A miniaturized spn network planning and design method based on manhattan distance

Abstract

The application discloses a miniaturized SPN network planning and designing method based on Manhattan distance. In order to overcome the problems of insufficient deployment thickness, too long access distance and weak service opening effectiveness of the current SPN network designing method for group customer special line service, the application comprises the following steps: S1, building an SPN access layer network deployment model and inputting necessary key information; S2, calculating the economic benefit difference in two deployment scenarios; S3, total length algorithm of terminal optical cable routing; and S4, Manhattan minimum distance algorithm based on weighted multi-dimension. The SPN network is deployed in advance, the access distance of the group customer service is shortened, once the service is triggered, the service can be quickly accessed, and due to the short access distance, the probability of failure is reduced, and the service safety is high.

Description

Technical Field

[0001] This invention relates to the field of network planning and design, and more particularly to a miniaturized SPN network planning and design method based on Manhattan distance. Background Technology

[0002] Corporate leased line services are a major profit driver for telecom operators in the future. However, existing SPN networks have shortcomings in supporting convenient access for corporate leased line services, making it difficult to support the rapid development of corporate leased line services.

[0003] The mainstream transmission bearer network for telecommunications operators in the 4G era is the PTN network. The PTN network is divided into three layers: core layer, aggregation layer, and access layer. Since 4G base stations adopt the D-RAN mode of networking, the access layer PTN equipment is deployed in the base station equipment room. Therefore, the deployment scale of PTN equipment is large, the range is wide, and the deployment thickness is strong. The distance to the group's dedicated line customers is basically within 500 meters, which makes the service access very convenient.

[0004] The mainstream transmission network in the 5G era is the SPN network, which is also divided into three layers: core layer, aggregation layer, and access layer. However, 5G base stations mainly adopt the C-RAN mode for networking, with C-RAN accounting for more than 70%. Therefore, SPN deployment is more concentrated than PTN. Access layer SPN equipment is generally deployed in the service aggregation room, which is several hundred meters to 1.5 kilometers away from the group's dedicated line customers, resulting in poor service access convenience.

[0005] For example, a Chinese patent document, "A Method and System for Deploying an Access Layer Network" (publication number CN 106454859 A), discloses a method and system for deploying an access layer network. This method involves obtaining the probability values ​​of a newly built base station being connected to the nearest node in the access chain of the access layer network. It assumes that a next-generation network device is pre-placed on a target node in the access chain, where the target node is a current-generation network device node in the access chain. The method then obtains the path length values ​​of the newly built base station connecting to the nearest next-generation network device node on each of the aforementioned nodes, where the current next-generation network device nodes include the target node and existing next-generation network device nodes in the access chain. Based on the probability values ​​and the currently obtained path length values, the method determines the expected path value corresponding to the target node. Based on the expected path values ​​corresponding to each current-generation network device node, the method obtains the deployment scheme of the access layer network. This allows the node with the shortest expected path to be identified as a key node, and the pre-placement of next-generation network devices can shorten the fiber jumper distance between the newly built base station and the next-generation network device node, saving scarce fiber core resources between base stations. However, the SPN network design method for dedicated line services for corporate clients has problems such as insufficient deployment thickness, excessively long access distance, and weak service activation effectiveness.

[0006] In summary, traditional SPN network planning and design methods are no longer suitable for enterprise customer services, and there is an urgent need for a new SPN network planning and design method for enterprise leased line services. Summary of the Invention

[0007] This invention primarily addresses the problems of insufficient deployment thickness, excessively long access distances, and weak service activation effectiveness in current SPN network design methods for dedicated line services for corporate clients. It provides a miniaturized SPN network planning and design method based on Manhattan distance, which analyzes the geographical locations of potential clients, pre-deploys network coverage in densely populated service areas, and then enables service access based on the client's actual location when services are triggered. This achieves precise and rapid network construction, shortens the network construction cycle, accelerates network delivery, and enables rapid service activation.

[0008] The above-mentioned technical problems of the present invention are mainly solved by the following technical solutions:

[0009] A method for planning and designing miniaturized SPN networks based on Manhattan distance includes the following steps:

[0010] S1: Build an SPN access layer network deployment model that includes different deployment scenarios, and input the necessary key information;

[0011] S2: Calculate the economic benefits of each scenario based on the necessary key information under different deployment scenarios, and calculate the difference in economic benefits between scenarios;

[0012] S3: Select the deployment strategy with higher economic benefits based on the difference in economic benefits, that is, do not deploy SPN or deploy SPN.

[0013] S4: If the sunken SPN deployment is selected, the distance from each deployment location to the nearest secondary fiber distribution point is obtained according to the algorithm of the total length of the terminal optical cable route;

[0014] S5: The optimal location for the sunken HUB CPE is finally determined by the Manhattan minimum distance algorithm based on weighted multidimensionality.

[0015] This solution deploys the SPN network in advance to shorten the access distance for enterprise customers' services. Once a service is triggered, it can be quickly connected. Furthermore, due to the shorter access distance, the probability of failure is reduced, resulting in higher service security.

[0016] As a preferred option, key information includes the number of SPN dedicated lines N, the number of fiber cores F1 occupied from the customer room to the secondary fiber distribution point, and the total length of the optical cable route at the end of scenario i X. i The number of SPN CPEs deployed is E1, the number of HUB CPEs deployed is E2, and the number of SPN ports occupied in the upper-layer network is P.

[0017] As a preferred option, the deployment scenarios include both the SPN deployment scenario with and without being deployed in the lower-level SPN.

[0018] In the scenario of SPN deployment in the lower-level area, the customer end business first connects to the miniaturized HUB CPE in the area, and then connects to the upper level through the secondary fiber distribution point.

[0019] In non-downward SPN deployment scenarios, the customer terminal is directly connected to the secondary fiber distribution point, and then connected up level by level.

[0020] Preferably, step S2 includes the following steps:

[0021] S201: Define D(X1) as the economic benefit value of SPN access layer network deployment in the non-sinking SPN deployment scenario; define D(X2) as the economic benefit value of SPN access layer network deployment in the sinking SPN deployment scenario;

[0022] S202: Input key information into D(X1) to obtain:

[0023] D(X1) = 4N·X1·a + N·b + 2N·d

[0024] Where 'a' represents the economic value of each core per kilometer of optical cable;

[0025] b represents the economic value of each SPN CPE device;

[0026] c represents the economic value of each HUB CPE device;

[0027] d is the economic value of each upper-layer network SPN port;

[0028] S203: Input key information into D(X2) to obtain:

[0029]

[0030] Where θ is the maximum number of ports on the HUB CPE service board;

[0031] Indicates rounding up;

[0032] S204: Compare economic benefits by using the difference method to obtain the difference in economic benefits D(X1, X2).

[0033] As a preferred option, a deployment model is constructed to determine whether the economic benefit difference is greater than 0; if so, a sinking SPN deployment is selected, and the process proceeds to step S4 to calculate the deployment location; otherwise, a non-sinking SPN deployment is selected, and the process ends.

[0034] Preferably, step S3 includes the following process:

[0035] S301: Establish a coordinate system with N group customer locations and the secondary fiber distribution point as the origin, with the X-axis representing latitude and the Y-axis representing longitude;

[0036] S302: Calculate the total length X1 of the terminal optical cable route in the non-sinking SPN deployment scenario and the total length X2 of the terminal optical cable route in the sinking SPN deployment scenario, respectively.

[0037] S303: Substitute the calculated X1 and X2 into the deployment model to obtain a miniaturized SPN network plan related to the latitude and longitude of the group customer's location.

[0038] As a preferred option, the calculation process for the total length X1 of the terminal optical cable route in the non-submerged SPN deployment scenario is as follows:

[0039]

[0040] The calculation process for the total length of the terminal optical cable route X2 in the scenario of a sunken SPN deployment is as follows:

[0041]

[0042] The SPN network plan after substitution is as follows:

[0043]

[0044] Among them, (A0) lon B0 lat () represents the latitude and longitude of the secondary fiber splitting point;

[0045] (Ai lon Bi lat () represents the latitude and longitude of the i-th group customer location;

[0046] (AM lon BM lat ) represents the latitude and longitude of a random location among M group customer locations.

[0047] Preferably, a weight ω is set that takes into account both slope and curvature. i ;

[0048] Sort the x-coordinates of n group customer locations, calculate the sum of the location weights, and when... Stop at this time;

[0049] At this point, the previous position is the x-coordinate of the position that minimizes the distance;

[0050] Sort the y-coordinates of n group customer locations, calculate the sum of the location weights, and when... Stop at this time;

[0051] At this point, the previous position is the ordinate of the position that minimizes the distance;

[0052] The combination of the obtained horizontal and vertical coordinates is the solution of the weighted two-dimensional Manhattan distance that minimizes the sum of the distances from other group customer locations to it.

[0053] The beneficial effects of this invention are:

[0054] 1. Provide SPN network coverage planning strategies for business buildings and industrial parks in densely populated business areas through models, laying the network foundation for business development.

[0055] 2. By deploying the SPN network in advance, the access distance for enterprise customers' services is shortened. Once a service is triggered, it can be quickly connected. Furthermore, due to the shorter access distance, the probability of failure is reduced, resulting in higher service security.

[0056] 3. Compare the investment benefits of centralized and decentralized deployment of SPN access devices, and propose a reference threshold for decentralized deployment. When the volume of dedicated line services for enterprise customers exceeds the reference threshold, the decentralized deployment of SPN is more effective; otherwise, centralized deployment is more effective.

[0057] 4. Based on real business cases continuously input in practical applications, continuously revise system parameters and business models to improve planning accuracy and make them applicable to various scenarios. Attached Figure Description

[0058] Figure 1 This is a flowchart of the SPN network planning and design method of the present invention.

[0059] Figure 2 This is a network deployment model diagram of the SPN access layer of the present invention.

[0060] Figure 3 This is the quantized coordinate diagram of scenario 1 of the present invention.

[0061] Figure 4 This is the quantized coordinate diagram of scenario 2 of the present invention.

[0062] Figure 5 This is a coordinate map of an industrial park in an embodiment of the present invention.

[0063] Figure 6 This is a diagram showing the total distance of the optical cable route at the end of scenario 1 / 2 of this invention. Detailed Implementation

[0064] The technical solution of the present invention will be further described in detail below through embodiments and in conjunction with the accompanying drawings.

[0065] Example:

[0066] This embodiment presents a method for planning and designing a miniaturized SPN network based on Manhattan distance, such as... Figure 1 As shown, it includes the following steps:

[0067] S1: Build an SPN access layer network deployment model that includes different deployment scenarios and input the necessary key information.

[0068] like Figure 2 As shown, in this embodiment, there are two scenarios under the model.

[0069] Scenario 1: The customer terminal is directly connected to the secondary fiber distribution point, and then connected upstream through the trunk optical cable to the SPN equipment in the business aggregation room.

[0070] Scenario 2: Deploy a miniaturized HUB CPE within a certain area. Customer-end services first connect to the miniaturized HUB CPE, and then connect to the SPN equipment in the service aggregation room through the secondary fiber distribution point.

[0071] The established model needs to obtain the following input information for subsequent calculations. The input parameters of the model scenario are shown in Table 1.

[0072] Table 1. Model Input Parameters

[0073] Model input parameters Parameter Description N SPN Special Line Number <![CDATA[F1]]> Number of fiber cores used from customer room to secondary fiber distribution point <![CDATA[X1]]> Scenario 1: Total length of fiber optic cable route at the end <![CDATA[X2]]> Scenario 2: Total length of fiber optic cable route at the end <![CDATA[E1]]> SPN CPE deployment quantity <![CDATA[E2]]> Number of HUB CPE deployments P Number of SPN ports used in upper layer network

[0074] S2: Calculate the economic benefits of each scenario based on the necessary key information under different deployment scenarios, and calculate the difference in economic benefits between scenarios.

[0075] S201: Define D(X1) as the economic benefit value of SPN access layer network deployment in scenario 1.

[0076] Define D(X2) as the economic benefit value of SPN access layer network deployment in scenario 2.

[0077] S202: Input the following parameters for D(X1):

[0078] 1. Number of SPN dedicated lines, N;

[0079] N≥1, N∈N +

[0080] 2. Number of fiber cores occupied from the customer's room to the secondary fiber distribution point: F1;

[0081] Each optical cable route occupies 2 fiber cores (1 for receiving and 1 for transmitting), that is, N dedicated lines require F1 = 2 * 2 * N = 4N fiber cores.

[0082] 3. Total length of the fiber optic cable route at the end of scenario 1;

[0083] The total length of the N terminal optical cable routes is set to X1.

[0084] 4. SPN CPE deployment quantity E1;

[0085] N leased lines require N SPN CPEs to be deployed in the customer's data center, i.e., E1 = N.

[0086] 5. Number of HUB CPE deployments: E2;

[0087] Since scenario 1 does not converge services, there is no need to deploy a HUB CPE, i.e., E2=0.

[0088] 6. Number of SPN ports occupied in the upper-layer network, P;

[0089] Each SPN leased line needs to be dual-routed to the SPN upper-layer network device of the same service aggregation data center node, thus requiring P=2N ports.

[0090] Assuming the economic value of each fiber optic cable per core per kilometer is *a*, the economic value of each SPN CPE device is *b*, and the economic value of each HUB CPE device is *c*, then the economic value of each upper-layer network SPN port is *d*. Therefore, D(X1) is:

[0091] D(X1) = 4N·X1·a + N·b + 2N·d

[0092] S203: Input the following parameters for D(X2):

[0093] 1. Number of SPN dedicated lines, N;

[0094] N≥1, N∈N +

[0095] Scenario 2 uses HUB CPE to converge services, assuming the maximum number of ports on the HUB CPE service board is θ.

[0096] 2. Number of fiber cores occupied from the customer's room to the secondary fiber distribution point: F1;

[0097] Two fiber optic cables are routed from the customer's room where the HUB CPE is deployed to the secondary fiber distribution point. Each fiber optic cable route occupies 2 fiber cores (1 for receiving and 1 for transmitting). This means that regardless of the size of N, each HUB CPE requires 4 fiber cores. Therefore, because N dedicated lines need to be deployed... Taiwan HUB CPE, therefore N dedicated lines need to be occupied Core fiber core, among which This indicates rounding up to the nearest integer.

[0098] 3. Total length of the fiber optic cable route at the end of scenario 2;

[0099] The total length of the N terminal optical cable routes is set to X2.

[0100] 4. SPN CPE deployment quantity E1;

[0101] N dedicated lines require N SPN CPEs, but no additional CPEs are needed at the aggregation point, i.e., E1 = N - [N / θ].

[0102] 5. Number of HUB CPE deployments: E2;

[0103] Data from HUB CPE deployment required for N dedicated lines

[0104] 6. Number of SPN ports occupied in the upper-layer network, P;

[0105] Unlike Scenario 1, in Scenario 2, all services are aggregated at the HUB CPE before being connected to the SPN device in the service aggregation room. Therefore, each HUB CPE will occupy 2 ports, hence the number of upper-layer network SPN ports occupied.

[0106] Then, D(X2) is:

[0107]

[0108] S204: Compare the economic benefits of scenario 1 and scenario 2 using the difference method to obtain D(X). 1， X2):

[0109]

[0110] It can be simplified to:

[0111]

[0112] To further simplify:

[0113]

[0114] Where N, θ, a, b, c, and d are all constants, N is the number of dedicated lines, θ is the maximum number of ports on the HUB CPE service board, and a, b, c, and d are economic values. Therefore, an empirical method can be used to replace the equivalent multiples of a, b, c, and d with values ​​of the same type. Assuming... Therefore, D(X1, X2) can be further equivalent to:

[0115]

[0116] Right now:

[0117]

[0118] Since 4a > 0, to determine whether D(X1X2) is greater than 0, we only need to check...

[0119]

[0120] Therefore, in step S2, the economic value difference of the SPN access layer network deployment model under the two scenarios is constructed, so as to select the deployment strategy with higher economic benefits (sinking or not sinking the miniaturized SPN). If the strategy of sinking the miniaturized SPN is adopted, the deployment location of the sinking miniaturized SPN is further derived based on the mathematical model through the distance decision algorithm of X1 and X2 in step S3, and finally the complete and accurate SPN network planning and design results for the group's leased line business are output.

[0121] S3: Determine the deployment location in the miniaturized SPN deployment scenario based on the algorithm of the total length of the terminal optical cable route.

[0122] Taking the integrated service access area microgrid as the region, let the latitude and longitude of a certain secondary fiber distribution point within the region be (A0) lon B0 lat ), the latitude and longitude of N group customer locations are (A1) lon B1 lat )……(AN lon BN lat ).

[0123] like Figure 3 As shown, a coordinate system is established with the secondary fiber distribution point as the origin, connecting N group customer locations with the secondary fiber distribution point. The X-axis represents latitude, and the Y-axis represents longitude.

[0124] Therefore, an algorithm for the distance X1 can be established under scenario 1. Ideally, the total length of the end-point optical cable route is the sum of the perimeters of all rectangles, that is:

[0125]

[0126] like Figure 4 As shown, the same method is used to establish the coordinate system for Scene 2.

[0127] Then we can establish an algorithm for the X2 distance in scenario 2, assuming that the latitude and longitude of a random point among N group customer locations is (AM) lon BM lat Ideally, the total length of the final optical cable route is the sum of the perimeter of rectangle M and the perimeter of the rectangle formed by all points except the customer point M and point M, that is:

[0128]

[0129] Substituting the algorithms of X1 and X2 in step S3 into the deployment model of S2, we can obtain a miniaturized SPN network planning and design method related to the latitude and longitude of collective customer locations, namely:

[0130]

[0131] S4: The optimal location of the deployed HUB CPE is finally determined by the weighted multidimensional Manhattan minimum distance algorithm, thus completing a miniaturized SPN network planning and design based on multidimensional Manhattan distance.

[0132] Considering the deviation between the actual physical route and the ideal coordinates, a weighted calculation is performed on X2 to correct for minor deviations, with the weight set to ω. i Assume ω i =F(K i U i Considering that the actual route mainly follows municipal roads and pipelines, and is not a perfectly straight line distribution, there is a slope K between the distance from the ideal Manhattan matrix on the horizontal plane. i The functional relationship considers the latitude and longitude coordinates of the customer's location as Earth's curved surface coordinates, which exhibit curvature U when converted to the ideal Manhattan distance. i The functional relationship.

[0133] Therefore, the weighted optical cable route distance X′2 can be obtained, that is:

[0134]

[0135] Furthermore, the optical cable route distance between each point in X′2 can actually be regarded as the distance between the two points in the north-south direction plus the distance in the east-west direction, i.e., the Manhattan distance. Therefore, X′2 can be regarded as the sum of the weighted two-dimensional Manhattan distances of the coordinates of N group customer locations.

[0136] Furthermore, because there must exist a certain point M(AM) lon BM lat The sum of its Manhattan distances to all other points is minimized, i.e., X′2 is minimized.

[0137] On the x-axis, find the condition that... The smallest point M: Sort the x-coordinates of N points, assuming X k <M<x k+1 Then we have:

[0138]

[0139] Therefore, the factors affecting the change in distance X′2 are only subject to the weights, or more precisely, to the difference between the sum of the weights in the first half.

[0140] when When X′2(M)>X′2(k+1), the distance X′2 gradually decreases over the continuous interval;

[0141] when When X′2(M) < X′2(k+1), the distance X′2 gradually increases over the continuous interval; therefore, the point with the minimum distance satisfies and This means the position where the sum of the weights in the first half was originally less than the sum of the weights in the second half, and the relationship changes after adding the weight of the next position.

[0142] Therefore, for the weighted Manhattan distance, what needs to be done is to sort the n points, and then accumulate the weights until the weight on the left is greater than the weight on the right. At this point, the previous position is the x-coordinate of the position that minimizes the distance.

[0143] Similarly, each dimension can be considered separately. After sorting the n points along the vertical axis, the weights are accumulated until the weight on the left is greater than the weight on the right. At this point, the previous position is the vertical coordinate of the position that minimizes the distance.

[0144] Combining the above steps yields the solution that minimizes the weighted two-dimensional Manhattan distance X′2. That is:

[0145] First, the deployment model of the SPN access layer network is used to determine which scenario should adopt the strategy of deploying HUB CPE; then, if the strategy of deploying HUB CPE is determined, the distance formula X2 for this scenario is obtained according to the algorithm of the total length of the end optical cable route.

[0146] Finally, the optimal location of the deployed HUB CPE is determined by the weighted multidimensional Manhattan minimum distance algorithm, thus completing the planning and design of a miniaturized SPN network based on multidimensional Manhattan distance.

[0147] Taking an industrial park in a certain province as an example, such as Figure 5 As shown, the latitude and longitude of the secondary fiber distribution points and group customer points in the park are first converted into a coordinate system with the secondary fiber distribution points as the origin, that is, secondary fiber distribution point A (0,0), group customer point B (1,2), group customer point C (2,5), group customer point D (3,4), group customer point E (5,3), and group customer point F (4,6), for a total of 5 SPN dedicated lines, i.e., N=5.

[0148] Based on the multidimensional Manhattan distance, construct the total distance X1 of the end-point optical cable route in scenario 1 and the total distance X2 of the end-point optical cable route in scenario 2, and assume that the HUB CPE is deployed at points B, C, D, E, and F respectively, construct X2-B, X2-C, X2-D, X2-E, and X2-F respectively, as follows. Figure 6 As shown.

[0149] According to the conclusion of the analysis in step S2, the difference in economic benefits of the deployment model D(X1, X2) in the two scenarios is only related to the parameters X1, X2, N, and θ.

[0150] In this embodiment, the number of SPN leased lines N = 5, because the maximum number of ports θ of the HUB CPE service board is usually 8, 10, or 16 or more. This embodiment takes a major manufacturer as an example. Will Figure 6 The Manhattan distances of X1, X2-B, X2-C, X2-D, X2-E, and X2-F are shown in Table 2.

[0151] Table 2 Distance from Manhattan

[0152]

[0153]

[0154] According to the method proposed by the present invention, substituting X1, X2-B, X2-C, X2-D, X2-E, and X2-F into D(X1, X2) respectively yields the conclusion that D(X1, X2) > 0. That is, in the embodiment, scenario 2 should be adopted: sinking the SPN network to the campus.

[0155] 5·X1-1·X2>2.5+14

[0156] According to the method in step S4, each dimension is considered separately. After sorting the n points in the horizontal / vertical coordinate direction, the sum of the weights of the first half, which was originally less than the sum of the weights of the second half, is added to the weight of the next position, and the position where the size relationship changes is the position where the distance is minimized. At this time, the previous position is the vertical coordinate of the position where the distance is minimized. As shown in Table 3, according to the method in step S4, and considering that the industrial park in the embodiment is relatively regular and close to a grid distribution, the weight ω is... i If we consider it as a fixed value between 0 and 1, we can find that the sum of distances at customer point D is minimized, that is, point D is the optimal deployment location for HUB CPE. According to Table 2 above, in the embodiment, we can intuitively see that X2-D is minimized, thus verifying the accuracy of the planning and design method.

[0157] Table 3. Manhattan Distance Weighting Table

[0158]

[0159] The solution in this embodiment deploys the SPN network in advance to shorten the access distance for enterprise customer services. Once a service is triggered, it can be quickly connected. Furthermore, due to the shorter access distance, the probability of failure is reduced, resulting in higher service security.

[0160] It should be understood that the embodiments are for illustrative purposes only and are not intended to limit the scope of the invention. Furthermore, it should be understood that after reading the teachings of this invention, those skilled in the art can make various alterations or modifications to the invention, and these equivalent forms also fall within the scope defined by the appended claims.

Claims

1. A method for planning and designing miniaturized SPN networks based on Manhattan distance, characterized in that, Includes the following steps: S1: Build an SPN access layer network deployment model that includes different deployment scenarios, and input key information, including the number of SPN dedicated lines, the number of fiber cores occupied from the customer room to the secondary fiber distribution point, the total length of the optical cable route at the end of scenario i, the number of SPN CPE deployments, the number of HUBCPE deployments, and the number of SPN ports occupied in the upper layer network. S2: Calculate the cost of each scenario based on key information in different deployment scenarios, and calculate the cost difference between scenarios; Deployment scenarios include non-sinking SPN deployment scenarios and sinking SPN deployment scenarios. In non-sinking deployment scenarios, the customer terminal is directly connected to the secondary fiber distribution point and connected up level by level. In sinking deployment scenarios, the customer terminal service first connects to the miniaturized HUB CPE in the area, and then connects up level by level through the secondary fiber distribution point. S3: Determine if the cost difference is greater than 0; if so, select the SPN deployment that is pushed down and proceed to step S4; otherwise, select the SPN deployment that is not pushed down. S4: If the SPN deployment is selected, the distance from each potential deployment location to the nearest secondary fiber distribution point and the total length of the terminal optical cable route between each potential deployment location and each group customer location are calculated according to the algorithm of the total length of the terminal optical cable route. S5: Based on each potential sinking deployment location and the total length of the terminal optical cable route, the sinking deployment location that minimizes the total length of the terminal optical cable route from the group customer side to the HUB CPE is determined by setting weights based on slope and curvature for the group customer locations, sorting and accumulating weights in different dimensions to obtain the optimal coordinates and combining them.

2. The method for planning and designing a miniaturized SPN network based on Manhattan distance according to claim 1, characterized in that, Step S2 includes the following steps: Define D(X1) as the deployment cost of the SPN access layer network in the non-sinking SPN deployment scenario; Inputting key information into D(X1), we obtain: D(X1) = 4N·X1·a + N·b + 2N·d Where 'a' represents the cost per core per kilometer of optical cable; b represents the cost per SPN CPE device; d is the cost per upper-layer network SPN port.

3. The method for planning and designing a miniaturized SPN network based on Manhattan distance according to claim 2, characterized in that, Step S2 further includes the following steps: Define D(X2) as the deployment cost of the SPN access layer network in the sinking SPN deployment scenario; Inputting key information into D(X2), we obtain: Where θ is the maximum port count of the HUB CPE service board, and c is the cost of each HUB CPE device; This indicates rounding up to the nearest integer.

4. The method for planning and designing a miniaturized SPN network based on Manhattan distance according to claim 3, characterized in that, Step S2 further includes the following steps: By comparing the costs, we obtain the cost difference D(X1,X2): 。 5. The method for planning and designing a miniaturized SPN network based on Manhattan distance according to claim 1, characterized in that, Step S4 includes the following steps: With the secondary fiber distribution point as the origin, establish a coordinate system between the N group customer locations and the secondary fiber distribution point corresponding to the SPN dedicated line number N, with the X-axis representing latitude and the Y-axis representing longitude; Calculate the total length X1 of the terminal optical cable route in the non-sinking SPN deployment scenario and the total length X2 of the terminal optical cable route in the sinking SPN deployment scenario, respectively. Substitute the calculated X1 and X2 into the deployment model to obtain a miniaturized SPN network plan related to the latitude and longitude of the group's customer locations.

6. The method for planning and designing a miniaturized SPN network based on Manhattan distance according to claim 5, characterized in that, The calculation process for the total length X1 of the terminal optical cable route in a non-submerged SPN deployment scenario is as follows: ， The calculation process for the total length of the terminal optical cable route X2 in the scenario of a sunken SPN deployment is as follows: ， The SPN network plan after substitution is as follows: , among which, (A0) lon B0 lat () represents the latitude and longitude of the secondary fiber splitting point; (Ai lon ,Bi lat () represents the latitude and longitude of the i-th group customer location; (AM lon ,BM lat ) represents the latitude and longitude of a random location among N group customer locations.

7. The method for planning and designing a miniaturized SPN network based on Manhattan distance according to claim 1, characterized in that, In step S5, weights considering slope and curvature are set, and the horizontal and vertical coordinates of the group customer locations are sorted. The corresponding weights are accumulated for the sorted coordinates. When the sum of the accumulated weights is greater than the sum of the remaining unaccumulated weights for the first time, the accumulation stops. The position above the stopping position is taken as the optimal coordinate of the corresponding dimension. Finally, the optimal coordinates of the horizontal and vertical dimensions are combined to obtain the solution of minimizing the weighted two-dimensional Manhattan distance.

Images