CN113472420A - Satellite network cache placement method based on regional user interest perception - Google Patents

Satellite network cache placement method based on regional user interest perception Download PDF

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CN113472420A
CN113472420A CN202110727166.3A CN202110727166A CN113472420A CN 113472420 A CN113472420 A CN 113472420A CN 202110727166 A CN202110727166 A CN 202110727166A CN 113472420 A CN113472420 A CN 113472420A
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content
leo satellite
cache
cluster
satellite node
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CN113472420B (en
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刘治国
董效奇
汪林
潘成胜
李运琪
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Dalian University
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Abstract

The invention relates to a satellite network cache placement method based on regional user interest perception, which comprises the steps of extracting a request log of a base station and establishing a content library set; acquiring state information of an LEO satellite node; establishing an LEO satellite node set as a cache space according to the state information; calculating the similarity of the content labels; clustering the content into a plurality of content clusters according to the similarity of the content labels; calculating the interestingness of each content cluster; dividing the cache space into cache subspaces of each content cluster according to the interest degree of the content cluster; determining popularity of the content; determining the number of the selected contents in each content cluster according to the popularity and the cache subspace; placing selected content assemblies in the plurality of content clusters into a content assembly; ranking all the placing contents according to the popularity to obtain a placing content ordered set; and placing the contents in the ordered set of placed contents into the LEO satellite node according to the scheme of shortest placing time. The method and the device realize the reduction of content response time delay and the improvement of content hit rate.

Description

Satellite network cache placement method based on regional user interest perception
Technical Field
The invention relates to the field of satellite networks, in particular to a satellite network cache placement method based on regional user interest perception.
Background
The sixth generation mobile communication system is a communication system that integrates a terrestrial network with a satellite communication system. In the aspect of communication coverage, the communication scene of 6G can be expanded to sea, land, air and even underwater space. As on-board processing performance continues to improve, research into deploying caching schemes on satellites is receiving increasing attention from researchers. And the cache placement problem in the satellite network directly influences the content request effect.
The satellite network adopts a communication mode based on ICN, and the satellite nodes can realize data caching and local caching content perception. And adopting a network architecture based on the SDN to globally control various network resources.
However, the content has regional differences in the wide-area coverage satellite network, and the content selection of the whole network affects the content request response effect.
Disclosure of Invention
The invention aims to provide a satellite network cache placement method based on regional user interest perception, which can reduce the response time delay of contents and improve the hit rate of the contents.
In order to achieve the purpose, the invention provides the following scheme:
a satellite network cache placement method based on regional user interest perception, the method comprising:
extracting request logs of all base stations in an area and establishing a whole network content library set in the area;
acquiring state information of a LEO satellite node, wherein the state information comprises: inter-satellite link bandwidth information of the LEO satellite and space capacity information of the LEO satellite;
establishing an LEO satellite node set as a cache space according to the state information of the LEO satellite nodes;
calculating the label similarity of the contents in the content library set;
clustering the content in the content library set into a plurality of content clusters according to the content label similarity;
calculating the interest degree of the users in the area to each content cluster;
dividing a cache subspace of each content cluster in the cache space according to the interestingness of the content cluster;
determining the popularity of the content in each of the content clusters;
determining the number of the selected contents in each content cluster according to the popularity and the cache subspace;
placing selected ones of the plurality of content clusters into a content collection;
ranking all the placing contents according to the popularity of each placing content in the placing content set to obtain a placing content ordered set;
and sequentially placing the contents in the placed content ordered set into the LEO satellite node according to the state information of the LEO satellite node according to the scheme with the shortest placing time.
Optionally, the calculating the tag similarity of the content in the content library set specifically includes:
using formulas
Figure BDA0003139099920000021
Calculating the label similarity of the contents in the content library set; wherein, Sim(s)a,sb) Is the label similarity of content a and content b, saIs content a, sbIs content b, ljFor the jth tag, the number of tags,
Figure BDA0003139099920000022
the weight of the jth label in content a,
Figure BDA0003139099920000023
is the weight of the jth label in the content b, and m is the total number of labels.
Optionally, the calculating the interest level of the user in the area in each content cluster specifically includes:
using formulas
Figure BDA0003139099920000024
Calculating to obtain each content cluster of users in the regionThe interest level of (2); wherein,
Figure BDA0003139099920000025
the interest degree of the users in the area to the g-th content cluster, q is the number of base stations in the area, u1、u2And uqThe number of users under the first base station, the second base station and the q-th base station respectively, omega is the total number of users in the area,
Figure BDA0003139099920000026
and
Figure BDA0003139099920000027
short-term interest degrees of users with the areas of the first base station, the second base station and the q base station to the g content cluster are respectively,
Figure BDA0003139099920000031
1,2, q, wherein (t)0,t1)、(t1,t2) And (t)n-1,tn) First, second and nth statistical time periods respectively,
Figure BDA0003139099920000032
for the short-term interest of users under the z-th base station in the area in the g-th content cluster,
Figure BDA0003139099920000033
and
Figure BDA0003139099920000034
respectively the number of times of requests of the user to the g-th content cluster in the first statistical time period, the second statistical time period and the n-th statistical time period under the z-th base station,
Figure BDA0003139099920000035
and
Figure BDA0003139099920000036
for all users under the z th base station in the first, second and nth statistical time periodsNumber of requests for content clusters.
Optionally, the dividing the cache subspace of each content cluster in the cache space according to the interestingness of the content cluster specifically includes:
using formulas
Figure BDA0003139099920000037
Determining a cache subspace of a single content cluster; wherein, CgThe cache subspace for the g-th content cluster,
Figure BDA0003139099920000038
the interest degree of users in the area to the g-th content cluster, C is the total cache space, d is the number of the content clusters, and g is the g-th content cluster.
Optionally, the determining the popularity of the content in each content cluster specifically includes:
using formulas
Figure BDA0003139099920000039
Determining the popularity of the content in each of the content clusters; wherein k is the popularity ranking of the whole network content, s is the content name,
Figure BDA00031390999200000310
and for the popularity of the ith content in each content cluster, alpha is a parameter of Zipf distribution, and N is the total number of the whole network contents.
Optionally, the determining the number of the selected contents in each content cluster according to the popularity and the cache subspace specifically includes:
using formulas
Figure BDA00031390999200000311
Calculating the number of the selected contents in the g-th content cluster; wherein w is the number of contents selected in the content cluster,
Figure BDA00031390999200000312
to cache whether the ith content is present in the subspace,
Figure BDA00031390999200000313
is the fractional space of the ith content, CgIs the cache subspace of the g-th content cluster.
Optionally, the sequentially placing the content in the ordered set of placed contents into the LEO satellite node according to the state information of the LEO satellite node according to the scheme that the placing time is the shortest includes:
initializing i, and enabling i to be 1;
calculating the average response time delay of each LEO satellite node in the LEO satellite node set according to the ith content in the placed content ordered set;
sequencing all LEO satellite nodes according to the ascending order of the average response time delay, initializing h, and enabling h to be 1;
judging whether the space of the ith content in the ordered set of the placed contents is larger than the remaining cache space of the selected h-th LEO satellite node or not to obtain a first judgment result;
if the first judgment result shows that the content is the h-th content, increasing the value of the h by 1, and returning to the step of judging whether the space for placing the ith content in the ordered set of contents is larger than the residual cache space of the selected h-th LEO satellite node to obtain a first judgment result;
and if the first judgment result shows that the content is not the h-th LEO satellite node, sending the ith content to the h-th LEO satellite node, increasing the value of i by 1, and returning to the step of calculating the average response time delay of each LEO satellite node in the LEO satellite node set according to the ith content in the placed content ordered set until all the content in the placed content ordered set is traversed.
Optionally, the calculating an average response delay of each LEO satellite node in the LEO satellite node set according to the ith content in the placed content ordered set specifically includes:
making N decision schemes according to the required cache space of each content in the placed content ordered set and the size of the residual cache space of each LEO satellite node;
using formulas
Figure BDA0003139099920000041
Calculating the average response time delay under each decision scheme; where T is the average response delay under the decision scheme,
Figure BDA0003139099920000042
to place the ith content into the response delay of the placeable LEO satellite node for the ith content marked in the decision scheme,
Figure BDA0003139099920000043
required buffer space for ith content, vxThe bandwidth of the x-th communication link between the placeable LEO satellite node of the ith content and the content request point, n is the number of the communication links between the placeable LEO satellite node of the ith content and the content request point, tdFor propagation delay of inter-satellite links of LEO satellite nodes,
Figure BDA0003139099920000045
for the number of times the ith content was accessed,
Figure BDA0003139099920000044
requesting the response time of the ith content from the LEO satellite node for a user request point, wherein Y is the number of the selected contents in all content clusters in the area;
and selecting the decision scheme with the minimum average response time delay for content placement.
Optionally, the making N decision schemes according to the size of the cache space required by each content in the ordered set of placed contents and the remaining cache space of each LEO satellite node specifically includes:
initializing i, and enabling i to be 1;
determining LEO satellite nodes with the content capable of placing LEO satellite nodes and the residual cache space larger than the cache space required by the ith content in the ordered set of placed contents to form a set of LEO satellite nodes with the content capable of placing LEO satellite nodes;
judging whether the LEO satellite node set capable of being placed in the content is empty or not to obtain a second judgment result;
if the second judgment result shows that the content of the LEO satellite node set can be placed in the ordered set of the placement contents, selecting any LEO satellite node in the LEO satellite node set with the content capable of being placed, marking the LEO satellite node with the ith content capable of being placed as the LEO satellite node with the ith content, updating the residual cache space of the content capable of being placed in the LEO satellite node with the ith content, increasing the value of i by 1, and returning to the step of determining the LEO satellite node with the residual cache space of the content capable of being placed in the LEO satellite node larger than the cache space required by the ith content in the ordered set of the placement contents to form the LEO satellite node set with the content capable of being placed in the ordered set;
and if the second judgment result shows that the content is in the ordered set, giving up the ith content, increasing the value of i by 1, returning to the step of determining the LEO satellite nodes with the residual cache space for placing the LEO satellite nodes larger than the cache space required by the ith content in the ordered set of the placed content to form a set of the LEO satellite nodes with the placeable content, and generating a decision scheme until the content in the ordered set of the placed content is traversed to be finished.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the invention provides a satellite network cache placement method based on regional user interest perception, which comprises the following steps: extracting request logs of all base stations in an area and establishing a whole network content library set in the area; acquiring state information of a LEO satellite node, wherein the state information comprises: inter-satellite link bandwidth information of the LEO satellite and space capacity information of the LEO satellite; establishing an LEO satellite node set as a cache space according to the state information of the LEO satellite nodes; calculating the label similarity of the contents in the content library set; clustering the content in the content library set into a plurality of content clusters according to the content label similarity; calculating the interest degree of the users in the area to each content cluster; dividing a cache subspace of each content cluster in the cache space according to the interestingness of the content cluster; determining the popularity of the content in each of the content clusters; determining the number of the selected contents in each content cluster according to the popularity and the cache subspace; placing selected ones of the plurality of content clusters into a content collection; ranking all the placing contents according to the popularity of each placing content in the placing content set to obtain a placing content ordered set; and sequentially placing the contents in the placed content ordered set into the LEO satellite node according to the state information of the LEO satellite node according to the scheme with the shortest placing time. The method provided by the invention is superior to a comparison method in the aspects of response delay and cache hit rate of the content, not only reduces the response delay of the content, but also considers the distribution balance of the content.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
FIG. 1 is a flowchart of a satellite network cache placement method based on regional user interest perception according to the present invention;
FIG. 2 is a scene description diagram of a satellite network cache placement method based on regional user interest perception according to the present invention;
FIG. 3 is a comparison graph of average response time delay of a satellite network cache placement method based on regional user interest perception provided by the present invention;
FIG. 4 is a comparison graph of average cache hit rates of a satellite network cache placement method based on regional user interest perception provided by the present invention;
FIG. 5 is a comparison graph showing how the cache hit rate of a satellite network cache placement method based on regional user interest perception is affected by the number of base stations according to the present invention;
fig. 6 is a graph of the variation of the average response delay of the satellite network cache placement method based on the regional user interest perception along with the Zipf parameter.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention aims to provide a satellite network cache placement method based on regional user interest perception, which can reduce the response time delay of contents and improve the hit rate of the contents.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
The invention relates to a double-layer satellite network architecture based on SDN (software Defined network), wherein an LEO (Low Earth orbit) layer satellite is a forwarding layer in the architecture. A constellation composed of 3 geo (geographic orbit) satellites is an SDN control layer and is responsible for state collection of LEO satellites and calculation of cache placement positions.
The application scene of the invention comprises two parts, namely a ground network and a satellite communication network. SDN based satellite networks consist of a GEO satellite constellation and a LEO satellite constellation. The GEO satellite is responsible for monitoring the state of the LEO satellite, is provided with an SDN controller and uniformly controls the network state and the resource configuration of the LEO through an OpenFlow protocol. A forwarding plane is formed by networking a plurality of LEO satellites, and a stable inter-satellite link is formed through a fixed laser link under the management of SDN control.
In the above scenario, the number of ground communication base stations under the coverage of a single LEO satellite is not fixed. Most users access the network through a ground base station, and the base station can count and collect request data of a large number of users. After the base station establishes communication with the satellite, request data of local users can be uploaded to the satellite, and regional content is selected for caching under the unified decision of the SDN controller. And the SDN controller can monitor the state of the whole network satellite, including the state of the LEO satellite and the state of an inter-satellite link, and can decide the optimal content placement position in a global view. Fig. 2 is a network scenario diagram.
As shown in fig. 1, a satellite network cache placement method based on regional user interest perception includes: extracting request logs of all base stations in an area and establishing a whole network content library set in the area; acquiring state information of a LEO satellite node, wherein the state information comprises: inter-satellite link bandwidth information of the LEO satellite and space capacity information of the LEO satellite; establishing an LEO satellite node set as a cache space according to the state information of the LEO satellite nodes; calculating the label similarity of the contents in the content library set; clustering the content in the content library set into a plurality of content clusters according to the content label similarity; calculating the interest degree of the users in the area to each content cluster; dividing a cache subspace of each content cluster in the cache space according to the interestingness of the content cluster; determining the popularity of the content in each of the content clusters; determining the number of the selected contents in each content cluster according to the popularity and the cache subspace; placing selected ones of the plurality of content clusters into a content collection; ranking all the placing contents according to the popularity of each placing content in the placing content set to obtain a placing content ordered set; and sequentially placing the contents in the placed content ordered set into the LEO satellite node according to the state information of the LEO satellite node according to the scheme with the shortest placing time.
The calculating of the tag similarity of the content in the content library set specifically includes: using formulas
Figure BDA0003139099920000081
Calculating the label similarity of the contents in the content library set; wherein, Sim(s)a,sb) Is the label similarity of content a and content b, saIs content a, sbIs content b, ljFor the jth tag, the number of tags,
Figure BDA0003139099920000082
for jth tag in content aThe weight in (1) is (are),
Figure BDA0003139099920000083
is the weight of the jth label in the content b, and m is the total number of labels.
The content name is divided into a number of matchable fields according to the "/" separator in the packet naming. Dividing fields in the naming format and a full gateway key word set K ═ K1,k2,···,kuThe elements in the are matched.
The theme tag set is L ═ L1,l2,···,lmThat a keyword may belong to multiple topic types, a single content siIs characterized by:
Figure BDA0003139099920000084
presentation subject label ljIn the content siThe weight in (1).
After the matching of the content matching field and the keyword, one label l is calculated by adopting a statistical methodjIn the content siThe weight in (1). While a keyword may be subordinate to multiple tags, e.g. tag k1：la,···,lbLabel ljIn the content siThe weight calculation formula in (1) is:
Figure BDA0003139099920000085
wherein,
Figure BDA0003139099920000086
represents the content siAfter matching the keyword, the keyword depends from the tag ljThe total number of (a) and (b),
Figure BDA0003139099920000087
represents the content siThe sum of the number of field matchable separated. After the VSM vector of the content feature is established, the cosine similarity of any two content features is calculated as:
Figure BDA0003139099920000091
clustering the content in the content library set into a plurality of content clusters according to the content label similarity as follows:
randomly draw d samples from the content set as an initial mean vector u1,u2,···,ud}
Initialization
Figure BDA0003139099920000092
Fori＝1:n
Calculating a sample siAnd each mean vector uj(1. ltoreq. j. ltoreq. d) distance Sim(s)i,uj)；
According to the sum ofiDetermining cluster marks according to the nearest mean vector;
content siDividing into a cluster of responses;
End
Forj＝1:d
calculating a new mean vector within each cluster
Figure BDA0003139099920000093
Summing each sample in the cluster/number of samples in the cluster;
If
Figure BDA0003139099920000094
the current mean vector ujIs updated to
Figure BDA0003139099920000095
Else
Keeping the current mean vector unchanged;
End
End
until the mean vector of each cluster is not updated;
output G ═ G1,g2,···,gd}。
The calculating the interest degree of the user in the region in each content cluster specifically includes: using formulas
Figure BDA0003139099920000096
Calculating the interest degree of the users in the region to each content cluster; wherein,
Figure BDA0003139099920000097
the interest degree of users in the area to the g-th content cluster, g is the g-th content cluster, q is the number of base stations in the area, u1、u2And uqThe number of users under the first base station, the second base station and the q-th base station respectively, omega is the total number of users in the area,
Figure BDA0003139099920000098
and
Figure BDA0003139099920000099
respectively short-term interest degrees of users under a first base station, a second base station and a q-th base station in the area in the g-th content cluster,
Figure BDA0003139099920000101
1,2, q, wherein (t)0,t1)、(t1,t2) And (t)n-1,tn) First, second and nth statistical time periods respectively,
Figure BDA0003139099920000102
for the short-term interest of users under the z-th base station in the area in the g-th content cluster,
Figure BDA0003139099920000103
and
Figure BDA0003139099920000104
respectively the number of times of requests of the user to the g-th content cluster in the first statistical time period, the second statistical time period and the n-th statistical time period under the z-th base station,
Figure BDA0003139099920000105
and
Figure BDA0003139099920000106
the number of requests for all content clusters in the first, second and nth statistical time periods for the user under the z-th base station respectively.
Under the system model, a single LEO satellite covers a plurality of ground base stations. In selecting the most appropriate cache contents to maximize the cache gain of the LEO satellite, the collection of the request data of the base station under the satellite coverage is mainly considered. The group users are relatively fixed under a single base station, and the movement of small-scale users has little influence on the group request data. Since popular content has a life cycle that is not typically too long, the short-term historical request behavior can reflect the user's local preference for content at the base station. Meanwhile, the user's interest in the content may be represented by the number of requests for the content. Defining a statistical time t0-t1The short-term interest of the group users under the base station to a single content cluster g is
Figure BDA0003139099920000107
Then
Figure BDA0003139099920000108
Wherein,
Figure BDA0003139099920000109
representing the statistical time t of users under a single base station0-t1The cumulative number of requests for the content cluster g over time,
Figure BDA00031390999200001010
indicating the statistical time t of the user under the base station0-t1Total number of requests in time. And in order to eliminate accidental variation caused by over short selected statistical time, the mean value of the preamble statistical period is increased to more accurately represent the mean valueFront value, so with short-term interest in preamble periods
Figure BDA00031390999200001011
Is calculated as:
Figure BDA00031390999200001012
wherein,
Figure BDA00031390999200001013
representing the current statistical time period t0-t1The degree of interest in the content of the content,
Figure BDA00031390999200001014
representing the interestingness within n adjacent preamble periods of the statistical period.
Due to the fact that a plurality of base stations exist in the coverage range of a single satellite, the different activity degrees of users under different base stations are considered, and the users under different base stations also have different interests. Therefore, the interest degree of the user in the single base station for the content cannot represent the interest degree of the whole area, and after the interest degrees of the user in the single base station are respectively calculated, the weighted value of the interest degree of each base station in the whole area is used as the interest preference of the area content, so that the caching income is maximized. The number of base stations in a defined area is q, and the number of fixed users under the base stations is mu respectively1,μ2···μqThe total number of the regional users is omega, the interest degree of a single base station to a single content cluster can be respectively calculated through a formula 3.5, and then the interest degree of a single content cluster g in the region
Figure BDA0003139099920000111
Comprises the following steps:
Figure BDA0003139099920000112
the dividing the cache subspace of each content cluster in the cache space according to the interestingness of the content cluster specifically includes: benefit toBy the formula
Figure BDA0003139099920000113
Determining a cache space of a single content cluster; wherein, CgIs the buffer space of the g-th content cluster,
Figure BDA0003139099920000114
the interest degree of the users in the area to the g-th content cluster, C is the total cache space, and d is the number of the content clusters.
The determining the popularity of the content in each content cluster specifically includes: using formulas
Figure BDA0003139099920000115
Determining the popularity of the content in each of the content clusters; wherein k is the popularity ranking of the whole network content, s is the content name,
Figure BDA0003139099920000116
and for the popularity of the ith content in each content cluster, alpha is a parameter of Zipf distribution, and N is the total number of the whole network contents.
The determining the number of the selected contents in each content cluster according to the popularity and the cache subspace specifically includes: using formulas
Figure BDA0003139099920000117
Calculating the number of the selected contents in the g-th content cluster; wherein w is the number of contents selected in the content cluster,
Figure BDA0003139099920000118
for caching subspaces for the presence of content si，
Figure BDA0003139099920000119
Is a content siC is the ratio space ofgIs the cache subspace of the g-th content cluster.
The requests for media content by users throughout the network conform to a Zipf distribution. Namely popularity representation with popularity ranking k and content name s in the whole networkComprises the following steps:
Figure BDA00031390999200001110
where α is a parameter of the Zipf distribution, and N represents the number of media contents of the whole network.
Due to the limited satellite cache space, the reasonable placement of selected cache content can improve user experience. The process by which a user request is responded to is first analyzed. The single policy calculation is considered herein as a time slice, and the choice of time slice is small. And the concept of virtual nodes and virtual topology is introduced in the satellite network, i.e. user requests within a single time slice are aggregated onto the satellite acting as a virtual node, while the dynamics of the satellite topology of the shorter time slice are not taken into account. The user request is sent to the virtual node, and if the content exists in the node cache, the content is returned. If the content does not exist in the node, the interest packet is sent to the surrounding nodes to search for the required content. If the search exceeds the response time, the content is searched directly from an Internet Service Provider (ISP). Under the ideal condition, the content required by the user can be satisfied in the satellite network.
After the cache space of the whole network is divided according to the interest degree of the user in the content cluster, in the space distributed by a single content cluster, the content clusters are arranged in a descending order according to the popularity degree of the content, and the content with high popularity degree is preferentially placed. If the size of the selected content to be cached exceeds the remaining size of the current content cluster, the content which can be cached in the content popularity list is selected in a forward-delay manner until the cache space allocated to the content cluster is completely allocated. Defining a selected one of the content clusters as g ═ s1,s2···swThe number of the selected contents in a single cluster is w, and the sizes of the contents are respectively w
Figure BDA0003139099920000121
Then
Figure BDA0003139099920000122
The sequentially placing the contents in the placing content ordered set into the LEO satellite node according to the state information of the LEO satellite node according to the scheme that the placing time is shortest specifically includes: initializing i, and enabling i to be 1; calculating the average response time delay of each LEO satellite node in the LEO satellite node set according to the ith content in the placed content ordered set; sequencing all LEO satellite nodes according to the ascending order of the average response time delay, initializing h, and enabling h to be 1; judging whether the space of the ith content in the ordered set of the placed contents is larger than the remaining cache space of the selected h-th LEO satellite node or not to obtain a first judgment result; if the first judgment result shows that the content is the h-th content, increasing the value of the h by 1, and returning to the step of judging whether the space for placing the ith content in the ordered set of contents is larger than the residual cache space of the selected h-th LEO satellite node to obtain a first judgment result; and if the first judgment result shows that the content is not the h-th LEO satellite node, sending the ith content to the h-th LEO satellite node, increasing the value of i by 1, and returning to the step of calculating the average response time delay of each LEO satellite node in the LEO satellite node set according to the ith content in the placed content ordered set until all the content in the placed content ordered set is traversed.
The sequentially placing the contents in the ordered set of placed contents into the cache space according to the scheme that the placing time is shortest specifically includes: calculating the average response time delay of each content placement position in the content placeable satellite node set, and selecting the content placeable satellite node with the minimum average response time delay as the placement position of the content; selecting the content with the highest popularity in the ordered set of placed content; judging the size of the placement space of the content with the highest popularity in the ordered set of placement content and the size of the remaining cache space in which the selected content can be placed in the satellite node, and obtaining a first judgment result; if the first judgment result shows that the placement space of the content with the highest popularity in the placed content ordered set is smaller than the remaining cache space of the selected content where the satellite node can be placed, recording the position of the selected content where the satellite node can be placed, and selecting the next placement position and the content with the highest popularity in the placed content ordered set; if the first judgment result shows that the placement space of the content with the highest popularity in the placed content ordered set is larger than the remaining cache space of the selected content placeable satellite node, selecting the next content with the minimum average response time delay to place the satellite node; and traversing all the contents in the placed content ordered set until the placement is finished.
Making N decision schemes according to the required cache space of each content in the placed content ordered set and the size of the residual cache space of each LEO satellite node; using formulas
Figure BDA0003139099920000131
Calculating the average response time delay under each decision scheme; where T is the average response delay under the decision scheme,
Figure BDA0003139099920000132
to place the ith content into the response delay of the placeable LEO satellite node for the ith content marked in the decision scheme,
Figure BDA0003139099920000133
required buffer space for ith content, vxThe bandwidth of the x-th communication link between the placeable LEO satellite node of the ith content and the content request point, n is the number of the communication links between the placeable LEO satellite node of the ith content and the content request point, tdFor propagation delay of inter-satellite links of LEO satellite nodes,
Figure BDA0003139099920000134
for the number of times the ith content was accessed,
Figure BDA0003139099920000135
requesting the response time of the ith content from the LEO satellite node for a user request point, wherein Y is the number of the selected contents in all content clusters in the area; and selecting the decision scheme with the minimum average response time delay for content placement.
The calculating an average response delay of each LEO satellite node in the LEO satellite node set according to the ith content in the placed content ordered set specifically includes: the making of N decision schemes according to the size of the required cache space of each content in the ordered set of placed contents and the remaining cache space of each LEO satellite node specifically includes: initializing i, and enabling i to be 1; determining LEO satellite nodes with the content capable of placing LEO satellite nodes and the residual cache space larger than the cache space required by the ith content in the ordered set of placed contents to form a set of LEO satellite nodes with the content capable of placing LEO satellite nodes; judging whether the LEO satellite node set capable of being placed in the content is empty or not to obtain a second judgment result; if the second judgment result shows that the content of the LEO satellite node set can be placed in the ordered set of the placement contents, selecting any LEO satellite node in the LEO satellite node set with the content capable of being placed, marking the LEO satellite node with the ith content capable of being placed as the LEO satellite node with the ith content, updating the residual cache space of the content capable of being placed in the LEO satellite node with the ith content, increasing the value of i by 1, and returning to the step of determining the LEO satellite node with the residual cache space of the content capable of being placed in the LEO satellite node larger than the cache space required by the ith content in the ordered set of the placement contents to form the LEO satellite node set with the content capable of being placed in the ordered set; and if the second judgment result shows that the content is in the ordered set, giving up the ith content, increasing the value of i by 1, returning to the step of determining the LEO satellite nodes with the residual cache space for placing the LEO satellite nodes larger than the cache space required by the ith content in the ordered set of the placed content to form a set of the LEO satellite nodes with the placeable content, and generating a decision scheme until the content in the ordered set of the placed content is traversed to be finished.
When the second judgment result shows that the LEO satellite nodes in the LEO satellite node set can be placed in the selected content before the change, and another LEO satellite node is selected as the marked LEO satellite node which can be placed, so that various decision schemes can be generated. And selecting the decision scheme with the minimum average response time delay from the multiple decision schemes for content placement.
Summarizing the selected contents in each content cluster to form a content set S to be placed in the current areaselect＝{s1,s2,···,sYThe number of selected contents in the whole areaFor the whole Y, the content sizes are respectively
Figure BDA0003139099920000141
The bandwidth of a communication link between a deployment point and a device access node is v1,v2,···,vnThen a single content siThe communication delay of the backhaul is:
Figure BDA0003139099920000142
wherein, tdRepresenting the propagation delay of the inter-satellite link.
Defining content s at a device access nodeiThe number of times of access is fsiThe device access node requesting content s from the point of deploymentiHas a response time of Tsi. If the content to be deployed exists in the current satellite network and the response time delay from the known equipment access node to the current cached content node is TcurThen the average response time from the device access node to the computing deployment point is:
Figure BDA0003139099920000143
where Y represents the number of contents in the list currently to be selected for execution. The response time of requesting the content i from the deployment point should be less than the response time delay of the existing nodes in the current network, otherwise the deployment action is meaningless. And the content request delay should not exceed the request tolerance time TtolAnd if the condition is not met, not deploying the content at the node. x is the number ofsiIndicating whether or not there is content s at the current deployment pointiIf the content s already existsiThen xsi1, otherwise xsi＝0，csiRepresents the content siSize of (C)remainRepresenting the amount of cache space remaining available in the deployment node, which is known since LEO nodes periodically upload node state information to the SDN controller. The objective function is that the average response time is required to be minimum, and the constraint conditions respectively represent the response time limit from the deployment point to the equipment access node and the cache space limit of the corresponding content category.
Cache content placement problem transferThe optimization problem of the minimum average response time delay of all the contents from the request point to the deployment point for acquiring the contents is solved. The problem can be regarded as a knapsack problem, and the number of the knapsack in each cluster is uncertain, and a placing constraint condition exists, so that the problem is complex. The knapsack problem is solved by a greedy algorithm within the limits of satellite computing capacity and decision time, and local optimization is searched for through multiple iterations, so that global optimization is solved. After the content is selected, the selected contents in each content cluster are collected to form a content set S to be placed in the current areaselect＝{s1,s2,···,sYRanking the elements in the set again according to popularity to obtain an ordered set
Figure BDA0003139099920000151
Then taking the average time delay of the placement as an optimization target, and selecting the ordered set each time
Figure BDA0003139099920000152
And (4) calculating the average response time delay of the content placed in the available nodes under the limitation of the cache space, and selecting the placement method with the lowest average response time delay. And continuously iterating to obtain a local optimal solution to complete the placement of a video. Thereafter, from the ordered collection
Figure BDA0003139099920000153
And selecting the next content with the highest popularity and repeating the placing action, wherein when the residual cache space is not enough for storing the new content, the cache placing action is terminated.
The method can delay the cache in the information center network to be placed in the low orbit satellite, and realizes the quick response of the user content request. Compared with the traditional method for acquiring data from the source data center, the method has the advantages that the response time of requesting the content can be shortened, and meanwhile, the hit rate of the content is improved.
Under an SDN-based satellite network architecture, an SDN controller is placed on a GEO satellite. The LEO satellite nodes can sense local cache contents and upload cache updates to the SDN nodes in time. And meanwhile, the link state of the whole LEO satellite constellation can be acquired through the SDN controller.
Fig. 3 is a graph illustrating the average response delay of fig. 4 for requesting the full network content from the virtual node under four different caching policies. With the Zipf parameter set to 0.8. It can be seen that the average response delay of the regional user interest perception cache placement algorithm (RUIPM) provided by the invention is lower than that of the other three cache placement strategies. And when the cache space is small, the response time delay of the four strategies is higher than that of the cache space. The reason is that when the cache space cannot meet the requirement, the cache content needs to be placed in a node farther away from the virtual node, and the response time of the content is increased.
Fig. 4 is a comparison graph of cache hit rates of four caches in different cache spaces. The RUIPM algorithm provided by the invention has great advantages in optimizing the cache hit rate of the whole network, and the reason is that the algorithm divides the cache space according to the interest degree on the basis of sensing the interest of users in the region, and gives consideration to the cache of cold content on the basis of ensuring the cache of hot popular content, thereby ensuring the high cache hit rate. And the cache hit rate is continuously improved along with the increase of the cache capacity, and the hit rate gradually becomes stable after the cache capacity exceeds 300 MB. This means that after the cache capacity is larger than 300MB, most of the content requested by the user is cached in the network.
Fig. 5 is a comparison diagram of the cache hit rate influenced by the number of base stations in an area, and since a plurality of ground communication base stations exist in the coverage area of a single satellite and the area mentioned in the present invention is a concept defined by human, the number of base stations in the area is not fixed. There is also a large difference in user interests from base station to base station. Therefore, the influence of the number of base stations in the comparison area on the cache hit rate is compared. It can be seen from the comparison graph that the cache hit rate mainly depends on the size of the cache space under the same number of base stations. Under the condition of the same cache space, the cache hit rate is gradually reduced along with the increase of the number of the base stations, because the user interests of the base stations are different from those of the base stations, the content cached in the whole network cannot meet the user needs of all the base stations. And in the case of a cache space of 50MB, the hit rate performance of the cache is the worst, because most of the department content cannot be cached in the network when the cache space cannot meet the system requirements at all. And when the cache space is 300MB, most of the whole network content library is cached in the network, so that the cache hit rate is hardly influenced by the number of the base stations.
Fig. 6 is a graph of fixing the buffer capacity to 300MB to compare the change of the Zipf parameter in the four buffer strategies with the change of the overall network average response delay. It can be seen that the performance of the RUIPM algorithm proposed by the present invention is more stable, the average response time delay of the content gradually decreases as the Zipf parameter becomes larger, because the increase of the Zipf parameter indicates that the user requests gradually several to fewer contents, and when the parameter is between 1-1.5, the types of the contents cached in the whole network become less, and the contents are the most popular contents. This is the same idea as the criminal cache placement strategy, so the strategy can bring better response delay. The algorithm adopts a greedy algorithm to optimize the response time delay of the placement position, and because the theme interest division thought is adopted, part of unhealthy contents are cached, the department contents occupy the optimal placement position of the unhealthy contents, and the time delay performance of the algorithm is slightly higher than the most popular cache strategy when the Zipf parameter is between 1 and 1.5. In addition, the random placement strategy decides whether to cache the content with random probability, and the algorithm makes the hot content not be cached sufficiently, so the time delay performance is poor.
The invention provides a LEO satellite network cache placement strategy (RUIPM) based on regional interest perception. The invention designs a low orbit satellite network cache placement method under the ICN-based communication mode. And taking the label of the content as the distance measurement of the content similarity, and dividing the whole network content into a plurality of content clusters through a clustering algorithm. And evaluating the interest preference of the regional users to each content cluster by using historical request data, and dividing the cache space of the whole network content according to preference weight. And defining the placement problem of the content by taking the average time delay as an optimization target, and solving the placement problem by adopting a greedy algorithm. Simulation results show that the method provided by the invention is superior to a comparison method in the aspects of content response delay and cache hit rate, not only reduces the content response delay, but also considers the distribution balance of the content.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.
The principle and the implementation mode of the invention are explained by applying a specific example, and the description of the embodiment is only used for helping to understand the method and the core idea of the invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.

Claims (9)

1. A satellite network cache placement method based on regional user interest perception is characterized by comprising the following steps:
extracting request logs of all base stations in an area and establishing a whole network content library set in the area;
acquiring state information of a LEO satellite node, wherein the state information comprises: inter-satellite link bandwidth information of the LEO satellite and space capacity information of the LEO satellite;
establishing an LEO satellite node set as a cache space according to the state information of the LEO satellite nodes;
calculating the label similarity of the contents in the content library set;
clustering the content in the content library set into a plurality of content clusters according to the content label similarity;
calculating the interest degree of the users in the area to each content cluster;
dividing a cache subspace of each content cluster in the cache space according to the interestingness of the content cluster;
determining the popularity of the content in each of the content clusters;
determining the number of the selected contents in each content cluster according to the popularity and the cache subspace;
placing selected ones of the plurality of content clusters into a content collection;
ranking all the placing contents according to the popularity of each placing content in the placing content set to obtain a placing content ordered set;
and sequentially placing the contents in the placed content ordered set into the LEO satellite node according to the state information of the LEO satellite node according to the scheme with the shortest placing time.
2. The method for placing the satellite network cache based on the regional user interest perception according to claim 1, wherein the calculating the tag similarity of the content in the content library set specifically includes:
using formulas
Figure FDA0003139099910000021
Calculating the label similarity of the contents in the content library set; wherein, Sim(s)a,sb) Is the label similarity of content a and content b, saIs content a, sbIs content b, ljFor the jth tag, the number of tags,
Figure FDA0003139099910000022
the weight of the jth label in content a,
Figure FDA0003139099910000023
is the weight of the jth label in the content b, and m is the total number of labels.
3. The method for placing the satellite network cache based on the regional user interest perception according to claim 1, wherein the calculating the interest degree of the users in the region in each content cluster specifically includes:
using formulas
Figure FDA0003139099910000024
Calculating the interest degree of the users in the region to each content cluster; wherein,
Figure FDA0003139099910000025
the interest degree of the users in the area to the g-th content cluster, q is the number of base stations in the area, u1、u2And uqThe number of users under the first base station, the second base station and the q-th base station respectively, omega is the total number of users in the area,
Figure FDA0003139099910000026
and
Figure FDA0003139099910000027
respectively short-term interest degrees of users under a first base station, a second base station and a q-th base station in the area in the g-th content cluster,
Figure FDA0003139099910000028
wherein (t)0,t1)、(t1,t2) And (t)n-1,tn) First, second and nth statistical time periods respectively,
Figure FDA0003139099910000029
for the short-term interest of users under the z-th base station in the area in the g-th content cluster,
Figure FDA00031390999100000210
and
Figure FDA00031390999100000211
respectively the number of times of requests of the user to the g-th content cluster in the first statistical time period, the second statistical time period and the n-th statistical time period under the z-th base station,
Figure FDA00031390999100000212
and
Figure FDA00031390999100000213
the number of requests for all content clusters in the first, second and nth statistical time periods for the user under the z-th base station respectively.
4. The satellite network cache placement method based on regional user interest perception according to claim 1, wherein the dividing of the cache subspace of each content cluster in the cache space according to the interest degree of the content cluster specifically comprises:
using formulas
Figure FDA00031390999100000214
Determining a cache subspace of a single content cluster; wherein, CgThe cache subspace for the g-th content cluster,
Figure FDA00031390999100000215
the interest degree of the users in the area to the g-th content cluster, C is the total cache space, and d is the number of the content clusters.
5. The method for placing the satellite network cache based on the regional user interest perception according to claim 1, wherein the determining the popularity of the content in each content cluster specifically includes:
using formulas
Figure FDA0003139099910000031
Determining the popularity of the content in each of the content clusters; wherein k is the popularity ranking of the whole network content, s is the content name,
Figure FDA0003139099910000032
and for the popularity of the content i in each content cluster, alpha is a parameter of Zipf distribution, and N is the total number of the content in the whole network.
6. The satellite network cache placement method based on regional user interest perception according to claim 1, wherein the determining the number of the selected contents in each content cluster according to the popularity and the cache subspace specifically includes:
using formulas
Figure FDA0003139099910000033
Calculating the number of the selected contents in the g-th content cluster; wherein w is the number of contents selected in the content cluster,
Figure FDA0003139099910000034
for caching subspaces for the presence of content si，
Figure FDA0003139099910000035
Is a content siC is the ratio space ofgIs the cache subspace of the g-th content cluster.
7. The method for placing the satellite network cache based on the interest perception of the regional user according to claim 1, wherein the sequentially placing the contents in the ordered set of placed contents into the LEO satellite node according to the scheme that the placing time is the shortest according to the state information of the LEO satellite node specifically comprises:
initializing i, and enabling i to be 1;
calculating the average response time delay of each LEO satellite node in the LEO satellite node set according to the ith content in the placed content ordered set;
sequencing all LEO satellite nodes according to the ascending order of the average response time delay, initializing h, and enabling h to be 1;
judging whether the space of the ith content in the ordered set of the placed contents is larger than the remaining cache space of the selected h-th LEO satellite node or not to obtain a first judgment result;
if the first judgment result shows that the content is the h-th content, increasing the value of the h by 1, and returning to the step of judging whether the space for placing the ith content in the ordered set of contents is larger than the residual cache space of the selected h-th LEO satellite node to obtain a first judgment result;
and if the first judgment result shows that the content is not the h-th LEO satellite node, sending the ith content to the h-th LEO satellite node, increasing the value of i by 1, and returning to the step of calculating the average response time delay of each LEO satellite node in the LEO satellite node set according to the ith content in the placed content ordered set until all the content in the placed content ordered set is traversed.
8. The method for placing the satellite network cache based on regional user interest perception according to claim 7, wherein the calculating an average response delay of each LEO satellite node in the LEO satellite node set according to an ith content in the placed content ordered set specifically includes:
making N decision schemes according to the required cache space of each content in the placed content ordered set and the size of the residual cache space of each LEO satellite node;
using formulas
Figure FDA0003139099910000041
Calculating the average response time delay under each decision scheme; where T is the average response delay under the decision scheme,
Figure FDA0003139099910000042
Figure FDA0003139099910000043
to place the ith content into the response delay of the placeable LEO satellite node for the ith content marked in the decision scheme,
Figure FDA0003139099910000044
required buffer space for ith content, vxThe bandwidth of the x-th communication link between the placeable LEO satellite node of the ith content and the content request point, and n is the number of the communication links between the placeable LEO satellite node of the ith content and the content request point，tdFor propagation delay of inter-satellite links of LEO satellite nodes,
Figure FDA0003139099910000045
for the number of times the ith content was accessed,
Figure FDA0003139099910000046
requesting the response time of the ith content from the LEO satellite node for a user request point, wherein Y is the number of the selected contents in all content clusters in the area;
and selecting the decision scheme with the minimum average response time delay for content placement.
9. The satellite network cache placement method based on regional user interest perception according to claim 8, wherein the making of N decision schemes according to the required cache space of each content in the placed content ordered set and the size of the remaining cache space of each LEO satellite node specifically comprises:
initializing i, and enabling i to be 1;
determining LEO satellite nodes with the content capable of placing LEO satellite nodes and the residual cache space larger than the cache space required by the ith content in the ordered set of placed contents to form a set of LEO satellite nodes with the content capable of placing LEO satellite nodes;
judging whether the LEO satellite node set capable of being placed in the content is empty or not to obtain a second judgment result;
if the second judgment result shows that the content of the LEO satellite node set can be placed in the ordered set of the placement contents, selecting any LEO satellite node in the LEO satellite node set with the content capable of being placed, marking the LEO satellite node with the ith content capable of being placed as the LEO satellite node with the ith content, updating the residual cache space of the content capable of being placed in the LEO satellite node with the ith content, increasing the value of i by 1, and returning to the step of determining the LEO satellite node with the residual cache space of the content capable of being placed in the LEO satellite node larger than the cache space required by the ith content in the ordered set of the placement contents to form the LEO satellite node set with the content capable of being placed in the ordered set;
and if the second judgment result shows that the content is in the ordered set, giving up the ith content, increasing the value of i by 1, returning to the step of determining the LEO satellite nodes with the residual cache space for placing the LEO satellite nodes larger than the cache space required by the ith content in the ordered set of the placed content to form a set of the LEO satellite nodes with the placeable content, and generating a decision scheme until the content in the ordered set of the placed content is traversed to be finished.
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