CN110062421B - Pigeon group optimization algorithm for fog wireless access network and cooperation caching method based on algorithm - Google Patents
Pigeon group optimization algorithm for fog wireless access network and cooperation caching method based on algorithm Download PDFInfo
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Abstract
The invention discloses a pigeon group optimization algorithm used in a fog wireless access network and a cooperative caching method based on the algorithm, which comprises the following steps: (1) dividing fog wireless access nodes in a fog wireless access network into a plurality of clusters; (2) specifying a route for forwarding a file request of a user in a network; (3) the fog wireless access point calculates the local popularity of each file according to the number of received file requests, and finally, an improved pigeon group optimization algorithm is adopted to solve the optimal cache distribution in the fog wireless access point cluster; (4) the cluster head adopts an improved pigeon group optimization algorithm to solve a cooperation strategy in the fog wireless access node cluster through the received file request and the in-cluster cache table; the invention can effectively reduce the average downloading time delay of the network.
Description
Technical Field
The invention relates to a content caching technology, in particular to a pigeon swarm optimization algorithm used in a fog wireless access network and a cooperative caching method based on the algorithm.
Background
At present, in order to reduce the load of a backhaul link in a network, people mainly focus on research on cache arrangement in a wireless communication system under the existing architectures such as a cloud wireless access network, and most of the research does not consider cooperation between base stations.
However, the existing communication network architecture does not meet the requirement of 5G/B5G communication, and with the arrival of the 5G/B5G era, the number of files in the network is greatly increased, and the average download delay of the files in the network is also greatly increased. Therefore, finding a low-latency cache arrangement strategy suitable for the 5G/B5G network architecture is an urgent problem to be solved.
Disclosure of Invention
The purpose of the invention is as follows: aiming at the problems in the prior art, the invention provides a pigeon flock optimization algorithm used in a fog wireless access network and a cooperative caching method based on the algorithm.
The technical scheme adopted by the invention is as follows: a pigeon flock optimization algorithm for a fog wireless access network is characterized in that on the basis of a traditional pigeon flock optimization algorithm, Cauchy disturbance is applied to an optimal solution in each iteration:
Xg′＝Xg+C(x0,γ)·(ub-lb). (1)
in the formula, XgRepresenting the optimal solution in the current iteration, ub and lb respectively representing the upper and lower bounds of the solution space of the solution problem, Xg' denotes a perturbed global optimum solution, C (x)0γ) represents a random number generated from a Cauchy distribution density function as follows:
wherein x0And γ is a parameter.
Further, a compass factor R which changes adaptively is introduced:
where t denotes the current number of iterations, Nc1，Nc2Representing the maximum number of iterations for the map and compass operators and the landmark operator, respectively, and alpha is a constant used to determine the minimum value of R.
The invention also discloses a cooperative caching method for the fog wireless access network based on the improved pigeon swarm optimization algorithm, which comprises the following steps:
s1: the method comprises the following steps that fog wireless access nodes in a fog wireless access network are divided into a plurality of clusters, each cluster comprises a plurality of fog wireless access nodes, one fog wireless access node is arranged in each cluster and serves as a cluster head, the fog wireless access nodes are communicated with other fog wireless access nodes, and a corresponding in-cluster cache table is arranged in each cluster head;
s2: when a route forwarded by a file request of a user in a network is specified, if a local fog wireless access node is not hit, the file request is forwarded to a cluster head of the cluster, and if the local fog wireless access node is hit, a requested file is directly sent;
s3: the fog wireless access point calculates the local popularity of each file according to the number of received file requests, and the optimal cache distribution in the fog wireless access point cluster is solved by adopting a pigeon group optimization algorithm;
s4: and the cluster head adopts a pigeon group optimization algorithm to solve the cooperation strategy in the fog wireless access node cluster through the received file request and the in-cluster cache table.
Further, in S1, the fog wireless access points in the same cluster are connected by a control link, the fog wireless access points in different clusters do not communicate with each other, and the user accesses the cluster head or other fog wireless access points in the fog wireless access point cluster according to the geographic location.
Further, the specification of the route in S2 is specifically: sending a file request of a user to a local fog wireless access point, and checking whether a requested file is cached locally or not when the local fog wireless access point receives the file request; if the file is cached, the requested file is directly sent; if the cache does not exist, forwarding the file request to a cluster head; when a cluster head receives file requests from other fog wireless access points in a cluster, checking whether a requested file exists in a locally stored in-cluster cache table; if yes, the fog wireless access point caching the requested file in the control cluster cooperates with the requested local fog wireless access point to send the requested file; and if not, controlling the requested fog wireless access node to directly download the file from the cloud.
Further, the method for calculating the local popularity of the file in S3 includes: calculating the normalized local popularity of each fog wireless access point through the received file request:
wherein, tnmFor nth file in fog wireless access node amNumber of applications of (a)mIndicating that the fog wireless access node is the mth fog wireless access point in the cluster, and N is the total number of the request files.
Further, in S3, the caching policy in one cluster is represented by a caching policy matrix; according to the local popularity of the file and the cache capacity of each fog wireless access point, the minimum download delay is taken as an optimization target, the cache capacity is taken as a constraint condition, the size of a solution space is the cache capacity of the fog wireless access point, the optimization target is a cache strategy matrix, the intra-cluster cache arrangement problem is expressed as an integer linear programming problem, and the integer look-ahead programming problem is solved by using a pigeon group optimization algorithm.
Further, in S4, the cooperation relationship of different fog wireless access nodes in the cluster is represented by a cooperation relationship matrix; according to the local popularity of the file, the cache capacity of each fog wireless access point and the route of file request forwarding, expressing the in-cluster cache cooperation problem as an integer linear programming problem, taking the minimized download delay as an optimization target, taking the cache capacity as a constraint condition, taking an optimized object as a cooperation relation matrix, and solving the integer linear programming problem by using a pigeon group optimization algorithm.
Has the advantages that: the invention has the following advantages:
(1) the invention realizes the cooperative caching in the cluster by dividing the fog wireless access nodes in the fog network into the clusters, can effectively improve the caching cooperation degree in the network and reduce the load of a backward transmission link of the network.
(2) The users covered by a single fog wireless access node are few, and the received file request has difficulty in revealing the aggregation effect of the files. The fog wireless access nodes are properly clustered, and the local popularity of the file can be more accurately estimated through more file requests
(3) The cooperative caching strategy can be obtained on each fog wireless access node in a distributed manner in a cluster;
(4) the invention adopts an innovative improved pigeon group optimization algorithm, and compared with the traditional greedy algorithm, the invention obviously reduces the calculation complexity and is more suitable for the fog wireless access network. Compared with the traditional group intelligent algorithm, the global search capability is obviously improved, and the local optimum and premature convergence are effectively avoided.
Drawings
FIG. 1 is a schematic diagram of a mist net cache arrangement according to the present invention;
FIG. 2 is a graph comparing the performance of the present invention with centralized caching and distributed caching based on a belief propagation algorithm in an embodiment;
fig. 3 is a comparison graph of download delays and iteration times of different misty wireless access nodes in the same cluster in the embodiment.
Detailed Description
The invention is further illustrated below with reference to the figures and examples.
The embodiment provides a cooperative caching method for a fog wireless access network, which comprises the following steps:
s1: dividing fog wireless access nodes in a fog wireless access network into a plurality of clusters; as shown in fig. 1, each cluster includes a plurality of fog wireless access nodes, and one fog wireless access node in each cluster is used as a cluster head and is connected with other fog wireless access nodes through control links; fog wireless access points in the same cluster are communicated with each other, fog wireless access points in different clusters are not communicated with each other, and a user directly accesses to a cluster head or other fog wireless access points in the fog wireless access point cluster according to the geographic position.
S2: a route is defined by which a user's file request is forwarded in the network.
Sending a file request of a user to a local fog wireless access point;
when a local fog wireless access point receives a file request, checking whether a requested file is cached locally; if the file is cached, the requested file is directly sent; if the cache does not exist, forwarding the file request to a cluster head;
when a cluster head receives file requests from other fog wireless access points in a cluster, checking whether a requested file exists in a cluster cache file list stored locally; if yes, the fog wireless access point which caches the requested file in the control cluster and the requested local fog wireless access point cooperate to send the requested file; if not, controlling the requested fog wireless access node to directly download the file from the cloud;
s3: the fog wireless access point calculates the local popularity of each file according to the number of received file requests, and an improved pigeon group optimization algorithm is adopted to solve the optimal cache distribution in the fog wireless access point cluster: expressing the caching strategy in one cluster by a caching strategy matrix; according to the local popularity of the file and the cache capacity of each fog wireless access point, taking the minimum download delay as an optimization target, taking the cache capacity as a constraint condition, taking the size of a solution space as the cache capacity of the fog wireless access point, taking the optimization target as a cache strategy matrix, representing the intra-cluster cache arrangement problem as an integer linear programming problem, and solving the integer look-ahead programming problem by using a pigeon group optimization algorithm;
the method for calculating the local popularity of the file comprises the following steps:
each fog wireless access point calculates the normalized local popularity of the file through the received file request:
wherein, tnmFor the nth file fnIn fog wireless access node amNumber of applications of (a)mIndicating that the fog wireless access node is the mth fog wireless access point in the cluster, wherein N is the total number of the request files;
compared with the traditional pigeon breeding optimization algorithm, the improved pigeon breeding optimization algorithm specifically comprises two improvements:
1. applying Cauchy perturbation to optimal solution in each iteration
Xg′＝Xg+C(x0,γ)·(ub-lb). (1)
In the formula, XgRepresenting the optimal solution in the current iteration, ub and lb respectively representing the upper and lower bounds of the solution space of the solution problem, Xg' represents the perturbed global optimal solution. C (x)0γ) represents a random number generated from a Cauchy distribution density function as follows:
wherein x0And γ is a parameter.
2. Compass factor R with adaptive variation
Where t denotes the current number of iterations, Nc1，Nc2Representing the maximum number of iterations for the map and compass operators and the landmark operator, respectively, and alpha is a constant used to determine the minimum value of R.
S4: the cluster head adopts an improved pigeon group optimization algorithm to solve the cooperation strategy in the fog wireless access node cluster through the received file request and the in-cluster cache table: expressing the cooperative relationship of different fog wireless access nodes in the cluster by using a cooperative relationship matrix; according to the local popularity of the file, the cache capacity of each fog wireless access point and the route of file request forwarding, expressing the in-cluster cache cooperation problem as an integer linear programming problem, taking the minimized download delay as an optimization target, taking the cache capacity as a constraint condition, taking an optimized object as a cooperation relation matrix, and solving the integer linear programming problem by using a pigeon group optimization algorithm;
s5: when the user interest changes, repeating S3-S4, and obtaining a new cache distribution.
For the simulation verification of the present embodiment, as shown in fig. 2, the embodiment studies the relationship between the network cache capacity and the network average download delay, and takes the total network cache capacity as 0.1 and 0.15 … 0.5.5 of the total file size, respectively, to make the relationship between the total cache capacity and the network average download delay. It can be seen that in the algorithm, for all different cache capacities, the average download delay of the network is very close to the optimal solution obtained by the centralized algorithm, and compared with the distributed cache algorithm based on confidence propagation, the average download delay of the network is obviously reduced.
The embodiment also researches the relationship between the download delay and the iteration times of different fog wireless access nodes in the same cluster in the cooperative mode and the non-cooperative mode, as shown in fig. 3. The average downloading time delay of the iteration times of the three fog wireless access nodes in the same cluster from 0 to 120 in a cooperative mode and a non-cooperative mode is respectively researched, and the relation between the downloading time delay and the iteration times is made. It can be seen that the average download delay in the cooperative mode is significantly lower than that in the non-cooperative mode, mainly because when the local request in the cooperative mode is not satisfied, the file can be downloaded from other misty wireless access nodes in the cluster through cooperation. Meanwhile, the download delay convergence in the cooperative mode is slower than that in the non-cooperative mode, that is, the calculation complexity is higher, mainly because the local popularity of the file changes once after each cooperation, and therefore more calculation is needed to achieve convergence. However, under the two modes, the algorithm can achieve convergence within 50 times, which shows that the invention has very low computational complexity and is very suitable for a 5G/B5G network.
Claims (4)
1. A cooperative caching method for a fog wireless access network is characterized in that: the method comprises the following steps:
s1: the method comprises the following steps that fog wireless access nodes in a fog wireless access network are divided into a plurality of clusters, each cluster comprises a plurality of fog wireless access nodes, one fog wireless access node is arranged in each cluster and serves as a cluster head, the fog wireless access nodes are communicated with other fog wireless access nodes, and a corresponding in-cluster cache table is arranged in each cluster head;
s2: when a route forwarded by a file request of a user in a network is specified, if a local fog wireless access node is not hit, the file request is forwarded to a cluster head of the cluster, and if the local fog wireless access node is hit, a requested file is directly sent;
s3: the fog wireless access point calculates the local popularity of each file according to the number of received file requests, and a caching strategy in one cluster is expressed by a caching strategy matrix; according to the local popularity of the file and the cache capacity of each fog wireless access point, taking the minimum download delay as an optimization target, taking the cache capacity as a constraint condition, solving the size of a space as the cache capacity of the fog wireless access point, taking the optimization target as a cache strategy matrix, representing the in-cluster cache arrangement problem as an integer linear programming problem, and solving the integer look-ahead programming problem by adopting a pigeon group optimization algorithm to obtain the optimal cache distribution in the fog wireless access point cluster;
s4: the cluster head represents the cooperation relation of different fog wireless access nodes in the cluster by a cooperation relation matrix through the received file request and a cluster cache table; according to the local popularity of the file, the cache capacity of each fog wireless access point and the route of file request forwarding, expressing the in-cluster cache cooperation problem as an integer linear programming problem, taking the minimized download delay as an optimization target, taking the cache capacity as a constraint condition and taking an optimized object as a cooperation relation matrix, and solving the integer linear programming problem by using a pigeon group optimization algorithm to obtain a cooperation strategy in the fog wireless access node cluster;
s5: when the user interest changes, repeating S3-S4 to obtain new cache distribution;
the pigeon swarm optimization algorithm is characterized in that Cauchy disturbance is applied to the optimal solution in each iteration on the basis of the traditional pigeon swarm optimization algorithm:
Xg'＝Xg+C(x0,γ)·(ub-lb). (1)
in the formula, XgRepresenting the optimal solution in the current iteration, ub and lb respectively representing the upper and lower bounds of the solution space of the solution problem, Xg' denotes a perturbed global optimum solution, C (x)0γ) represents a random number generated from a Cauchy distribution density function as follows:
wherein x0And gamma is a parameter;
and introducing a compass factor R which changes adaptively:
where t denotes the current number of iterations, Nc1，Nc2Representing the maximum number of iterations for the map and compass operators and the landmark operator, respectively, and alpha is a constant used to determine the minimum value of R.
2. The cooperative buffering method for the fog radio access network as claimed in claim 1, wherein: in S1, the fog wireless access points in the same cluster are connected through a control link, the fog wireless access points in different clusters are not communicated with each other, and a user accesses to a cluster head or other fog wireless access points in the fog wireless access point cluster according to the geographic position.
3. The cooperative buffering method for the fog radio access network as claimed in claim 1, wherein: the route specification in S2 is specifically: sending a file request of a user to a local fog wireless access point, and checking whether a requested file is cached locally or not when the local fog wireless access point receives the file request; if the file is cached, the requested file is directly sent; if the cache does not exist, forwarding the file request to a cluster head; when a cluster head receives file requests from other fog wireless access points in a cluster, checking whether a requested file exists in a locally stored in-cluster cache table; if yes, the fog wireless access point which caches the requested file in the control cluster and the requested local fog wireless access point cooperate to send the requested file; and if not, controlling the requested fog wireless access node to directly download the file from the cloud.
4. The cooperative buffering method for the fog radio access network as claimed in claim 1, wherein: the method for calculating the local popularity of the file in the S3 comprises the following steps: calculating the normalized local popularity of each fog wireless access point through the received file request:
wherein, tnmFor nth file in fog wireless access node amNumber of applications of (a)mIndicating that the fog wireless access node is the mth fog wireless access point in the cluster, and N is the total number of the request files.
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| CN111314960B (en) * | 2020-02-19 | 2023-04-07 | 东南大学 | Social awareness-based collaborative caching method in fog wireless access network |
| CN111935783A (en) * | 2020-07-09 | 2020-11-13 | 华中科技大学 | Edge cache system and method based on flow perception |
| CN111970717B (en) * | 2020-08-07 | 2022-11-25 | 杭州电子科技大学 | Method for content caching and user-base station association in fog-based wireless access network |
| CN112073275B (en) * | 2020-09-08 | 2022-06-21 | 广西民族大学 | Content distribution method and device for ultra-dense network UDN |
| CN112738263B (en) * | 2020-12-31 | 2022-06-14 | 杭州电子科技大学 | Genetic algorithm-based Fog-RAN network cache placement problem decision method |
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