth orbit hybrid satellite network according to claim 5, characterized in that, the computing resources z required by the satellite s to process the subtask j in the step 7) j,s The computing method is shown as formula (4): In formula (4), m j and o j respectively represent the task data volume and the task complexity of the subtask j in the task offloading request J, t max represents the task tolerance delay of the task offloading request J, represents the uplink transmission delay of the subtask j in the task offloading request J, and is calculated as shown in formula (5), represents the uplink and downlink propagation delay of the subtask j in the task offloading request J, and is calculated as shown in formula (6); In formula (5), R i,s denotes the transmission rate between the ground user i and the low-orbit satellite s, is a binary variable, which indicates whether the subtask j is forwarded via the medium-orbit cooperative satellite s. If the subtask j is forwarded via the medium-orbit cooperative satellite s, let Otherwise, let R e denotes the inter-satellite transmission rate. In formula (6), c is the speed of light, d e denotes the inter-satellite distance.

7. The task offloading method based on a medium-low earth orbit hybrid satellite network according to claim 1, characterized in that, The step 108 of constructing the optimal task offloading decision n for the task offloading request J based on the differential evolution algorithm * The method comprises the following steps: 11) Let the population be a set N = {n}, where the population individuals n = {nj|j ∈J Let} be the unloading decision vector, and nj be the unloading satellite for subtask j in set J. Based on the candidate low-Earth orbit unloading satellite set S for each subtask j... j Randomly initialize n j Calculate the objective function value t of n. n Let the optimal objective function value t * =min{t n | n∈N }, optimal individual The maximum number of iterations is C, and the iteration count variable c = 0; 12) Let c = c + 1, if c ≤ C, let temporary set N' = N, jump to step 13), otherwise, jump to step 16); 13) if Take the first element n in the set N', calculate the objective function value t n , mutate and cross the n to get the mutated and crossed individual n cross , calculate the objective function value Jump to step 14), otherwise, jump to step 12); 14) if Let n = n cross , go to step 15), otherwise, go to step 13); 15) if t n ≤ t * , let t * = t n , n * = n, go to step 13), otherwise, go to step 13); 16) output optimal offload decision n * Step ends.

8. The task offloading method based on a medium-low earth orbit hybrid satellite network according to claim 7, characterized in that, The objective function value t of n in step 11) is calculated n The calculation method of t is shown in formula (7): In formula (7), t j denotes the offloading completion latency of subtask j, which is calculated as shown in formula (8): In formula (8), denotes the computation latency of subtask j, which is calculated as shown in formula (9): In formula (9), Let s represent the computing resources allocated by the low-orbit satellite to the subtask j, which is calculated as shown in formula (10): In equation (10), denotes the remaining available computing resources of satellite s, z j,s denotes the required computing resources of subtask j to complete the task at satellite s.

9. The task offloading method based on a medium-low earth orbit hybrid satellite network according to claim 7, characterized in that, The method of mutation and crossover operation on n in the step 13) specifically includes: (1) Mutation operation: Each of the individuals n in the population is mutated by formula (11) to obtain j Thus, the mutated individuals are obtained ​ In formula (11), denotes rounding down, and ε1, ε2, ε3 denote random integers within the numerical interval [1, S j ] and ε1≠ε2≠ε3, α1∈[0,1] denotes a mutation scaling factor; (2) Cross operation: each of the individuals n in the population is cross-processed by formula (12) to obtain j ​​ In formula (12), rand(0, 1) represents a random number in the numerical interval [0, 1), and α2 ∈ [0, 1] represents a crossover probability.

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