5G networking multi-hop forwarding path dynamic processing method under cloud edge cooperation and storage medium

Abstract

The invention discloses a dynamic processing method for a 5G networking multi-hop forwarding path under cloud edge collaboration and a storage medium, and the method employs an ant algorithm to improve the data transmission efficiency of the whole network and reduce the delay of data transmission through optimizing a forwarding line between data base stations. While the service quality is ensured, unnecessary data transmission distance and transfer are reduced, so that the operation and maintenance cost can be effectively reduced; according to the technical scheme adopted by the embodiment of the invention, path selection is automatically optimized through an algorithm, and good expandability and flexibility are achieved.

Description

Technical Field

[0001] The present 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 Art

[0002] "Multi-hop" refers to the process by which data is transmitted from sender to receiver. Instead of reaching the final destination directly through a single wireless communication, it must be forwarded through one or more intermediate nodes (or relay nodes). This communication method is particularly suitable for situations where the distance between nodes is large or obstacles prevent the signal from reaching the destination node directly. During multi-hop communication, after receiving the data, the intermediate nodes forward it until the data reaches the final destination node. Each forwarding step is called a "hop." For example, if data is transmitted from node A to node D, it must be forwarded through nodes B and C in sequence, which is called a three-hop communication path (A→B→C→D).

[0003] In 5G networks, multi-hop forwarding is usually used in the following scenarios: 1. In remote areas, mountainous areas, underground buildings and other places where signals are difficult to cover, relay nodes are used to forward signals through multiple hops to improve network coverage and quality. 2. Under the Cloud-Edge Collaborative architecture, data may be transmitted step by step to the cloud through multiple edge nodes, or sent back from the cloud to the terminal device through multiple edge nodes. When the terminal device or node moves, the network path may need to be dynamically adjusted to maintain stable data transmission and avoid connection interruption or excessive delay. The 5G network is also composed of a large number of 5G communication data base stations (referred to as data base stations); in the traditional data forwarding process mentioned above, there may be problems such as ineffective transmission paths and long distances between data base stations, resulting in low data forwarding efficiency. Data base stations need to forward data one by one according to the signal coverage of the data base stations, so that the data base station at the sending end forwards the data to the data base station at the target end;

[0004] However, in real-world scenarios, there are many data base stations between the sending end and the target end. Due to the signal coverage of the data base stations, the data information needs to be repeatedly and multiple times forwarded between many data base stations before reaching the final target data base station, which will cause serious data forwarding delays during the data forwarding process. Therefore, how to ensure that data can be sent quickly and with the lowest delay when there are multiple data base stations in transit is a difficult problem that needs to be solved urgently. Summary of the Invention

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

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

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

[0008] Acquire a forwarding line for data forwarding between every two data base stations and a line distance of each forwarding line based on the coordinate information of each data base station and the signal coverage range;

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

[0010] Preferably, according to the forwarding route, an ant 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, including the following steps:

[0011] Setting a maximum number of iterations y and an iteration counter; wherein the number of iterations of the iteration counter is initially 0;

[0012] Starting from the data sending base station, the initial position of each ant is obtained according to the signal coverage of the data sending base station; a taboo position table corresponding to each ant in each iteration is established, and the coordinate information of the data sending 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 of the data sending base station;

[0013] Determine a second data forwarding base station for each of the ants according to the line distance;

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

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

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

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

[0018] placing the current ant's iteration route into the iteration route set; if not, controlling the current ant to continue traversing the data base station until the taboo position table in each iteration includes the target data base station;

[0019] Further determining whether all the ants have obtained the current ant's current iteration route; if so, obtaining the current ant's current iteration route with the shortest distance from the current ant's current iteration route in the current iteration route set as a candidate target route; placing the candidate target route into the candidate target route set; and simultaneously increasing 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 so, obtain the current ant's current iteration path with the shortest distance from the current ant's current iteration path in the set of candidate target paths as the target path; 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 output the target path.

[0021] Preferably, the initial position of each of the ants is obtained according to the signal coverage range of the data sending 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 data sending base station; and each ant is randomly placed at a position corresponding to the coordinate information of each first forwarding data base station as the initial position of each ant.

[0022] Preferably, determining the second data forwarding base station of each ant according to the line distance includes the following steps:

[0023] Get the second data forwarding base station set P to be selected by each ant ij ={p i1 , p i2 , p i3 ,...p ij}; where p ij is the jth selected second data forwarding base station for the i-th ant;

[0024] Obtaining a subsequent data forwarding base station q corresponding to each of the second data forwarding base stations to be selected; and counting the number n of subsequent data forwarding base stations of each of the second data forwarding base stations to be selected;

[0025] Obtaining a line distance m from the first data forwarding base station to each selected second data forwarding base station in the forwarding line of each ant;

[0026] Constructing a data forwarding matrix based on the second data forwarding base station set to be selected and the line distance m ;

[0027] The data forwarding matrix Expressed as: ;

[0028] Calculating and obtaining the fitness f of each of the candidate second data forwarding base stations according to the data forwarding matrix and the number n of the subsequent data forwarding base stations;

[0029] Obtaining a target second data forwarding base station according to the fitness f;

[0030] Preferably, obtaining the target second data forwarding base station according to the fitness f is selecting a candidate second data forwarding base station with the highest fitness as the target second data forwarding base station;

[0031] Preferably, the fitness f is calculated as follows: ;

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

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

[0034] Traversing each of the candidate second forwarding data base stations, obtaining a third forwarding data base station set K={k1, k2, k3, ...kt} of the candidate second forwarding data base station according to the signal coverage of the second forwarding data base station, where kt is the tth third forwarding data base station of the second forwarding data base station;

[0035] Filter and obtain the shortest distance d according to the forwarding lines from the second data forwarding base station to each of the third data forwarding base stations and the line distances;

[0036] Obtaining a distance difference matching degree f' of each of the third data forwarding base stations by calculation according to the shortest distance d and the third data forwarding base station set;

[0037] According to the distance difference matching degree f' of each of the third data forwarding base stations, screening and obtaining the target third data forwarding base station corresponding to the second data forwarding base station;

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

[0039] The target third forwarding data base station is used as the second forwarding data base station to be selected, 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, thereby obtaining subsequent forwarding data base stations corresponding to each of the second forwarding data base stations to be selected.

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

[0041] Wherein, di'' is the shortest distance from the i''th second data forwarding base station to the t'th third data forwarding base station; is the distance from the tth third data forwarding base station to the second data forwarding base station; is the average distance from the third data forwarding base station to the second data forwarding base station; t is the t-th; T is the total number of third data forwarding base stations;

[0042] The present invention also provides a storage medium, which includes a stored program, wherein when the program is running, the device where the storage medium is located is controlled to execute the above-mentioned method for dynamic processing of multi-hop forwarding paths in 5G networking under cloud-edge collaboration.

[0043] Compared with the prior art, the embodiments of the present invention have at least the following technical advantages:

[0044] From the analysis of the above-mentioned 5G networking multi-hop forwarding path dynamic processing method and storage medium under cloud-edge collaboration provided by the present invention, it can be seen that the ant algorithm is used in specific applications to optimize the forwarding lines between data base stations, so that the data transmission efficiency of the entire network is improved and the data transmission delay is reduced; while ensuring the quality of service, unnecessary data transmission distances and transits are reduced, thereby effectively reducing operation and maintenance costs; the technical solution adopted in the above-mentioned embodiment of the present application automatically optimizes path selection through an algorithm, and has good scalability and flexibility. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0046] Figure 1A schematic diagram of the overall operation steps of a method for dynamically processing multi-hop forwarding paths in a 5G network under cloud-edge collaboration provided by an embodiment of the present invention;

[0047] Figure 2 A schematic diagram of a data forwarding line between data base stations in a method for dynamically processing a multi-hop forwarding path in a 5G network under cloud-edge collaboration provided by an embodiment of the present invention;

[0048] Figure 3 A schematic diagram of the operational steps for obtaining the optimal data forwarding line in a method for dynamically processing multi-hop forwarding paths in a 5G network under cloud-edge collaboration provided by an embodiment of the present invention;

[0049] Figure 4 A schematic diagram of the operational flow of obtaining the optimal data forwarding line in a method for dynamically processing multi-hop forwarding paths in a 5G network under cloud-edge collaboration provided by an embodiment of the present invention;

[0050] Figure 5 A schematic diagram of the operation steps for obtaining a second forwarding data base station in a method for dynamically processing a multi-hop forwarding path in a 5G network under cloud-edge collaboration provided by an embodiment of the present invention;

[0051] Figure 6 A schematic diagram of data forwarding line simulation in a method for dynamic processing of multi-hop forwarding paths in a 5G network under cloud-edge collaboration provided by an embodiment of the present invention;

[0052] Figure 7 A schematic diagram of the operational steps for obtaining subsequent forwarding data base stations in a method for dynamic processing of multi-hop forwarding paths in a 5G network under cloud-edge collaboration provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0053] The technical solution of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0054] The present invention will be further described in detail below through specific embodiments in conjunction with the accompanying drawings.

[0055] Example 1

[0056] like Figure 1 As shown, accordingly, the present invention also proposes a method for dynamically processing multi-hop forwarding paths in 5G networking under cloud-edge collaboration, including the following steps:

[0057] Step S10: obtaining a data base station set in the current area; obtaining a sending data base station and a target data base station in the data base station set; and obtaining a signal coverage range of each data base station in the data base station set;

[0058] It should be noted that, due to the signal coverage of each data base station, the data forwarding of each data base station in the above-mentioned data base station set can be forwarded by the sending data base station, and the data base stations connected to each other can be forwarded step by step or through the coverage of the data base stations, so that the forwarded data is finally sent to the target data base station; but cross-domain data forwarding is not allowed; for example: Figure 2 As shown in the figure, 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; among them, data base station ① is the sending data base station, and data base station ⑥ is the target data base station. Data base station ① sends data, and data base stations ③, data base station ④, and data base station ⑤ forward it, and finally send the data to data base station ⑥; and every two adjacent data base stations in the data base station set are adjacent to each other, among which the signal coverage range of each data base station is shown as the dotted line in the figure, so the forwarded data can be forwarded by data base station ① to data base station ④, and then to data base station ⑥; at the same time, it can be forwarded by data base station ① to data base station ②, and then to data base station ⑤, and finally to data base station ⑥, and so on; and in the data forwarding process of these data base stations, due to line reasons, the forwarded data cannot be directly forwarded by data base station ① to data base station ⑤, and at the same time, it cannot be forwarded by data base station ① to data base station ⑥...

[0059] Step S20: acquiring a forwarding line for data forwarding between every two data base stations and a line distance of each forwarding line based on the coordinate information of each data base station and the signal coverage range;

[0060] It should be noted that the above-mentioned embodiment of the present application ensures that all data base stations that need to be considered are included in the calculation range by obtaining the data base station set in the current area, and by obtaining the coordinate information of each data base station, a clear understanding of the position of the base station in the geographic space can be obtained, laying the foundation for the subsequent optimal data forwarding line.

[0061] Step S30: According to the forwarding route, an ant algorithm is used to iteratively traverse each of the data base stations in the data base station set to obtain an optimal data forwarding route from the sending data base station to the target data base station;

[0062] It should be noted that the ant algorithm in the above-mentioned embodiment of the present application is a heuristic algorithm that simulates the path of ants in nature to find food. It can effectively find the shortest path in a complex network. In this scenario, it can help technicians find the route with the highest data transmission efficiency. 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 always remains at a high level. The optimal data forwarding route means that the transmission of data between base stations will consume the least time and resources, which is crucial to improving network performance and reducing operating costs.

[0063] In summary, the above-mentioned embodiments of the present application improve the data transmission efficiency of the entire network and reduce the delay of data transmission by optimizing the forwarding lines between data base stations; while ensuring the quality of service, unnecessary data transmission distances and transits are reduced, thereby effectively reducing operation and maintenance costs; the technical solution adopted in the above-mentioned embodiments of the present application automatically optimizes path selection through an algorithm, and has good scalability and flexibility.

[0064] Specifically, if Figure 3 or Figure 4 As shown, in step S30, according to the forwarding line, the ant algorithm is used to iteratively traverse each data base station in the data base station set to obtain the optimal data forwarding line from the sending data base station to the target data base station, including the following steps:

[0065] Step S31: setting a maximum number of iterations y and an iteration counter; wherein the number of iterations of the iteration counter is initially 0;

[0066] Step S32: Starting from the data sending base station, the initial position of each ant is obtained according to the signal coverage of the data sending base station; each ant is randomly placed at a position corresponding to the coordinate information of each first forwarding data base station as the initial position of each ant; a taboo position table corresponding to each ant in each iteration is established, and the coordinate information of the data sending 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 of the data sending base station;

[0067] The aforementioned obtaining the initial position of each ant based on the signal coverage range of the data sending base station refers to obtaining the coordinate information of the first data forwarding base station and the first data forwarding base station based on the signal coverage range of the data sending base station; and randomly placing each ant at a position corresponding to the coordinate information of each first data forwarding base station as the initial position of each ant;

[0068] It should be noted that, in the above-mentioned embodiment of the present application, each ant is randomly placed at a position corresponding to the coordinate information of each data base station, which is a position corresponding to the coordinate information of each data base station adjacent to the base station that sends the data. In other words, starting from the base station that sends the data, each ant is randomly sent to the position of each data base station adjacent to the base station that sends the data, which is also the position of the data base station that each ant traverses for the first time;

[0069] Step S33: Determine the second data forwarding base station for each ant based on the line distance (the second data forwarding base station refers to the location of the next data base station determined by the ant based on the transition probability at the current location of the first data forwarding base station, that is, the location of the data forwarding base station within the signal coverage range of the current first data forwarding base station, excluding the data forwarding base stations in the taboo location table in each iteration);

[0070] Step S34: repeat the above operation and update the taboo position table in each iteration;

[0071] Step S35: obtaining a target route by judging and analyzing the taboo position table and the iteration counter in each iteration;

[0072] Specifically, in step S35, the target route is obtained by judging and analyzing the taboo position table and the iteration counter in each iteration, including the following steps:

[0073] Step S351: Determine whether the taboo position table in each iteration contains the target data base station; if so, establish a path set for each iteration; sequentially arrange the data base stations in the taboo position table in each iteration to obtain the path of the current ant in this iteration, and calculate the distance and number of data base stations of the path of the current ant in this iteration;

[0074] placing the current ant's iteration route into the iteration route set; if not, controlling the current ant to continue traversing the data base station until the taboo position table in each iteration includes the target data base station;

[0075] Step S352: further determining whether all the ants have obtained the current ant's current iteration route; if so, obtaining the current ant's current iteration route with the shortest distance from the current ant's current iteration route in the current iteration route set as a candidate target route; placing the candidate target route into the candidate target route set; and simultaneously increasing the iteration count of the iteration counter by 1;

[0076] Step S353: Determine whether the number of iterations is greater than or equal to the maximum number of iterations y. If so, obtain the current ant's current iteration path with the shortest path distance from the current ant in the set of candidate target paths as the target path. 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 output the target path (the target path is the optimal forwarding path).

[0077] It should be noted that the above-mentioned embodiment of the present application defines a maximum number of iterations and an iteration counter to provide a basic condition for stopping the subsequent algorithm, ensuring that the algorithm can stop iteration after a sufficient number of iterations to prevent overfitting. Furthermore, by placing ants at random positions near the data base station, the ants can begin searching for surrounding data base stations and exploring possible paths, laying the foundation for searching for the optimal route. The forwarding distance of the data forwarding route is used to calculate the transfer probability of the ants between different data base stations, helping each ant select the next update position and promoting the ants to move towards the target data base station.

[0078] The embodiment of the present application weakens and excludes the effectiveness of pheromones in the implementation process of the present application, and only uses the line distance of the line forwarding to calculate the probability of the ant updating the position, thereby reducing the complexity of the calculation and effectively improving the calculation efficiency; by judging whether the taboo position table contains the target data base station, it helps to determine whether the target is reached; if not, it continues to traverse the data base stations until the target is found; by establishing a set of lines for each iteration, recording the path of the ant, and calculating the distance and the number of data base stations, it provides a data basis for evaluating the ant path; before reaching the maximum number of iterations, it continuously optimizes the ant path to find the target line with the shortest distance, and finally outputs the best forwarding line to improve data forwarding efficiency;

[0079] The above-mentioned embodiment of the present application utilizes the characteristics of the ant algorithm, and by weakening the complex calculations of pheromones and heuristic searches, uses the line distance of the data forwarding line to calculate the transfer probability of each ant, helping ants find the best forwarding line in the network, improving data transmission efficiency and network performance; through iterative optimization, the best forwarding line is finally found, making data forwarding more efficient and reliable.

[0080] During the specific implementation of the technical solution adopted in the above-mentioned present application, technical personnel found that after directly using the heuristic factor function in the ant algorithm to calculate the probability of the next updated position of the ant, in the process of obtaining the next search position of each ant, due to the difference in heuristic functions, the new search positions obtained may be different. At the same time, due to the difficulty in selecting the parameters of the heuristic function and the high complexity of the calculation, the search results are inaccurate due to the parameter selection, which leads to an increase in the number of iterations for obtaining the optimal forwarding route or inaccurate or a long search calculation time due to the high complexity. Therefore, how to find a suitable and fixed function to accurately, quickly and simply obtain the next search position of each ant is also a difficult problem that technical personnel in this field urgently need to solve.

[0081] Specifically, if Figure 5 As shown, in step S33, determining the second forwarding data base station of each ant according to the line distance includes the following operation steps:

[0082] Step S331: Obtain the second base station set P to be selected for forwarding data of each ant ij ={p i1 , p i2 , p i3 ,...p ij}; where p ij is the jth selected second data forwarding base station for the i-th ant;

[0083] Step S332: Acquire the subsequent data forwarding base station q corresponding to each of the second data forwarding base stations to be selected; and count the number n of subsequent data forwarding base stations of each of the second data forwarding base stations to be selected;

[0084] It should be noted that the above-mentioned subsequent forwarding data base station actually includes all data base stations in a data forwarding line process. For example: the currently selected second data forwarding base station is data base station a, and the next data base station g is selected for forwarding within the signal coverage range of data base station a. Then, the next data base station y is selected for forwarding within the signal range of data base station g, and then the next data base station z is selected for forwarding within the signal range of data base station y... until the target data base station is selected, then the subsequent forwarding data base stations of the currently selected second forwarding data base station a are g, y, z...the target data base station; therefore, the subsequent forwarding data base station q is essentially a set of data base stations in the form of a list, which can also be expressed as {q1, p2, p4, ...p b Therefore, the subsequent data forwarding base station q is a subsequent forwarding list of a certain item element (base station) in the candidate second data forwarding base station;

[0085] Step S333: obtaining the line distance m between the first data forwarding base station and each candidate second data forwarding base station in the forwarding line of each ant;

[0086] Step S334: Constructing a data forwarding matrix based on the second selected data forwarding base station set and the line distance m ;

[0087] The data forwarding matrix Expressed as: ;

[0088] Step S335: Calculate and obtain the fitness f of each of the candidate second data forwarding base stations according to the data forwarding matrix and the number n of the subsequent data forwarding base stations;

[0089] The fitness f is calculated as follows: ;

[0090] Wherein, n is the number of subsequent data forwarding base stations of the second data forwarding base station; is the data forwarding matrix, i' is the total number of ants, and i is the i-th ant;

[0091] Step S336: Obtain a target second data forwarding base station according to the fitness f;

[0092] In the above embodiment of the present application, a candidate second data forwarding base station with the highest adaptability is selected as the target second data forwarding base station;

[0093] It should be noted that the above-mentioned embodiment of the present application can provide a range of candidate base stations for subsequent calculations and selections by obtaining the set of candidate second forwarding data base stations for each ant; 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 station can be associated with the line distance, providing a data basis 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 to provide 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;

[0094] In summary, the embodiment of the present application, based on considerations of line distance, the number of subsequent data forwarding base stations and the data forwarding matrix, can optimize data forwarding and improve network performance by calculating fitness and selecting the optimal base station. It can effectively select the target second forwarding data base station, and abandon the complex pheromone update calculation and the complex probability calculation method of the heuristic function in the original ant algorithm with a simple fitness calculation method. The position of each ant is updated using the number of subsequent forwarding data base stations of the current second forwarding data base station and the line distance, thereby improving the efficiency of machine selection and fully considering 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.

[0095] During the specific implementation of the above embodiment of the present application, technicians found that when the number of data base stations is large, there are many lines from each candidate second forwarding data base station to the target data base station, for example, as follows Figure 6 As shown (the circles in the figure represent the signal coverage range of each data base station), there are data base stations S1, S2, S3, S4, S5, ...Si; among them, S1 is the data forwarding base station, Si is the target data base station, in the process of implementing the above technical solution, S2 and S3 are selected as the first forwarding data base stations, and then, S4, S5, S6, and S7 are selected as the second forwarding data base stations to be selected, and then, in the process of calculating the target second forwarding data base station, because the signal coverage range of each data base station is different, the second forwarding data base station S to be selected is selected. The subsequent data forwarding base stations of 4 may be S9→S16→25→...→Si; or S9→S10→S17→...→Si; or S9→S17→S27→...→Si, etc. Although each subsequent data forwarding base station ends at the target data base station, the large number of forwarding possibilities causes a large amount of data redundancy, making it very slow to calculate a suitable and fast forwarding route. Therefore, it is necessary to limit each subsequent data forwarding base station to form a fixed and fastest forwarding route for the subsequent data forwarding base station.

[0096] Specifically, if Figure 7 As shown, in step S332, obtaining the subsequent data forwarding base station q corresponding to each of the candidate second data forwarding base stations includes the following steps:

[0097] Step S3321: traverse each of the candidate second forwarding data base stations, and obtain a third forwarding data base station set K={k1, k2, k3, ...kt} of the candidate second forwarding data base station according to the signal coverage of the second forwarding data base station, where kt is the t-th third forwarding data base station of the second forwarding data base station;

[0098] Step S3322: Filter and obtain the shortest distance d according to the forwarding lines from the second data forwarding base station to each of the third data forwarding base stations and the line distances;

[0099] Step S3323: Calculate and obtain the distance difference matching degree f' of each of the third data forwarding base stations according to the shortest distance d and the third data forwarding base station set;

[0100] The distance difference matching degree f' is calculated as follows: ;

[0101] Wherein, di'' is the shortest distance from the i''th second data forwarding base station to the t'th third data forwarding base station; is the distance from the tth third data forwarding base station to the second data forwarding base station; is the average distance from the third data forwarding base station to the second data forwarding base station; t is the tth (referring to the tth third data forwarding base station); T is the total number of third data forwarding base stations;

[0102] Step S3324: Filter and obtain a target third data forwarding base station corresponding to the second data forwarding base station according to the distance difference matching degree f' of each third data forwarding base station;

[0103] Step S3325: Repeat the above operation until all candidate second data forwarding base stations are traversed to obtain the target third data forwarding base station corresponding to each candidate second data forwarding base station;

[0104] Step S3326: Take the target third forwarding data base station as the second forwarding data base station to be selected, 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, and obtain subsequent forwarding data base stations corresponding to each of the second forwarding data base stations to be selected.

[0105] It should be noted that the above-mentioned embodiment of the present application can effectively determine the potential forwarding targets of each second forwarding data base station by traversing the candidate second forwarding data base stations and obtaining the set of third forwarding data base stations, thereby preparing a data basis for subsequent calculations; further screening to obtain the shortest distance d can help determine the optimal forwarding path, and by calculating the distance difference matching degree f', the advantages and disadvantages of each third forwarding data base station can be evaluated, which helps to select the most suitable forwarding target; screening the target data base station according to 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 are traversed, it is ensured that each second forwarding data base station can select the best forwarding target, and the data forwarding path is comprehensively optimized; using the target third forwarding data base station as the candidate second forwarding data base station to continuously optimize the forwarding path can further improve the stability of the network and the efficiency of data transmission, ensuring that data can be transmitted to the destination quickly and reliably; through the operation of the above steps, the subsequent forwarding data base stations of each candidate second forwarding data base station can be effectively acquired and optimized, thereby forming a fixed and fastest forwarding forwarding line of the subsequent forwarding data base station.

[0106] In summary, the present invention proposes a method and storage medium for dynamically processing multi-hop forwarding paths in a 5G network under cloud-edge collaboration. By optimizing the forwarding lines between data base stations, the data transmission efficiency of the entire network is improved and the delay of data transmission is reduced. While ensuring the quality of service, unnecessary data transmission distances and transfers are reduced, thereby effectively reducing operation and maintenance costs. The technical solution adopted in the above-mentioned embodiment of the present application automatically optimizes path selection through an algorithm, and has good scalability and flexibility.

[0107] Furthermore, during the specific implementation of the technical solution of the present application, by defining the maximum number of iterations and the iteration counter, a basic condition is provided for stopping the subsequent algorithm, ensuring that the algorithm can stop iteration after a sufficient number of iterations, thereby preventing overfitting. Furthermore, by placing ants at random positions near the data base station, the ants can begin searching for surrounding data base stations and exploring possible paths, thus laying the foundation for searching for the optimal route. The forwarding distance of the data forwarding route is used to calculate the transfer probability of the ants between different data base stations, helping each ant select the next update position and promoting the ants to move towards the target data base station.

[0108] By leveraging the characteristics of the ant algorithm and reducing the complex calculations of pheromones and heuristic search, the algorithm uses the distance of data forwarding routes to calculate the transfer probability of each ant, helping ants find the best forwarding route in the network, improving data transmission efficiency and network performance. Through iterative optimization, the optimal forwarding route is ultimately found, making data forwarding more efficient and reliable.

[0109] Furthermore, by calculating fitness and selecting the optimal base station based on considerations of line distance, the number of subsequent data forwarding base stations, and the data forwarding matrix, data forwarding optimization and network performance improvement can be achieved, and the target second data forwarding base station can be effectively selected. A simple fitness calculation method is used, eliminating the complex pheromone update calculation and the complex heuristic function probability calculation method in the original ant algorithm. The position of each ant is updated using the number of subsequent data forwarding base stations and line distance of each ant at the current second data forwarding base station, thereby improving the efficiency of machine selection and fully considering the number of subsequent data forwarding base stations of each ant, thereby selecting a more accurate target second data forwarding base station as the next update location.

[0110] In a further technical solution, by traversing the candidate second forwarding data base stations and obtaining a set of third forwarding data base stations, the potential forwarding targets of each second forwarding data base station can be effectively determined, preparing a data foundation for subsequent calculations; further screening to obtain the shortest distance d can help determine the optimal forwarding path, and by calculating the distance difference matching degree f', the advantages and disadvantages of each third forwarding data base station can be evaluated, which helps to select the most appropriate forwarding target; screening the target data base station according to 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 are traversed, it is ensured that each second forwarding data base station can select the best forwarding target, and the data forwarding path is comprehensively optimized; using the target third forwarding data base station as the candidate second forwarding data base station to continuously optimize the forwarding path can further improve network stability and data transmission efficiency, ensuring that data can be transmitted quickly and reliably to the destination; 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 forwarding line for the subsequent forwarding data base station.

[0111] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them. A person skilled in the art may modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements 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 dynamically processing multi-hop forwarding paths in 5G networking under cloud-edge collaboration, characterized in that: The steps are as follows: Obtain a data base station set in the current area; obtain a sending data base station and a target data base station in the data base station set; obtain a signal coverage range of each data base station in the data base station set; Acquire a forwarding line for data forwarding between every two data base stations and a line distance of each forwarding line based on the coordinate information of each data base station and the signal coverage range; According to the forwarding route, an ant algorithm is used to iteratively traverse each of the data base stations in the data base station set to obtain an optimal data forwarding route from the sending data base station to the target data base station.

2. The method for dynamically processing multi-hop forwarding paths in 5G networking under cloud-edge collaboration according to claim 1 is characterized in that: The step of iterating through each of the data base stations in the data base station set by an ant algorithm according to the forwarding route to obtain the optimal data forwarding route from the sending data base station to the target data base station includes the following steps: Setting a maximum number of iterations y and an iteration counter; wherein the number of iterations of the iteration counter is initially 0; Starting from the data sending base station, the initial position of each ant is obtained according to the signal coverage of the data sending base station; a taboo position table corresponding to each ant in each iteration is established, and the coordinate information of the data sending 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 of the data sending base station; Determine a second data forwarding base station for each of the ants according to the line distance; Repeat the above operation and update the taboo position table in each iteration; The target route is obtained by judging and analyzing the taboo position table and the iteration counter in each iteration.

3. The method for dynamically processing multi-hop forwarding paths in 5G networking under cloud-edge collaboration according to claim 2 is characterized in that: 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: Determine whether the target data base station is included in the taboo position table in each iteration; if so, establish a route set for each iteration; arrange the data base stations in the taboo position table in sequence to obtain the current ant's route for this iteration, and calculate the distance and number of data base stations of the current ant's route for this iteration; Put the current ant's iteration route into the iteration route set; If not, controlling the current ant to continue traversing the data base station until the taboo position table in each iteration includes the target data base station; Further determining whether each of the ants has obtained the current ant's iterative route; If so, obtaining the current ant's current iteration route with the shortest distance from the current ant's current iteration route in each current iteration route set as the target route to be selected; Putting the target line to be selected into a set of target lines to be selected; At the same time, the number of iterations of the iteration counter is increased by 1; Determine whether the number of iterations is greater than or equal to the maximum number of iterations y; If so, the current ant's current iteration route with the shortest distance from the current ant's current iteration route in the set of target routes to be selected is obtained 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 output the target line.

4. The method for dynamically processing multi-hop forwarding paths in 5G networking under cloud-edge collaboration according to claim 3 is characterized in that: The initial position of each ant is obtained according to the signal coverage range of the data sending 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 data sending base station; and each ant is randomly placed at a position corresponding to the coordinate information of each first forwarding data base station as the initial position of each ant.

5. The method for dynamically processing multi-hop forwarding paths in 5G networking under cloud-edge collaboration according to claim 4 is characterized in that: Determining the second data forwarding base station of each ant according to the line distance includes the following steps: Get the second data forwarding base station set P to be selected by each ant ij ={p i1 , p i2 , p i3 ,...p ij }; Among them, p ij is the jth selected second data forwarding base station for the i-th ant; Obtaining a subsequent data forwarding base station q corresponding to each of the second data forwarding base stations to be selected; and counting the number n of subsequent data forwarding base stations of each of the second data forwarding base stations to be selected; Obtaining a line distance m from the first data forwarding base station to each selected second data forwarding base station in the forwarding line of each ant; Constructing a data forwarding matrix based on the second data forwarding base station set to be selected and the line distance m ; The data forwarding matrix Expressed as: ； Calculating and obtaining the fitness f of each of the candidate second data forwarding base stations according to the data forwarding matrix and the number n of the subsequent data forwarding base stations; A target second data forwarding base station is obtained according to the fitness f.

6. The method for dynamically processing multi-hop forwarding paths in 5G networking under cloud-edge collaboration according to claim 5, characterized in that: Acquiring the target second data forwarding base station according to the fitness f is to select a candidate second data forwarding base station with the highest fitness as the target second data forwarding base station.

7. The method for dynamically processing multi-hop forwarding paths in 5G networking under cloud-edge collaboration according to claim 6 is characterized in that: The fitness f is calculated as follows: ； Wherein, n is the number of subsequent data forwarding base stations of the second data forwarding base station; is the data forwarding matrix, i' is the total number of ants, and i is the i-th ant.

8. The method for dynamically processing multi-hop forwarding paths in 5G networking under cloud-edge collaboration according to claim 7 is characterized in that: Obtaining the subsequent data forwarding base station q corresponding to each of the candidate second data forwarding base stations includes the following steps: Traversing each of the candidate second forwarding data base stations, obtaining a third forwarding data base station set K={k1, k2, k3, ...kt} of the candidate second forwarding data base station according to the signal coverage of the second forwarding data base station, where kt is the tth third forwarding data base station of the second forwarding data base station; Filter and obtain the shortest distance d according to the forwarding lines from the second data forwarding base station to each of the third data forwarding base stations and the line distances; Obtaining a distance difference matching degree f' of each of the third data forwarding base stations by calculation according to the shortest distance d and the third data forwarding base station set; According to the distance difference matching degree f' of each of the third data forwarding base stations, screening and obtaining the target third data forwarding base station corresponding to the second data forwarding base station; Repeat the above operation until all candidate second data forwarding base stations are traversed to obtain the target third data forwarding base station corresponding to each candidate second data forwarding base station; The target third forwarding data base station is used as the second forwarding data base station to be selected, 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, thereby obtaining subsequent forwarding data base stations corresponding to each of the second forwarding data base stations to be selected.

9. A storage medium, characterized in that: The storage medium includes a stored program, wherein, when the program is running, the device where the storage medium is located is controlled to execute a method for dynamic processing of multi-hop forwarding paths in 5G networking under cloud-edge collaboration as described in any one of claims 1 to 9.

Images