Cloud-edge collaborative 5g networking multi-hop forwarding path dynamic processing method and storage medium

Abstract

The application discloses a cloud-edge coordination 5G networking multi-hop forwarding path dynamic processing method and a storage medium. The ant algorithm is used to optimize the forwarding lines between data base stations, so that the data transmission efficiency of the whole network is improved, and the data transmission delay is reduced. While ensuring the service quality, unnecessary data transmission distance and transfer are reduced, so that the operation and maintenance cost can be effectively reduced. The technical scheme adopted by the above embodiment of the application automatically optimizes path selection through an algorithm, and has good scalability and flexibility.

Description

Technical Field

[0001] This invention relates to the field of data transmission, and in particular to a method and storage medium for dynamic processing of multi-hop forwarding paths in 5G networking under cloud-edge collaboration. Background Technology

[0002] "Multi-hop" refers to a communication method where data transmission from the sender to the receiver does not directly reach its final destination via a single wireless communication, but rather requires forwarding through one or more intermediate nodes (or relay nodes). This communication method is particularly suitable for situations where the distance between nodes is long or where obstacles prevent the signal from directly reaching the destination node. In multi-hop communication data transmission, intermediate nodes receive the data and then forward it until the data reaches the final destination node. Each forwarding is called a "hop". For example, if data is transmitted from node A to node D and needs to be forwarded through nodes B and C in sequence, it is called a three-hop communication path (A→B→C→D).

[0003] In 5G networks, multi-hop forwarding is typically used in the following scenarios: 1. In remote areas, mountainous regions, or underground buildings where signal coverage is difficult, relay nodes are used to forward signals via multiple hops, improving network coverage and quality. 2. In a cloud-edge collaborative architecture, data may be transmitted to the cloud through multiple edge nodes, or vice versa, from the cloud through multiple edge nodes to the terminal device. When terminal devices or nodes move, the network path may need to be dynamically adjusted to maintain stable data transmission and avoid connection interruptions or excessive latency. 5G networks are also composed of a large number of 5G communication data base stations (referred to as data base stations). In the traditional data forwarding process described above, there may be problems such as inefficient transmission paths and excessively long distances between data base stations, leading to low data forwarding efficiency. Therefore, data base stations need to forward data one by one according to their signal coverage area, so that the sending data base station forwards the data to the target data base station.

[0004] However, in real-world scenarios, there are many data base stations between the sending and receiving ends. Due to the limited signal coverage of these base stations, the data information needs to be repeatedly forwarded among them before reaching the final target base station. This results in significant data forwarding latency. Therefore, ensuring that data can be transmitted quickly and with minimal latency when multiple data base stations are involved is a pressing problem that needs to be solved. Summary of the Invention

[0005] The purpose of this invention is to provide a dynamic processing method and storage medium for multi-hop forwarding paths in 5G networking under cloud-edge collaboration, which solves the above-mentioned technical problems pointed out in the prior art.

[0006] This invention provides a method for dynamically processing multi-hop forwarding paths in 5G networking under cloud-edge collaboration, comprising the following steps:

[0007] Obtain the data base station set for the current area; and obtain the transmitting data base station and the target data base station in the data base station set; obtain the signal coverage range of each data base station in the data base station set;

[0008] Based on the coordinate information of each data base station and the signal coverage area, the forwarding lines between each pair of data base stations and the line distance of each forwarding line are obtained.

[0009] Based on the forwarding route, the ant colony algorithm is used to iteratively traverse each of the data base stations in the data base station set to obtain the optimal data forwarding route from the sending data base station to the target data base station.

[0010] Preferably, based on the forwarding route, the optimal data forwarding route from the sending data base station to the target data base station is obtained by iteratively traversing each data base station in the data base station set using the ant colony algorithm, including the following steps:

[0011] Set the maximum number of iterations y and the iteration counter; wherein the iteration counter is initially set to 0.

[0012] Starting from the transmitting data base station, the initial position of each ant is obtained according to the signal coverage range of the transmitting data base station; a taboo position table is established for each ant in each iteration, and the coordinate information of the transmitting data base station and the initial position are added to the taboo position table in each iteration; the first forwarding data base station is a data base station within the signal coverage range of the transmitting data base station;

[0013] The second forwarding data base station for each of the ants is determined based on the line distance;

[0014] Repeat the above operations and update the taboo position table in each iteration;

[0015] The target route is obtained by analyzing the forbidden position table and the iteration counter in each iteration.

[0016] Preferably, the step of obtaining the target route by judging and analyzing the taboo position table and the number of iterations in each iteration includes the following steps:

[0017] Determine whether the target data base station is included in the taboo location table in each iteration; if so, establish a set of routes for each iteration; arrange each data base station in the taboo location table in each iteration in sequence to obtain the route of the current ant in this iteration, and calculate and obtain the distance and the number of data base stations of the route of the current ant in this iteration;

[0018] The current ant's current iteration route is added to the iteration route set; otherwise, the current ant continues to traverse the data base station until the target data base station is included in the taboo location table in each iteration.

[0019] Further determine whether each ant has obtained the current ant's current iteration path; if so, obtain the current ant's current iteration path with the shortest distance from each current iteration path set as the candidate target path; add the candidate target path to the candidate target path set; and increment the iteration count of the iteration counter by 1.

[0020] Determine whether the number of iterations is greater than or equal to the maximum number of iterations y; if yes, then select the current ant's current iteration route with the shortest distance from the current ant's current iteration route in the candidate target route set as the target route; if no, return to the above operation until the number of iterations is greater than or equal to the maximum number of iterations y, and output the target route.

[0021] Preferably, the initial position of each ant is obtained according to the signal coverage range of the transmitting data base station, including obtaining the coordinate information of the first forwarding data base station and the first forwarding data base station according to the signal coverage range of the transmitting data base station; and randomly placing each ant at the position corresponding to the coordinate information of each of the first forwarding data base stations as the initial position of each ant.

[0022] Preferably, determining the second forwarding data base station for each of the ants based on the line distance includes the following steps:

[0023] Obtain the set P of candidate second forwarding data base stations for each of the ants. ij ={p i1 p i2 p i3 ...p ij}; where p ij It is the j-th candidate second forwarding data base station for the i-th ant;

[0024] Obtain the subsequent forwarding data base station q corresponding to each of the candidate second forwarding data base stations; count the number n of subsequent forwarding data base stations for each of the candidate second forwarding data base stations;

[0025] Obtain the line distance m from the first forwarding data base station to each candidate second forwarding data base station in the forwarding lines of each of the ants;

[0026] Construct a data forwarding matrix R based on the set of candidate second forwarding data base stations and the line distance m;

[0027] The fitness f of each candidate second forwarding data base station is calculated based on the data forwarding matrix and the number n of subsequent forwarding data base stations.

[0028] The target second forwarding data base station is obtained based on the fitness f;

[0029] Preferably, the target second forwarding data base station is obtained by selecting the candidate second forwarding data base station with the highest fitness as the target second forwarding data base station based on the fitness f.

[0030] Preferably, the fitness f is calculated as follows:

[0031] ;

[0032] In the formula, n is the number of subsequent forwarding data base stations of the second forwarding data base station; Let i' be the data forwarding matrix, i' be the total number of ants, and i be the i-th ant;

[0033] Preferably, obtaining the subsequent forwarding data base station q corresponding to each of the candidate second forwarding data base stations includes the following steps:

[0034] Traverse each of the candidate second forwarding data base stations, and obtain the set of third forwarding data base stations K={k1, k2, k3, ...kt} of the candidate second forwarding data base stations according to the signal coverage range of the second forwarding data base stations; kt is the t-th third forwarding data base station of the second forwarding data base station;

[0035] Based on the forwarding lines from the second forwarding data base station to each of the third forwarding data base stations and the distances of those lines, the shortest distance d is obtained by filtering.

[0036] The distance difference matching degree f' of each of the third forwarding data base stations is calculated based on the shortest distance d and the set of third forwarding data base stations;

[0037] Based on the distance difference matching degree f' of each of the third forwarding data base stations, the target third forwarding data base station corresponding to the second forwarding data base station is selected and obtained;

[0038] Repeat the above operation until all candidate second forwarding data base stations have been traversed to obtain the target third forwarding data base station corresponding to each candidate second forwarding data base station;

[0039] The target third forwarding data base station is used as a candidate second forwarding data base station, and the above operation is repeated to obtain a new target third forwarding data base station until it is finally added to the target data base station, thus obtaining the subsequent forwarding data base station corresponding to each candidate second forwarding data base station.

[0040] Preferably, the distance difference matching degree f' is calculated as follows:

[0041] ;

[0042] In the formula, di'' is the shortest distance from the i''th second forwarding data base station to the tth third forwarding data base station; Let t be the distance from the t-th third forwarding data base station to the second forwarding data base station; The distance between the third forwarding data base station and the second forwarding data base station is the average value; t is the t-th base station; T is the total number of third forwarding data base stations.

[0043] The present invention also provides a storage medium comprising a stored program, wherein, when the program is running, it controls the device where the storage medium is located to execute the above-described dynamic processing method for multi-hop forwarding paths in 5G networking under cloud-edge collaboration.

[0044] Compared with the prior art, the embodiments of the present invention have at least the following technical advantages:

[0045] Analysis of the above-mentioned dynamic processing method and storage medium for multi-hop forwarding paths in 5G networking under cloud-edge collaboration provided by the present invention shows that, in specific applications, the ant colony algorithm improves the data transmission efficiency of the entire network and reduces data transmission latency by optimizing the forwarding lines between data base stations. While ensuring service quality, it reduces unnecessary data transmission distances and relays, thereby effectively reducing operation and maintenance costs. The technical solution adopted in the above-mentioned embodiments of this application automatically optimizes path selection through algorithms, and has good scalability and flexibility. Attached Figure Description

[0046] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0047] Figure 1 This is a schematic diagram of the overall operation steps of a dynamic processing method for multi-hop forwarding paths in 5G networking under cloud-edge collaboration, provided by an embodiment of the present invention.

[0048] Figure 2 This is a schematic diagram of the data forwarding lines between data base stations in a dynamic processing method for multi-hop forwarding paths in 5G networking under cloud-edge collaboration provided in an embodiment of the present invention.

[0049] Figure 3 This is a schematic diagram illustrating the operation steps for obtaining the optimal data forwarding path in a dynamic processing method for multi-hop forwarding paths in 5G networking under cloud-edge collaboration, provided in an embodiment of the present invention.

[0050] Figure 4 This is a schematic diagram of the operation process for obtaining the optimal data forwarding path in a dynamic processing method for multi-hop forwarding paths in 5G networking under cloud-edge collaboration provided in an embodiment of the present invention;

[0051] Figure 5 This is a schematic diagram illustrating the operation steps for obtaining the second forwarding data base station in a cloud-edge collaborative 5G networking multi-hop forwarding path dynamic processing method provided in an embodiment of the present invention;

[0052] Figure 6 This is a schematic diagram simulating a data forwarding line in a dynamic processing method for multi-hop forwarding paths in 5G networking under cloud-edge collaboration, provided in an embodiment of the present invention.

[0053] Figure 7 This is a schematic diagram illustrating the operation steps of obtaining subsequent forwarding data base stations in a cloud-edge collaborative 5G networking multi-hop forwarding path dynamic processing method provided in an embodiment of the present invention. Detailed Implementation

[0054] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0055] The present invention will now be described in further detail with reference to specific embodiments and accompanying drawings.

[0056] Example 1

[0057] like Figure 1 As shown, correspondingly, this invention also proposes a dynamic processing method for multi-hop forwarding paths in 5G networking under cloud-edge collaboration, including the following operation steps:

[0058] Step S10: Obtain the data base station set for the current area; and obtain the transmitting data base station and the target data base station in the data base station set; obtain the signal coverage range of each data base station in the data base station set;

[0059] It should be noted that, due to the signal coverage of each data base station in the aforementioned data base station set, data forwarding during the data forwarding process can proceed gradually from the sending data base station through interconnected data base stations, or by forwarding data within the coverage area of ​​the data base stations, ultimately delivering the forwarded data to the target data base station; however, cross-domain data forwarding is not permitted. For example: Figure 2 As shown, there are currently data base stations consisting of data base station ①, data base station ②, data base station ③, data base station ④, data base station ⑤, and data base station ⑥. Data base station ① is the transmitting data base station, and data base station ⑥ is the target data base station. Data is transmitted from data base station ①, and forwarded by data base stations ③, ④, and ⑤, ultimately reaching data base station ⑥. Each pair of adjacent data base stations is adjacent to each other. The signal coverage area of ​​each data base station is shown by the dotted line in the figure. Therefore, forwarded data can be forwarded from data base station ① to data base station ④, then to data base station ⑥; simultaneously, it can be forwarded from data base station ① to data base station ②, then to data base station ⑤, and finally from data base station ⑤ to data base station ⑥, and so on. Furthermore, during the data forwarding process, due to line limitations, data cannot be directly forwarded from data base station ① to data base station ⑤, nor can it be forwarded from data base station ① to data base station ⑥…

[0060] Step S20: Based on the coordinate information of each data base station and the signal coverage area, obtain the forwarding lines between every two data base stations and the line distance of each forwarding line.

[0061] It should be noted that the above-described embodiments of this application ensure that all data base stations that need to be considered are included in the calculation scope by obtaining the set of data base stations in the current area, and by obtaining the coordinate information of each data base station, a clear understanding of the location of the base station in geographic space can be obtained, laying the foundation for the optimal data forwarding route in the future.

[0062] Step S30: Based on the forwarding line, iteratively traverse each of the data base stations in the data base station set using the ant colony algorithm to obtain the optimal data forwarding line from the sending data base station to the target data base station;

[0063] It should be noted that the ant algorithm in the above embodiments of this application is a heuristic algorithm that simulates the food-finding path of ants in nature. It can effectively find the shortest path in complex networks. In this scenario, it can help technicians find the most efficient data transmission route. Through iterative traversal, the algorithm can continuously optimize path selection and adapt to environmental changes (such as changes in the distance between base stations, the addition of new base stations, etc.), ensuring that data forwarding efficiency remains at a high level. The optimal data forwarding route means that the transmission of data between base stations will consume the least amount of time and resources, which is crucial for improving network performance and reducing operating costs.

[0064] In summary, the embodiments of this application improve the data transmission efficiency of the entire network and reduce data transmission latency by optimizing the forwarding lines between data base stations. While ensuring service quality, they reduce unnecessary data transmission distances and relays, thereby effectively reducing operation and maintenance costs. The technical solutions adopted in the embodiments of this application automatically optimize path selection through algorithms, and have good scalability and flexibility.

[0065] Specifically, such as Figure 3 or Figure 4 As shown, in step S30, based on the forwarding line, the optimal data forwarding line from the sending data base station to the target data base station is obtained by iteratively traversing each data base station in the data base station set using the ant colony algorithm. This includes the following steps:

[0066] Step S31: Set the maximum number of iterations y and the iteration counter; wherein the iteration counter is initially set to 0.

[0067] Step S32: Starting from the transmitting data base station, obtain the initial position of each ant according to the signal coverage range of the transmitting data base station; randomly place each ant at the position corresponding to the coordinate information of each of the first forwarding data base stations, as the initial position of each ant; establish a taboo position table for each ant in each iteration, and add the coordinate information of the transmitting data base station and the initial position to the taboo position table in each iteration; the first forwarding data base station is a data base station within the signal coverage range of the transmitting data base station;

[0068] The above-mentioned method of obtaining the initial position of each ant based on the signal coverage of the transmitting data base station refers to obtaining the coordinate information of the first forwarding data base station and the first forwarding data base station based on the signal coverage of the transmitting data base station; and randomly placing each ant at the position corresponding to the coordinate information of each of the first forwarding data base stations as the initial position of each ant.

[0069] It should be noted that in the above embodiments of this application, the ants are randomly placed at the positions corresponding to the coordinate information of each data base station, which are the positions corresponding to the coordinate information of each data base station adjacent to the sending data base station. In other words, starting from the sending data base station, each ant is randomly sent to the position of each data base station adjacent to the sending data base station. This is also the position of the data base station visited by each ant for the first time.

[0070] Step S33: Determine the second forwarding data base station for each ant based on the line distance (the second forwarding data base station refers to the location of the next data base station determined by the ant based on the transfer probability at the current location of the first forwarding data base station, that is, the location of the data forwarding base station within the signal coverage area of ​​the current first forwarding data base station, excluding the data forwarding base stations in the taboo location table in each iteration).

[0071] Step S34: Repeat the above operation and update the taboo position table in each iteration;

[0072] Step S35: Obtain the target route by analyzing the forbidden position table and the iteration counter in each iteration;

[0073] Specifically, in step S35, the target route is obtained by analyzing the forbidden position table and the iteration counter in each iteration, including the following steps:

[0074] Step S351: Determine whether the target data base station is included in the taboo location table in each iteration; if so, establish a set of routes for each iteration; arrange each data base station in the taboo location table in each iteration in sequence to obtain the route of the current ant in this iteration, and calculate and obtain the distance and number of data base stations of the route of the current ant in this iteration;

[0075] The current ant's current iteration route is added to the iteration route set; otherwise, the current ant continues to traverse the data base station until the target data base station is included in the taboo location table in each iteration.

[0076] Step S352: Further determine whether each ant has obtained the current ant's current iteration path; if so, obtain the current ant's current iteration path with the shortest distance from each current iteration path set as the candidate target path; put the candidate target path into the candidate target path set; and increment the iteration count of the iteration counter by 1.

[0077] Step S353: Determine whether the number of iterations is greater than or equal to the maximum number of iterations y; if yes, then obtain the current ant's current iteration route with the shortest distance in the candidate target route set as the target route; if no, return to the above operation until the number of iterations is greater than or equal to the maximum number of iterations y, and output the target route (the target route is the above-mentioned best forwarding route).

[0078] It should be noted that the above embodiments of this application, by defining the maximum number of iterations and the iteration counter, provide the basic conditions for the subsequent stopping of the algorithm, ensuring that the algorithm can stop iterating after a sufficient number of iterations and preventing overfitting; furthermore, by placing the ants at random locations near the data base station, the ants can begin to search for surrounding data base stations and explore possible paths, laying the foundation for the search for the optimal route; by calculating the transfer probability of the ants between different data base stations through the forwarding distance of the data forwarding line, the ants are helped to select the next updated position, promoting the ants to move towards the target data base station;

[0079] This application embodiment weakens and excludes the utility of pheromones in the implementation process, and only uses the line distance of line forwarding to calculate the probability of ant updating position, thereby reducing the computational complexity and effectively improving computational efficiency; by judging whether the taboo position table contains the target data base station, it helps to determine whether the target has been reached; if not, it continues to traverse the data base stations until the target is found; by establishing a line set for each iteration, recording the ant's path, and calculating the distance and the number of data base stations, it provides data basis for evaluating the ant path; before reaching the maximum number of iterations, it continuously optimizes the ant's path, finds the target line with the shortest distance, and finally outputs the best forwarding line, improving data forwarding efficiency;

[0080] The above-described embodiments of this application utilize the characteristics of the ant algorithm and, through complex calculations involving weakening pheromones and heuristic search, use the line distance of the data forwarding path to calculate the transition probability of each ant, helping the ants find the optimal forwarding path in the network, thereby improving data transmission efficiency and network performance; through iterative optimization, the optimal forwarding path is finally found, making data forwarding more efficient and reliable.

[0081] In the specific implementation of the technical solution adopted in this application, those skilled in the art discovered that, when directly using the heuristic factor function in the ant colony algorithm to calculate the probability of the ant's next update position, the resulting new search positions may differ due to the different heuristic functions. Furthermore, the difficulty in selecting heuristic function parameters and the high computational complexity can lead to inaccurate search results, resulting in an increased or inaccurate number of iterations to obtain the optimal forwarding route, or excessively long search computation time due to high complexity. Therefore, finding a suitable and fixed function to accurately, quickly, and easily obtain the next search position of each ant is also a problem that those skilled in the art urgently need to solve.

[0082] Specifically, such as Figure 5 As shown, in step S33, determining the second forwarding data base station for each of the ants based on the line distance includes the following steps:

[0083] Step S331: Obtain the set P of candidate second forwarding data base stations for each of the ants. ij ={p i1 p i2 p i3 ...p ij}; where p ij It is the j-th candidate second forwarding data base station for the i-th ant;

[0084] Step S332: Obtain the subsequent forwarding data base station q corresponding to each of the candidate second forwarding data base stations; count the number n of subsequent forwarding data base stations for each of the candidate second forwarding data base stations;

[0085] It should be noted that the aforementioned subsequent forwarding data base stations essentially include all data base stations in a data forwarding process. For example, if the current candidate second data forwarding base station is data base station a, and within the signal coverage area of ​​data base station a, the next data base station g is selected for forwarding, then within the signal coverage area of ​​data base station g, the next data base station y is selected for forwarding, then within the signal coverage area of ​​data base station y, the next data base station z is selected for forwarding, and so on, until the target data base station is selected. Therefore, the subsequent forwarding data base stations of the current candidate second forwarding data base station a are g, y, z... and the target data base station. Thus, the subsequent forwarding data base station q is essentially a list-like set of data base stations, which can also be represented as {q1, q2, q3, ... q...} n}, where n is the number of subsequent forwarding data base stations for each candidate second forwarding data base station, or the nth subsequent forwarding data base station for the candidate second forwarding data base station; therefore, the subsequent forwarding data base station q is the subsequent forwarding list of a certain item element (base station) among the candidate second forwarding data base stations.

[0086] Step S333: Obtain the line distance m from the first forwarding data base station to each candidate second forwarding data base station in the forwarding lines of each ant;

[0087] Step S334: Construct a data forwarding matrix R based on the set of candidate second forwarding data base stations and the line distance m;

[0088] The data forwarding matrix R is represented as:

[0089] ;

[0090] Step S335: Calculate and obtain the fitness f of each of the candidate second forwarding data base stations based on the data forwarding matrix and the number n of subsequent forwarding data base stations;

[0091] The fitness f is calculated as follows:

[0092] ;

[0093] In the formula, n is the number of subsequent forwarding data base stations of the second forwarding data base station; R is the data forwarding matrix; i' is the total number of ants; and i is the i-th ant.

[0094] Step S336: Obtain the target second forwarding data base station according to the fitness f;

[0095] In the above embodiments of this application, the candidate second forwarding data base station with the highest fitness is selected as the target second forwarding data base station;

[0096] It should be noted that, in the embodiments of this application described above, by obtaining the set of candidate second forwarding data base stations for each ant, a range of candidate base stations can be provided for subsequent calculations and selections; by obtaining the number of subsequent forwarding data base stations, the degree of competition among different base stations can be considered when calculating fitness, so as to better select the target second forwarding data base station; by obtaining line distance information, the influence of base station distance can be considered in subsequent fitness calculations, so as to select a better target second forwarding data base station; by constructing a data forwarding matrix, the candidate second forwarding data base stations can be associated with line distances, providing a data foundation for subsequent fitness calculations; by calculating fitness, the weight of each base station in the data forwarding matrix and the number of subsequent forwarding data base stations can be comprehensively considered, providing an evaluation index for selecting the target second forwarding data base station; by selecting the base station with the highest fitness, the optimal target second forwarding data base station can be selected from multiple candidate base stations, thereby improving the efficiency and quality of data forwarding;

[0097] In summary, this application embodiment, considering line distance, the number of subsequent forwarding data base stations, and the data forwarding matrix, optimizes data forwarding and improves network performance by calculating fitness and selecting the optimal base station. It can effectively select the target second forwarding data base station, using a simple fitness calculation method that eliminates the complex pheromone update calculation and heuristic probability calculation method in the original ant algorithm. It uses the number of subsequent forwarding data base stations of each ant at the current second forwarding data base station and the line distance to update the position of each ant, improving the efficiency of machine selection. It also fully considers the number of subsequent forwarding data base stations of each ant, thereby selecting a more accurate target second forwarding data base station as the next update location.

[0098] In the specific implementation process of the above-described embodiments of this application, technicians have found that when the number of data base stations is large, the number of lines from each candidate second forwarding data base station to the target data base station is very large, for example, as follows: Figure 6As shown in the diagram (circles represent the signal coverage areas of each data base station), there are data base stations S1, S2, S3, S4, S5, ..., Si; where S1 is the data forwarding base station and Si is the target data base station. In the implementation of the above technical solution, S2 and S3 were selected as the first forwarding data base stations, and then S4, S5, S6, and S7 were selected as candidate second forwarding data base stations. Furthermore, in the process of calculating the target second forwarding data base station, because the signal coverage areas of each data base station are different, the candidate second forwarding data base station S... The subsequent forwarding data base stations for 4 may be S9→S16→25→...→Si; or S9→S10→S17→...→Si; or S9→S17→S27→...→Si, etc. Although each subsequent forwarding data base station ends at the target data base station, the large number of forwarding possibilities results in a lot of data redundancy, making it very slow to calculate a suitable and fast forwarding route. Therefore, it is necessary to limit each subsequent forwarding data base station to form a fixed and fastest forwarding route for the subsequent forwarding data base stations.

[0099] Specifically, such as Figure 7 As shown, in step S332, obtaining the subsequent forwarding data base station q corresponding to each of the candidate second forwarding data base stations includes the following operation steps:

[0100] Step S3321: Traverse each of the candidate second forwarding data base stations, and obtain the set of third forwarding data base stations K={k1, k2, k3, ...kt} of the candidate second forwarding data base stations according to the signal coverage range of the second forwarding data base station; kt is the t-th third forwarding data base station of the second forwarding data base station;

[0101] Step S3322: Based on the forwarding lines from the second forwarding data base station to each of the third forwarding data base stations and the distances of the lines, filter and obtain the shortest distance d;

[0102] Step S3323: Calculate and obtain the distance difference matching degree f' of each of the third forwarding data base stations based on the shortest distance d and the set of third forwarding data base stations;

[0103] The distance difference matching degree f' is calculated as follows:

[0104] ;

[0105] In the formula, di'' is the shortest distance from the i''th second forwarding data base station to the tth third forwarding data base station; Let t be the distance from the t-th third forwarding data base station to the second forwarding data base station; The distance between the third forwarding data base station and the second forwarding data base station is the average value; t is the t-th (referring to the t-th third forwarding data base station); T is the total number of third forwarding data base stations;

[0106] Step S3324: Based on the distance difference matching degree f' of each of the third forwarding data base stations, filter and obtain the target third forwarding data base station corresponding to the second forwarding data base station;

[0107] Step S3325: Repeat the above operation until all candidate second forwarding data base stations have been traversed to obtain the target third forwarding data base station corresponding to each candidate second forwarding data base station;

[0108] Step S3326: Select the target third forwarding data base station as the candidate second forwarding data base station, and repeat the above operation to obtain a new target third forwarding data base station until it is finally added to the target data base station, thereby obtaining the subsequent forwarding data base station corresponding to each candidate second forwarding data base station.

[0109] It should be noted that the above-described embodiments of this application, by traversing the candidate second forwarding data base stations and obtaining the set of third forwarding data base stations, can effectively determine the potential forwarding targets of each second forwarding data base station, preparing a data foundation for subsequent calculations; further, by filtering to obtain the shortest distance d, it can help determine the optimal forwarding path; by calculating the distance difference matching degree f', the merits of each third forwarding data base station can be evaluated, which helps to select the most suitable forwarding target; filtering the target data base station based on the distance difference matching degree of the third forwarding data base station helps to optimize the forwarding path selection; by repeating the operation until all candidate second forwarding data base stations have been traversed, it is ensured that each second forwarding data base station can select the optimal forwarding target, comprehensively optimizing the data forwarding path; by continuously optimizing the forwarding path using the target third forwarding data base station as a candidate second forwarding data base station, the stability of the network and the efficiency of data transmission can be further improved, ensuring that data can be transmitted to the destination quickly and reliably; through the above steps, the subsequent forwarding data base stations of each candidate second forwarding data base station can be effectively obtained and optimized, thereby forming a fixed and fastest forwarding subsequent forwarding data base station forwarding line.

[0110] In summary, the cloud-edge collaborative 5G networking multi-hop forwarding path dynamic processing method and storage medium proposed in this invention improves the data transmission efficiency of the entire network and reduces data transmission latency by optimizing the forwarding lines between data base stations. While ensuring service quality, it reduces unnecessary data transmission distances and relays, thereby effectively reducing operation and maintenance costs. The technical solution adopted in the above embodiments of this application automatically optimizes path selection through algorithms, and has good scalability and flexibility.

[0111] Furthermore, in the specific implementation of the technical solution of this application, by defining the maximum number of iterations and the iteration counter, the basic conditions for the subsequent stopping of the algorithm are provided, ensuring that the algorithm can stop iterating after a sufficient number of iterations and preventing overfitting; furthermore, by placing ants at random locations near data base stations, the ants can begin to search for surrounding data base stations and explore possible paths, laying the foundation for the search for the optimal route; by calculating the transfer probability of ants between different data base stations through the forwarding distance of the data forwarding line, the transfer probability of ants between different data base stations is helped to select the next updated position for each ant, promoting the ants to move towards the target data base station;

[0112] By leveraging the characteristics of the ant colony algorithm and employing complex calculations involving pheromone weakening and heuristic search, the algorithm calculates the transition probability of each ant using the distance of the data forwarding path. This helps the ants find the optimal forwarding path in the network, improving data transmission efficiency and network performance. Through iterative optimization, the algorithm ultimately finds the optimal forwarding path, making data forwarding more efficient and reliable.

[0113] Furthermore, considering the line distance, the number of subsequent forwarding data base stations, and the data forwarding matrix, by calculating fitness and selecting the optimal base station, data forwarding can be optimized and network performance improved. It can effectively select the target second forwarding data base station. With a simple fitness calculation method, it abandons the complex pheromone update calculation and complex heuristic function probability calculation method in the original ant algorithm. It uses the number of subsequent forwarding data base stations of each ant at the current second forwarding data base station and the line distance to update the position of each ant, improving the efficiency of machine selection. It also fully considers the number of subsequent forwarding data base stations of each ant, thereby selecting a more accurate target second forwarding data base station as the next update location.

[0114] In a further technical solution, by traversing the candidate second forwarding data base stations and obtaining the set of third forwarding data base stations, the potential forwarding targets of each second forwarding data base station can be effectively determined, providing a data foundation for subsequent calculations. Furthermore, by filtering to obtain the shortest distance d, the optimal forwarding path can be determined. Calculating the distance difference matching degree f' can evaluate the merits of each third forwarding data base station, aiding in the selection of the most suitable forwarding target. Filtering target data base stations based on the distance difference matching degree of the third forwarding data base stations helps optimize the forwarding path selection. Repeating this operation until all candidate second forwarding data base stations have been traversed ensures that each second forwarding data base station can select the optimal forwarding target, comprehensively optimizing the data forwarding path. Continuously optimizing the forwarding path using the target third forwarding data base station as a candidate second forwarding data base station further improves network stability and data transmission efficiency, ensuring that data can be transmitted to its destination quickly and reliably. Through the above steps, the effective acquisition and optimized selection of subsequent forwarding data base stations for each candidate second forwarding data base station can be achieved, thereby forming a fixed and fastest forwarding route for subsequent forwarding data base stations.

[0115] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; those skilled in the art can modify the technical solutions described in the foregoing embodiments, or make equivalent substitutions for some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for dynamic processing of multi-hop forwarding paths in 5G networking under cloud-edge collaboration, characterized in that, The following steps are included: Obtain the data base station set for the current area; and obtain the transmitting data base station and the target data base station in the data base station set; obtain the signal coverage range of each data base station in the data base station set; Based on the coordinate information of each data base station and the signal coverage area, the forwarding lines between each pair of data base stations and the line distance of each forwarding line are obtained. Based on the forwarding route, the ant colony algorithm is used to iteratively traverse each of the data base stations in the data base station set to obtain the optimal data forwarding route from the sending data base station to the target data base station. The step of iteratively traversing each of the data base stations in the data base station set using the ant colony algorithm to obtain the optimal data forwarding route from the sending data base station to the target data base station, based on the forwarding route, includes the following steps: Set the maximum number of iterations y and the iteration counter; wherein the iteration counter is initially set to 0. Starting from the transmitting data base station, the coordinate information of the first forwarding data base station and the first forwarding data base station are obtained according to the signal coverage range of the transmitting data base station; each ant is randomly placed at the position corresponding to the coordinate information of each first forwarding data base station, which is used as the initial position of each ant; a taboo position table is established for each ant in each iteration, and the coordinate information of the transmitting data base station and the initial position are added to the taboo position table in each iteration; the first forwarding data base station is a data base station within the signal coverage range of the transmitting data base station; Determining the second forwarding data base station for each of the ants based on the line distance includes the following steps: obtaining the set P of candidate second forwarding data base stations for each of the ants. ij ={p i1 p i2 p i3 ...p ij }; where p ij It is the j-th candidate second forwarding data base station for the i-th ant; Obtain the subsequent forwarding data base station q corresponding to each of the candidate second forwarding data base stations; count the number n of subsequent forwarding data base stations for each of the candidate second forwarding data base stations; Obtain the line distance m from the first forwarding data base station to each candidate second forwarding data base station in the forwarding lines of each of the ants; Construct a data forwarding matrix R based on the set of candidate second forwarding data base stations and the line distance m; The fitness f of each candidate second forwarding data base station is calculated based on the data forwarding matrix and the number n of subsequent forwarding data base stations. The fitness f is calculated as follows: ； In the formula, n is the number of subsequent forwarding data base stations of the second forwarding data base station; R is the data forwarding matrix, i' is the total number of ants, and i is the i-th ant; Select the candidate second forwarding data base station with the highest fitness as the target second forwarding data base station; Repeat the above operations and update the taboo position table in each iteration; The target route is obtained by analyzing the forbidden position table and the iteration counter in each iteration.

2. The method for dynamic processing of multi-hop forwarding paths in 5G networking under cloud-edge collaboration as described in claim 1, characterized in that, The step of obtaining the target route by analyzing the forbidden position table and the iteration counter in each iteration includes the following steps: Determine whether the target data base station is included in the taboo location table in each iteration; if so, establish a set of routes for each iteration; arrange each data base station in the taboo location table in each iteration in sequence to obtain the route of the current ant in this iteration, and calculate and obtain the distance and the number of data base stations of the route of the current ant in this iteration; Add the current ant's current iteration path to the iteration path set; If not, then control the current ant to continue traversing the data base station until the target data base station is included in the taboo location table in each iteration; Further determine whether each ant has obtained the current ant's iteration path; If so, then the current ant's current iteration path with the shortest distance in each current iteration path set is taken as the candidate target path; Add the candidate target routes to the candidate target route set; At the same time, increment the iteration count of the iteration counter by 1; Determine whether the number of iterations is greater than or equal to the maximum number of iterations y; If so, then the current ant's current iteration route with the shortest distance in the candidate target route set is taken as the target route; If not, return to the above operation until the number of iterations is greater than or equal to the maximum number of iterations y, and then output the target route.

3. The method for dynamic processing of multi-hop forwarding paths in 5G networking under cloud-edge collaboration as described in claim 2, characterized in that, Obtaining the subsequent forwarding data base station q corresponding to each of the candidate second forwarding data base stations includes the following steps: Traverse each of the candidate second forwarding data base stations, and obtain the set of third forwarding data base stations K={k1, k2, k3, ...kt} of the candidate second forwarding data base stations according to the signal coverage range of the second forwarding data base stations; kt is the t-th third forwarding data base station of the second forwarding data base station; Based on the forwarding lines from the second forwarding data base station to each of the third forwarding data base stations and the distances of those lines, the shortest distance d is obtained by filtering. The distance difference matching degree f' of each of the third forwarding data base stations is calculated based on the shortest distance d and the set of third forwarding data base stations; Based on the distance difference matching degree f' of each of the third forwarding data base stations, the target third forwarding data base station corresponding to the second forwarding data base station is selected and obtained; Repeat the above operation until all candidate second forwarding data base stations have been traversed to obtain the target third forwarding data base station corresponding to each candidate second forwarding data base station; The target third forwarding data base station is used as a candidate second forwarding data base station, and the above operation is repeated to obtain a new target third forwarding data base station until it is finally added to the target data base station, thus obtaining the subsequent forwarding data base station corresponding to each candidate second forwarding data base station.

4. A storage medium, characterized in that, The storage medium includes a stored program, wherein, when the program is running, it controls the device where the storage medium is located to execute the dynamic processing method for multi-hop forwarding paths in 5G networking under cloud-edge collaboration as described in any one of claims 1-3.

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