CN115086427B - Star-earth integrated collaboration sharing network oriented edge cache content placement method - Google Patents

Star-earth integrated collaboration sharing network oriented edge cache content placement method Download PDF

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CN115086427B
CN115086427B CN202210634973.5A CN202210634973A CN115086427B CN 115086427 B CN115086427 B CN 115086427B CN 202210634973 A CN202210634973 A CN 202210634973A CN 115086427 B CN115086427 B CN 115086427B
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顾术实
陈紫菡
左苗苗
余子超
张钦宇
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Shenzhen Graduate School Harbin Institute of Technology
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Abstract

The invention provides a method for placing edge cache content of a star-earth integrated collaboration sharing network, which comprises the following steps: step 1: firstly, setting the buffer matrix of the auxiliary satellite to 0, when the sum of SBS n and the number of the buffer coding packets of the main satellite is smaller thanKWhen the ground shared link is started, the content file placement matrix m of the SBSs is obtained by maximizing the total transmission flow i,n Obtaining a main satellite cache placement matrix by minimizing overall transmission energy consumption; step 2: after obtaining the buffer memory placement matrix of SBSs and main satellites, expanding the buffer memory placement matrix to a multi-satellite-ground integrated collaboration sharing network, and introducing sharing variablesɑ i Sharing variablesɑ i When the value is 0, only the ground shared link is started, at the moment, the buffer memory placement matrix in the auxiliary satellite is cleared, and the variables are sharedɑ i When the value is 1, only the inter-satellite shared link is started, and the buffer storage matrix in the SBSs is cleared. The beneficial effects of the invention are as follows: the invention realizes the energy efficiency maximization of the satellite-ground integrated collaboration sharing network.

Description

Star-earth integrated collaboration sharing network oriented edge cache content placement method
Technical Field
The invention relates to the technical field of satellites, in particular to an edge cache content placement method for a satellite-ground integrated collaboration sharing network.
Background
The explosive growth of mobile data traffic, the 6G landscape, further expands the scope and depth of network coverage, which is a challenge for conventional terrestrial cellular networks. The satellite-ground integrated network has wide coverage and seamless access capability, can obviously improve the performance of the ground cellular network, and is a necessary trend of future technical development.
Depending on the nature of the data traffic, i.e. the main part of the increased mobile traffic is repeated downloading of some popular content items from the remote server, the popular content items may be cached in the intermediate server using mobile edge caching and delivery techniques (Mobile Edge Caching, MEC), bringing the content closer to the user, creating less delivery delay, to significantly improve the quality of user experience and save transmission resource consumption of the backhaul and core network.
The terrestrial backhaul is a multi-hop unicast network, and therefore the cached content must be transmitted over multiple links and to each base station individually. And satellite systems can provide broadband backhaul links and operate in multi/broadcast mode, covering a wide area. Therefore, the caching and satellite communication technology are combined together, typical application scenes such as wide-area or global hot spot video pushing and popular content distribution are dealt with, the load pressure of a ground core network can be further relieved, and seamless linkage and broadband communication capacity of cross-domain real-time sharing information are improved.
However, the satellite-ground comprehensive network has limited cache and energy resources, the infrastructure is complex, the burden of a backhaul link is seriously increased, and the energy efficiency is reduced. Encoding caching is an emerging technique that improves caching efficiency, where each file can be divided into multiple segments and different segments of the file are strategically cached at edge nodes using encoding techniques during the caching process. Rateless coding has lower coding redundancy than traditional coding schemes, meaning that the coded data blocks can be generated continuously like a fountain, so that the data has no specific rate after being coded.
With the gradual implementation of Low Earth Orbit (LEO) satellite constellation such as Oneweb, starlink, a Low-Orbit satellite with Low delay and high bandwidth will be used as an access satellite of a future 6G space-Earth integrated network to communicate with a ground base station. More and more studies have considered low earth orbit satellite constellations when designing and implementing high performance radio access networks (Radio Access Network, RAN), however most studies have focused on transmission delays and transmission costs for multi-satellite terrestrial integrated networks, and transmitted complete files, which do not involve code caching techniques, or which only apply code caching techniques to single-satellite terrestrial integrated networks.
Disclosure of Invention
The invention provides a method for placing edge cache content of a star-earth integrated collaboration sharing network, which comprises the following steps:
step 1: firstly, setting a buffer matrix of an auxiliary satellite to 0, when the sum of the number of the SBS n and the number of the buffer coded packets of the main satellite is smaller than K, starting a ground shared link, and then obtaining a content file placement matrix m of the SBSs by maximizing the total transmission flow i,n Obtaining a main satellite buffer storage placement matrix by minimizing the total transmission energy consumption, and when the number of the coded packets buffered in the main satellite
Figure BDA0003681718310000021
Reaching K-m i,n File f i The ground shared link is disabled and the content file placement matrix m of the SBSs is readjusted i,n And the overall transmission energy efficiency is optimized.
Step 2: after obtaining the buffer memory placement matrix of SBSs and main satellites, expanding the buffer memory placement matrix to a multi-satellite-ground integrated collaboration sharing network, and introducing a sharing variable a i Shared variable a i When the value is 0, only the ground shared link is started, at the moment, the buffer memory placement matrix in the auxiliary satellite is cleared, when the value of the shared variable ai is 1, only the inter-satellite shared link is started, at the moment, the buffer memory placement matrix in the SBSs is cleared, and then the buffer memory placement matrix of all the SBSs and LEO satellites is solved by adopting a genetic algorithm.
As a further improvement of the present invention, in the step 1, further comprising:
step S1: initializing.
Step S2: placing the coding packet in SBS; when the cache size constraint is satisfied
Figure BDA0003681718310000022
At this time, for each SBS, according to the File set +.>
Figure BDA0003681718310000023
In the order of (a)Placing files f in sequence i If m i,n +1 < K and satisfies the power size constraint, then m i,n ＝m i,n +1, wherein->
Figure BDA0003681718310000024
Representing a set of files, M T Represents the number of code packets which can be stored at most in each SBS, m i,n Representing a file f cached in SBS n i I represents the file sequence number in the file set.
Step S3: code packet placement in the row-main satellite while adjusting the code packet placement in the SBS.
Step S4: updating
Figure BDA0003681718310000025
Step S5: steps S1-S4 are repeated until the variation of η is smaller than σ, stopping the iteration.
As a further improvement of the present invention, in the step S1, the initializing specifically includes:
step S10: let m i,n ,
Figure BDA0003681718310000026
Simultaneously setting 0; wherein m is i,n Representing a file f cached in SBS n i The number of coded packets,/->
Figure BDA0003681718310000027
Indicating the number of encoded packets buffered in the primary satellite.
Step S11: ordering the popularity of the files of each cell from high to low to obtain a file set
Figure BDA0003681718310000031
Step S12: according to
Figure BDA0003681718310000032
The popularity of the files in the whole area is ordered from high to low to obtain a file set +.>
Figure BDA0003681718310000033
Wherein U is i,n Representing the request file f in SBS n i Average number of users, +.>
Figure BDA0003681718310000034
Representing a set of cells, U i Representing the request file f in the entire region i Is a number of average users of the system.
Step S13: setting initial value eta of total energy efficiency eta 0 。
As a further improvement of the present invention, in the step S3, specifically, it includes:
according to the file set
Figure BDA0003681718310000035
Sequentially placing files f in the main satellite i When the cache size constraint is satisfied
Figure BDA0003681718310000036
In which M is S The number of code packets which can be buffered most in the satellite is represented, and the following operations are performed: first, calculate the file f in SBSs i The minimum buffering number of the coding packet is reduced by 1, and the file f is simultaneously i' The minimum buffer number of the coding packet is increased by 1, and the generated energy consumption is changed->
Figure BDA0003681718310000037
If->
Figure BDA0003681718310000038
And satisfy the following
Figure BDA0003681718310000039
And a power size constraint, then->
Figure BDA00036817183100000310
Up to->
Figure BDA00036817183100000311
Calculation of
Figure BDA00036817183100000312
If delta 2 ＞ηδ 1 And->
Figure BDA00036817183100000313
Satisfying the power size constraint, then +.>
Figure BDA00036817183100000314
m i,n ＝m i,n -1，m i',n ＝m i',n +1。
As a further improvement of the present invention, in the steps S2, S3, the formula of the power size constraint is as follows:
Figure BDA00036817183100000315
as a further improvement of the present invention, in the step 2, the solving the cache placement matrix by using a genetic algorithm specifically includes:
step 20: initializing parent population g=0.
Step 21: the fitness, i.e. the total energy efficiency of the system, is calculated.
Step 22: randomly selecting individuals with larger adaptability from parent population, and comparing the transmission file f in the selected individuals i Selecting a higher shared variable a i Taking values, then adjusting the number of coding packets in SBSs and satellites according to the file popularity under the power constraint and the cache size constraint, and generating new individuals by variation;
step 23: and calculating the fitness of the new individuals, merging with the parent population, and then sorting from large to small according to the fitness, and reserving the nPop individuals with the top ranking, namely the next generation population, wherein G=G+1.
Step 24: judging whether G is larger than the set genetic times GEN, if so, outputting individuals with the first fitness rank, otherwise, repeating the steps 22-24.
As a further improvement of the present invention, in said step 20, initializing the parent population specifically comprises:
according to the buffer storage placement vector m solved under single satellite scene i,n And
Figure BDA0003681718310000041
generating a first set of shared variables a i I.e. when the file f is cached in SBS n i When the total number of coded packets is greater than K, the variable a is shared i Take value 0, otherwise take value 1, remaining nPop-1 shared variables a i Randomly generating, and then under the buffer size constraint and the power constraint, placing the residual needed coding packets by the SBSs and the auxiliary satellites from low to high according to the file popularity, so as to generate a parent population with nPop individuals.
As a further development of the invention, in the steps 20, 22, the formula of the power constraint is as follows:
Figure BDA0003681718310000042
the formula of the buffer size constraint is as follows:
Figure BDA0003681718310000043
the beneficial effects of the invention are as follows: 1. according to the star-ground cooperative sharing transmission strategy, the ground base station and the buffer file on the satellite are placed in parallel, so that the energy efficiency maximization of the star-ground integrated cooperative sharing network is realized; 2. compared with a single satellite-ground integrated collaboration sharing network, the space-based network adopts a satellite constellation to increase one inter-satellite sharing link, and can effectively improve the transmission energy efficiency of the system.
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FIG. 1 is a schematic diagram of a star-ground integrated collaboration sharing network model provided by the invention;
FIG. 2 is a schematic diagram showing a comparison of two transmission strategies and two buffering modes under different popularity parameters according to the present invention;
FIG. 3 is a schematic diagram showing two transmission strategies and two buffering modes under different satellite numbers according to the present invention;
FIG. 4 is a schematic diagram showing a comparison of two transmission strategies and two buffering modes under different inter-star distances according to the present invention;
FIG. 5 is a diagram showing two transmission strategies and two buffering modes under different SBS numbers according to the present invention;
fig. 6 is a content placement flow chart of the present invention.
Detailed Description
In order to fully utilize the advantages of a satellite network, the coding caching technology is combined with a multi-satellite-ground integrated network, and because resources on the satellites are limited, the method considers the caching resource sharing of the satellites and the ground network and the satellite-ground integrated cooperative transmission of hot spot data, namely, the satellite-ground integrated cooperative sharing network is built, and the caching content of the ground base station and the caching content of the satellites are jointly designed, so that the accurate pushing of popular content is ensured, and the user service data flow and the overall transmission energy efficiency of different areas are improved. The star-ground integrated collaboration sharing network relates to a double-layer multi-cache node, and the design of file cache and transmission strategies is particularly important and complex.
According to the invention, the research on non-rate coding shows that the coding mode is to realize data fault tolerance by adding redundancy, MDS characteristics are required to be satisfied (namely, original data can be recovered by any k coded data blocks), and a large number of nonlinear data blocks can be generated by non-rate coding, so that the possibility is provided for caching and transmitting data in a multi-satellite-ground integrated network in a multi-level multi-node manner.
The invention adopts a non-rate coding mode, LT (Luby Transform) coding, can obtain infinite number of different coding packets, and can recover the original file by receiving K coding packets. The encoded packets generated by each file are stored distributed in small ground base stations (Small Base Station, SBSs) and LEO satellites.
In the satellite-ground integrated cooperative sharing network, only one main satellite can communicate with ground equipment, two sharing links exist, one is the ground sharing link, a cached coding packet is transmitted to the main satellite through a ground base station, and then the satellite broadcasts the coding packet to a user; the other is an inter-satellite shared link, and the buffered encoded packets are transmitted to the primary satellite via the secondary satellite (i.e., a satellite other than the primary satellite). The SBSs and the LEO satellites cooperate to provide services for the ground users, and the rest of the needed coding packets are transmitted through the shared link and then broadcast to the ground users through the main satellite.
The invention discloses a method for placing the edge cache content of a star-earth integrated cooperative sharing network, which only has a ground sharing link and adopts an iterative algorithm to solve. First, obtaining a content file placement matrix m of SBSs by maximizing overall transmission traffic i,n Second, obtaining a primary satellite buffer memory placement matrix by minimizing overall transmission energy consumption when the number of encoded packets buffered in the primary satellite
Figure BDA0003681718310000051
Reaching K-m i,n File f i The ground shared link is disabled and the content file placement matrix m of the SBSs is readjusted i,n And the overall transmission energy efficiency is optimized.
After the buffer memory placement matrix of the SBSs and the main satellite is obtained, the buffer memory placement matrix of the SBSs and the LEO satellites is expanded to a multi-satellite-ground integrated collaboration sharing network, and a genetic algorithm is adopted to solve the buffer memory placement matrix of the whole SBSs and LEO satellites. Shared variable a i When the value is 0, the ground shared link is started, at the moment, the buffer memory placement matrix in the auxiliary satellite is cleared, and the variable a is shared i When the value is 1, the inter-satellite shared link is started, and the buffer storage matrix in the SBSs is cleared. First initializing parent population, m is calculated in the last step i,n And
Figure BDA0003681718310000061
on the basis of (a), randomly generating a shared variable a i Under the constraint of buffering and power, the SBSs and the auxiliary satellites place the residual needed coding packets from low to high according to the popularity of the files; then calculating fitness, namely total energy efficiency of the system, randomly selecting two individuals with larger fitness in the father population, and comparing the transmitted files f in the two individuals i Selecting a higher shared variable a i Taking value, generating new individuals by mutation, merging and sequencing the new individuals with the parent population, and generating a next generation population; and repeating the genetic operation for a limited time, and outputting an optimal cache placement matrix.
As shown in FIG. 1, the star-ground integrated collaboration sharing network model has the following cell set
Figure BDA0003681718310000062
The cells covered by each SBSs are not overlapped, and the associated user set is +.>
Figure BDA0003681718310000063
A ground area is jointly served by a plurality of LEO satellites at the same orbit height, only one LEO satellite is communicated with ground equipment, namely a main satellite, the rest are auxiliary satellites, only adjacent satellites can be communicated, and the LEO satellite set is->
Figure BDA0003681718310000064
File set is +.>
Figure BDA0003681718310000065
Popularity μ of documents in SBS n i,n The experimental law published in 1949 by the linguist of the university of harvard, jinsli ziff (George Kingsley Zipf), which is a discrete probability distribution that satisfies the Zipf law, i.e., the frequency of an item is inversely proportional to its rank in the frequency table, is expressed as:
Figure BDA0003681718310000066
Figure BDA0003681718310000067
assuming that all files have the same size s, LT encoding the files can result in an infinite number of filesAnd receiving K coded packets from different coded packets to recover the original file. File f i Divided into k source packets each of size
Figure BDA0003681718310000068
D (d is more than or equal to 1 and less than or equal to K) source data packets are randomly and independently selected to be subjected to bit exclusive OR, so that infinite numbers of different coding packets can be obtained, and a source file can be restored with a certain probability by downloading K=k (1+epsilon) coding packets. The LT encoded packets generated for each file are stored in SBSs and LEO satellites in a distributed manner. m is m i,n Representing a file f cached in SBS n i Number of coded packets,/->
Figure BDA0003681718310000069
Representing a file f cached in LEO satellite l i Is a number of coded packets.
The SBSs and LEO satellites cooperatively transmit to provide services for ground users, and when the number of coded packets is insufficient, a shared link is started to transmit the rest coded packets to the main satellite. To maximize the overall transmission energy efficiency of the network, the transmission strategies and buffer matrices of SBSs and LEO satellites need to be carefully designed.
The secondary satellite's buffer matrix is first set to 0, i.e. only the ground shared link is considered. And when the sum of the number of the SBS n and the number of the main satellite cache coding packets is smaller than K, enabling a ground sharing link. The transmission flow rates of the SBSs and LEO satellites are respectively B T And B S The requests of all users should be satisfied as much as possible.
The transmission energy consumption of SBSs is P T The method is mainly divided into two parts, the power consumed by a user is transmitted and the power consumed by a satellite is shared, and the transmission energy consumption of LEO is P S 。
The total flow and total energy consumption of the network are respectively as follows:
B total ＝B T +B S
P total ＝P T +P S
we set up an energy efficiency optimization problem:
Problem 1
Figure BDA0003681718310000071
Figure BDA0003681718310000072
Figure BDA0003681718310000073
Figure BDA0003681718310000074
Figure BDA0003681718310000075
Figure BDA0003681718310000076
Figure BDA0003681718310000077
(2) (3) represents buffer size constraints of SBSs and LEO satellites, (4) represents transmission power constraints, (5) ensures that both SBSs and LEO satellites buffer files f i And (6) indicates that the number of code packets shared to the satellite is not negative.
The transmission file f in SBS n can be easily deduced i Is used for transmitting the traffic of the whole network transmission file f i The energy consumption is respectively
Figure BDA0003681718310000078
The optimization problem is a polynomial of the division, which we transform into a linear polynomial
Figure BDA0003681718310000079
The specific algorithm comprises the following steps:
step S1: initializing. Also let m i,n ,
Figure BDA00036817183100000710
Simultaneously setting 0; ordering the popularity of the files of each cell from high to low to obtain a file set +.>
Figure BDA00036817183100000711
According to->
Figure BDA00036817183100000712
The popularity of the files in the whole area is sequenced from high to low to obtain a file set
Figure BDA0003681718310000081
Setting initial value eta of total energy efficiency eta 0 。
Step S2: coding packet placement in SBS is performed. When the cache size constraint is satisfied
Figure BDA0003681718310000082
At this time, for each SBS, according to the File set +.>
Figure BDA0003681718310000083
Sequentially placing files f i If m i,n +1 < K and satisfies the power size constraint (4), then m i,n ＝m i,n +1。
Step S3: code packet placement in the row-main satellite while adjusting the code packet placement in the SBS. According to the file set
Figure BDA0003681718310000084
Sequentially placing files f in the main satellite i When the cache size constraint is satisfied +.>
Figure BDA0003681718310000085
When the method is performed, the following operations are performed: first, calculate the file f in SBSs i The minimum number of buffers for the encoded packets is reduced by 1,simultaneous file f i' The minimum buffer number of the coding packet is increased by 1, and the generated energy consumption is changed->
Figure BDA0003681718310000086
If it is
Figure BDA0003681718310000087
And satisfy->
Figure BDA0003681718310000088
And a power size constraint (4), then +.>
Figure BDA0003681718310000089
Up to
Figure BDA00036817183100000810
Calculation of
Figure BDA00036817183100000811
If delta 2 ＞ηδ 1 And->
Figure BDA00036817183100000812
Satisfying the power size constraint (4), then +.>
Figure BDA00036817183100000813
m i,n ＝m i,n -1，m i',n ＝m i',n +1。
Step S4: updating
Figure BDA00036817183100000814
Step S5: steps S1-S4 are repeated until the variation of η is smaller than σ, stopping the iteration.
Through simulation analysis, the invention obtains different user densities theta 0 Under the conditions of different buffer sizes M/sI (M represents the number of buffered files and I represents the total number of files) and different file popularity parameters alpha, the comparison of different transmission modes and different buffer modes on transmission energy efficiency is to enable a ground shared link respectivelyAnd optimizing content placement (TS-OPP), enabling ground shared links and hottest content placement (TS-MPP), not enabling ground shared links and optimizing content placement (NS-OPP), not enabling ground shared links and hottest content placement (NS-MPP).
FIG. 2 shows a comparison of two transmission strategies and two buffering modes (buffer size 10% and user density 100 users/km) under different popularity parameters 2 )。
Therefore, the transmission strategy and the caching mode provided for the cache nodes under different cache sizes, different user densities and different file popularity parameters can effectively improve the performance of the system in terms of transmission energy efficiency.
The analysis is that the buffer memory content of the single satellite-ground integrated collaboration sharing network is placed, the buffer memory content is expanded to multiple satellite scenes, namely, an inter-satellite sharing link is increased, at the moment, a sharing vector ai is introduced, when the value is 0, only a ground sharing link is started, at the moment, a buffer memory placement matrix in an auxiliary satellite is cleared, and a variable a is shared i When the value is 1, only the inter-satellite shared link is started, and the buffer storage matrix in the SBSs is cleared. Analyzing the transmission flow and the transmission energy consumption of the SBSs and the LEO satellites again, wherein the transmission flow formula in the network is the same as that in a single satellite scene, and the transmission energy consumption of the SBSs is as follows:
Figure BDA0003681718310000091
wherein,,
Figure BDA0003681718310000092
representing SBS n downlink transmission power; />
Figure BDA0003681718310000093
Representing the transmission power of the terrestrial shared link, +.>
Figure BDA0003681718310000094
Representing the number of encoded packets transmitted to the primary satellite over the terrestrial shared link, pr (U i,n 1) represents SBSn has at least one user request file f i Is a probability of (2).
The main satellite transmission energy consumption is:
Figure BDA0003681718310000095
wherein,,
Figure BDA0003681718310000096
indicating LEO downlink transmission power, +.>
Figure BDA0003681718310000097
Representing a file f cached in SBSs i Is the minimum number of encoded packets, pr (U) i Gtoreq.1) means that there is at least one user request file f in all cells i Is a probability of (2).
The transmission energy consumption of the auxiliary satellite is as follows:
Figure BDA0003681718310000098
wherein l represents the number of hops to the primary satellite and satisfies
Figure BDA0003681718310000099
Figure BDA00036817183100000910
Indicating that transmission is complete within time slot t>
Figure BDA00036817183100000911
Inter-satellite link transmission power, W, consumed by individual encoded packets S Is the channel bandwidth of the satellite, |sigma S | 2 Which represents the power of the noise and,
Figure BDA00036817183100000912
representing inter-satellite link fading coefficients, considering only free space loss, where H ISL And represents the distance between adjacent satellites, lambda is the wavelength of the carrier wave.
Total transport flow: b (B) total ＝B T +B S
Total transmission energy consumption: p (P) total ＝P T +P S +P ISL
Whereby the final optimization problem:
Figure BDA0003681718310000101
s.t.(1)(2)(6)
Figure BDA0003681718310000102
Figure BDA0003681718310000103
Figure BDA0003681718310000104
a i ∈{0,1} (10)
(7) The method comprises the steps of (1) representing buffer size constraint, (8) representing transmission power constraint, (9) representing at least one coded packet buffered in both satellite and SBSs, and (10) representing the value of a shared variable as 0 and 1.
Because of the cache variable related to double layers and multiple nodes, a genetic algorithm is adopted to solve a cache placement matrix, and the specific algorithm comprises the following steps:
step 20: initializing parent population g=0. According to the buffer storage placement vector m solved under single satellite scene i,n And
Figure BDA0003681718310000105
generating a first group a i I.e. when the file f is cached in SBS n i A when the total number of coded packets is greater than K i Take value 0, otherwise take value 1, remaining nPop-1 shared variables a i Randomly generated. The SBSs and secondary satellites then place the remaining required code packets from low to high according to file popularity under cache size constraints (7) and power constraints (8), yielding a parent population with nPop individuals.
Step 21: the fitness, i.e. the total energy efficiency of the system, is calculated.
Step 22: randomly selecting two individuals with larger adaptability from the parent population, and comparing the two individuals to transmit the file f i Selecting a higher shared variable a i And (3) taking a value, and then under the power constraint (8) and the buffer size constraint (7), regulating the number of coding packets in the SBSs and the satellites according to the file popularity size, and generating new individuals through mutation.
Step 23: and calculating the fitness of the new individuals, merging with the parent population, and then sorting from large to small according to the fitness, and reserving the nPop individuals with the top ranking, namely the next generation population, wherein G=G+1.
Step 24: judging whether G is larger than the set genetic times GEN, if so, outputting individuals with the first fitness rank, otherwise, repeating the steps 22-24.
Through simulation analysis, the invention obtains different satellite parameters, under different SBSs, the comparison of not enabling the inter-satellite shared link and enabling the inter-satellite shared link, different transmission modes and different buffer modes on transmission energy efficiency is respectively to enable two shared links and optimized content placement (TSS-OPP), enable two shared links and hottest content placement (TSS-MPP), only the inter-satellite shared link and optimized content placement (SS-OPP), and only the inter-satellite shared link and hottest content placement (SS-MPP). As shown in fig. 3-5, the comparison between two transmission strategies and two buffer modes under different satellite numbers in fig. 3 (the buffer size of the satellite is 20%, the inter-satellite distance is 100km, and the number of sbss is 5); fig. 4 shows a comparison of two transmission strategies and two buffer modes (the number of satellites is 5, the size of the satellite buffer is 20%, and the number of SBSs is 5) under different inter-satellites distances, and fig. 5 shows a comparison of two transmission strategies and two buffer modes (the number of satellites is 5, the size of the satellite buffer is 20%, and the inter-satellite distance is 100 km) under different SBSs.
Therefore, for different satellite parameters and different SBSs, the inter-satellite and ground shared links are started, and the performance of the system in the aspect of transmission energy efficiency can be effectively improved by using the provided collaborative caching mode based on the genetic algorithm.
The invention researches a transmission strategy and an edge cache content placement method of a satellite-ground integrated network, considers limited cache resources and energy resources and hierarchical isomerism of a system, combines a coding cache technology, provides a satellite-ground collaboration sharing transmission strategy, combines a ground base station with a cache file placed on a satellite, and realizes energy efficiency maximization of the satellite-ground integrated collaboration sharing network:
1. firstly, a single satellite-ground integrated network is considered, a concept of a ground shared link is provided, transmission flow and transmission energy consumption expression required by user demands in a system within a certain time are deduced by combining with non-rate coding cache, a system energy efficiency expression is obtained and optimized, and effectiveness of the provided collaborative shared transmission strategy and the caching mode in terms of improving system transmission energy efficiency is verified.
2. And expanding a plurality of satellites on the basis of a single satellite scene, adding an inter-satellite shared link, further deriving a new transmission energy efficiency expression, strategically selecting the shared link and the buffer file by using a genetic algorithm, and verifying that compared with a single satellite-ground integrated collaborative shared network, an inter-satellite shared link is increased by a space-based network by adopting a satellite constellation, so that the transmission energy efficiency of the system can be effectively improved.
The invention has the beneficial effects that: 1. according to the star-ground cooperative sharing transmission strategy, the ground base station and the buffer file on the satellite are placed in parallel, so that the energy efficiency maximization of the star-ground integrated cooperative sharing network is realized; 2. compared with a single satellite-ground integrated collaboration sharing network, the space-based network adopts a satellite constellation to increase one inter-satellite sharing link, and can effectively improve the transmission energy efficiency of the system.
The foregoing is a further detailed description of the invention in connection with the preferred embodiments, and it is not intended that the invention be limited to the specific embodiments described. It will be apparent to those skilled in the art that several simple deductions or substitutions may be made without departing from the spirit of the invention, and these should be considered to be within the scope of the invention.

Claims (6)

1. The method for placing the edge cache content of the star-to-ground integrated collaboration sharing network is characterized by comprising the following steps of:
step 1: firstly, setting a buffer matrix of an auxiliary satellite to 0, when the sum of the number of the buffer coding packets of the SBSn and the main satellite is smaller than K, starting a ground shared link, and obtaining a content file placement matrix m of the SBSs by maximizing the total transmission flow i,n Obtaining a main satellite buffer storage placement matrix by minimizing the total transmission energy consumption, and when the number of the coded packets buffered in the main satellite
Figure FDA0004182264020000011
Reaching K-m i,n File f i The ground shared link is disabled and the content file placement matrix m of the SBSs is readjusted i,n Optimizing the overall transmission energy efficiency;
step 2: after obtaining the buffer memory placement matrix of SBSs and main satellites, expanding the buffer memory placement matrix to a multi-satellite-ground integrated collaboration sharing network, and introducing a sharing variable a i Shared variable a i When the value is 0, only the ground shared link is started, at the moment, the buffer memory placement matrix in the auxiliary satellite is cleared, and the variable a is shared i When the value is 1, only the inter-satellite shared link is started, at the moment, the buffer storage matrix in the SBSs is cleared, and then the buffer storage matrix of all SBSs and LEO satellites is solved by adopting a genetic algorithm;
in the step 1, further includes:
step S1: initializing;
step S2: placing the coding packet in SBS; when the cache size constraint is satisfied
Figure FDA0004182264020000012
At this time, for each SBS, according to the File set +.>
Figure FDA0004182264020000013
Sequentially placing files f i If m i,n +1 < K and satisfies the power size constraint, then m i,n ＝m i,n +1, wherein->
Figure FDA0004182264020000014
Representing a set of files, M T Represents the number of code packets which can be stored at most in each SBS, m i,n Representing a file f cached in SBSn i I represents the file sequence number in the file set;
step S3: placing the coding packet in the main satellite, and simultaneously adjusting the placement condition of the coding packet in the SBS;
step S4: updating
Figure FDA0004182264020000015
Step S5: repeating steps S1-S4 until the variation of eta is less than sigma, stopping iteration;
in the step 2, the method for solving the cache placement matrix by adopting a genetic algorithm specifically comprises the following steps:
step 20: initializing parent population g=0;
step 21: calculating fitness, namely the total energy efficiency of the system;
step 22: randomly selecting individuals with larger adaptability from parent population, and comparing the transmission file f in the selected individuals i Selecting a higher shared variable a i Taking values, then adjusting the number of coding packets in SBSs and satellites according to the file popularity under the power constraint and the cache size constraint, and generating new individuals by variation;
step 23: calculating the fitness of new individuals, merging with the parent population, and then sequencing from large to small according to the fitness, and reserving the nPop individuals with the top ranking, namely the next generation population, wherein G=G+1;
step 24: judging whether G is larger than the set genetic times GEN, if so, outputting individuals with the first fitness rank, otherwise, repeating the steps 22-24.
2. The method for placing the content in the edge cache according to claim 1, wherein in the step S1, the initializing specifically includes:
step S10: let m i,n ,
Figure FDA0004182264020000021
Simultaneously setting 0; wherein m is i,n Representing a file f cached in SBSn i The number of coded packets,/->
Figure FDA0004182264020000022
Indicating the number of encoded packets buffered in the primary satellite;
step S11: ordering the popularity of the files of each cell from high to low to obtain a file set
Figure FDA0004182264020000023
Step S12: according to
Figure FDA0004182264020000024
The popularity of the files in the whole area is sequenced from high to low to obtain a file set
Figure FDA0004182264020000025
Wherein U is i,n Representing a request file f in SBSn i Average number of users, U i Representing the request file f in the entire region i Average number of users, +.>
Figure FDA0004182264020000026
Representing a set of cells;
step S13: setting initial value eta of total energy efficiency eta 0 。
3. The method for placing the content in the edge cache according to claim 1, wherein in the step S3, specifically comprising:
according to the file set
Figure FDA0004182264020000027
Sequentially placing files f in the main satellite i When the cache size constraint is satisfied
Figure FDA0004182264020000028
In which M is S The number of code packets which can be buffered most in the satellite is represented, and the following operations are performed: first, calculate the file f in SBSs i The minimum buffering number of the coding packet is reduced by 1, and the file f is simultaneously i' The minimum buffer number of the coding packet is increased by 1, and the generated energy consumption is changed
Figure FDA0004182264020000029
If->
Figure FDA00041822640200000210
And satisfy the following
Figure FDA0004182264020000031
And a power size constraint, then->
Figure FDA0004182264020000032
Up to->
Figure FDA0004182264020000033
Calculation of
Figure FDA0004182264020000034
If delta 2 ＞ηδ 1 And (2) and
Figure FDA0004182264020000035
satisfying the power size constraint, then +.>
Figure FDA0004182264020000036
m i,n ＝m i,n -1，m i',n ＝m i',n +1。
4. The method according to claim 3, wherein in the steps S2 and S3, the formula of the power size constraint is as follows:
Figure FDA0004182264020000037
5. the method for placing content in an edge cache according to claim 1, wherein in said step 20, initializing a parent population specifically comprises:
according to the buffer storage placement vector m solved under single satellite scene i,n And
Figure FDA0004182264020000038
generating a first set of shared variables a i I.e. when the file f is cached in SBSn i When the total number of coded packets is greater than K, the variable a is shared i Take value 0, otherwise take value 1, remaining nPop-1 shared variables a i Randomly generating, and then under the buffer size constraint and the power constraint, placing the residual needed coding packets by the SBSs and the auxiliary satellites from low to high according to the file popularity, so as to generate a parent population with nPop individuals.
6. The method for edge cache content placement as recited in claim 5, wherein, in said steps 20, 22,
the formula of the buffer size constraint is as follows:
Figure FDA0004182264020000039
the power constraint is formulated as follows:
Figure FDA00041822640200000310
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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107846704A (en) * 2017-10-26 2018-03-27 北京邮电大学 A kind of resource allocation and base station service arrangement method based on mobile edge calculations
CN111741495A (en) * 2020-06-22 2020-10-02 哈尔滨工业大学(深圳)(哈尔滨工业大学深圳科技创新研究院) Design method for high-energy-efficiency coding cache content placement scheme in heterogeneous network
CN113630176A (en) * 2021-09-18 2021-11-09 长春理工大学 Game cache multi-path transmission method for earth observation of LEO satellite data
CN114449477A (en) * 2022-03-08 2022-05-06 天津理工大学 Internet of vehicles content distribution method based on edge cache and immune clone strategy

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107846704A (en) * 2017-10-26 2018-03-27 北京邮电大学 A kind of resource allocation and base station service arrangement method based on mobile edge calculations
CN111741495A (en) * 2020-06-22 2020-10-02 哈尔滨工业大学(深圳)(哈尔滨工业大学深圳科技创新研究院) Design method for high-energy-efficiency coding cache content placement scheme in heterogeneous network
CN113630176A (en) * 2021-09-18 2021-11-09 长春理工大学 Game cache multi-path transmission method for earth observation of LEO satellite data
CN114449477A (en) * 2022-03-08 2022-05-06 天津理工大学 Internet of vehicles content distribution method based on edge cache and immune clone strategy

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