A dual-mode network planning method and system based on graph partitioning

Abstract

The present invention discloses a dual-mode network planning method based on graph-theoretic segmentation, comprising the following steps: data preprocessing, screening out the first region and the second region of the dual-mode network; constructing a graph model, constructing a graph model for the first region, and obtaining a graph set containing multiple connected graphs; graph segmentation, segmenting the graph set containing multiple connected graphs into multiple small graphs with high cohesion and capacity sizes related to the gateway capacity size, and deploying at least one gateway for each small graph; post-processing, merging the regions in the graph segmentation results into adjacent regions, thereby optimizing the dual-mode network structure. The present invention also discloses a dual-mode network planning system based on graph-theoretic segmentation. The present invention solves the existing dual-mode network planning and gateway site selection problems, as well as the technical problem of how to improve network performance.

Description

Technical Field

[0001] The present invention relates to the field of communication network technology, and in particular to a dual-mode network planning method and system based on graph theory segmentation. Background Art

[0002] A dual-mode network refers to a network composed of wired power line carrier communication (PLC) as the main and wireless radio frequency (RF) as the auxiliary. The equipment in the substation area is connected by wired PLC, and the equipment between substations is connected by wireless RF. Power line carrier communication is a communication method unique to the power system. Power line carrier communication refers to the technology of using existing power lines to transmit analog or digital signals at high speed through carriers. The biggest feature is that there is no need to re-establish the network. As long as there are wires, data can be transmitted; wireless radio frequency refers to radio frequency. Radio frequency technology is a technology that uses radio waves for communication and is widely used in communication, radar, medical, industry and other fields. Since dual-mode networks need to support multiple communication standards and technologies at the same time, the equipment cost increases, and the complexity and maintenance difficulty of the network are also increased. Dual-mode networks of different scales, different structures and different needs cannot adapt to the needs of various scenarios. Therefore, it is urgent to propose a dual-mode network planning method and system based on graph theory segmentation to solve the planning and gateway site selection problems of existing dual-mode networks, as well as the technical problem of how to improve network performance. Summary of the invention

[0003] The main purpose of the present invention is to propose a dual-mode network planning method and system based on graph theory segmentation, aiming to solve the planning and gateway site selection problems of existing dual-mode networks, as well as the technical problem of how to improve network performance.

[0004] To achieve the above object, the present invention provides a dual-mode network planning method based on graph theory segmentation, wherein the dual-mode network planning method based on graph theory segmentation comprises the following steps:

[0005] S1, data preprocessing, screening out the first area and the second area of ​​the dual-mode network;

[0006] S2, constructing a graph model, constructing a graph model for the first region, and obtaining a graph set including a plurality of connected graphs;

[0007] S3, graph segmentation, segmenting the graph set containing multiple connected graphs into multiple small graphs with high cohesion and capacity related to the gateway capacity, and deploying at least one gateway for each small graph;

[0008] S4, post-processing, merges the regions in the graph segmentation results into adjacent regions, thereby optimizing the dual-mode network structure.

[0009] In one of the preferred solutions, the step S1 data preprocessing is specifically as follows:

[0010] S11. Get the maximum number of devices that can be connected to a gateway, that is, the gateway capacity ;

[0011] S12, filter out the number of devices in each area in the entire dual-mode network to select the first area set , the second area set and the third station area set ;

[0012] S13, for the first area Each station area is segmented based on the size-constrained clustering method, that is, the number of samples in the class is increased on the basis of k-means and is not greater than the gateway capacity. The constraints of the fourth station set are obtained and the Fifth District Collection , then the third station area set and the Fifth District Collection For the planned regional set, the second regional set and the fourth district set A collection of regions that require further processing.

[0013] In one of the preferred solutions, step S12 is specifically:

[0014] Collect statistics on the equipment data in each substation in the entire dual-mode network and filter out the equipment whose number is greater than the gateway capacity. +10 first zone set , The number of devices is less than the gateway capacity -10 second zone set And the third district set of the remaining districts .

[0015] One of the preferred solutions, step S13 is to Each station area is segmented based on the size-constrained clustering method, specifically:

[0016] Determine the number of clusters , Taiwan District Collection The first area set , among which, the area collection The number of devices in , then the number of clusters ;

[0017] Determining the size of the clusters ,in, ,like , then the size of a class is ,the remaining The size of the class is ,otherwise The size of each class is ; Where mod is the remainder function;

[0018] Solved by the minimum cost flow algorithm The capacity does not exceed The class of ; where the capacity is The class filter is the fourth zone set , the capacity is Class screening for the fifth zone set .

[0019] One of the preferred solutions, the step S13 determines the third station area set and the Fifth District Collection After the planned area set, it also includes:

[0020] Determine the third zone set and the Fifth District Collection is the planned area set T;

[0021] Calculate the gateway position of the region set T, the gateway position is:

[0022] ;

[0023] in, For Region All points within The square of the distance, The smallest position is the gateway position. , For Region Any two points, For Region The number of elements in .

[0024] In one of the preferred solutions, the step S2 constructs a graph model, specifically:

[0025] S21, the second station area set and the fourth district set A collection of regions that need further processing , the region collection The n elements in are regarded as the vertices of the graph, and the region set Conduct traversal;

[0026] S22. After the traversal is completed, a graph set containing multiple connected graphs is obtained. ;

[0027] S23. Filter out the atlas The number of devices in the gateway is less than the gateway capacity Gallery , Atlas For the planned area set, determine the atlas The gateway location;

[0028] S24. Filter out the atlas The number of devices in the gateway is greater than or equal to the gateway capacity Gallery , Gallery A collection of regions that require further processing.

[0029] In one preferred solution, the step S21 sets the area To traverse, specifically:

[0030] Choose an element , use the graph breadth-first algorithm to traverse the region set , combining the wireless radio frequency and elements in the dual-mode network Directly or indirectly connected vertices Add to collection , using the adjacency matrix Storage elements With Vertex The connection relationship and distance;

[0031] make = - ,like , then repeat the previous step, otherwise, end the traversal.

[0032] In one of the preferred solutions, step S3 uses a greedy algorithm to segment the graph set containing multiple connected graphs.

[0033] In one of the preferred solutions, the step S3 of graph segmentation is specifically as follows:

[0034] S31. Settings , is the small graph with the largest number of vertices in the iteration;

[0035] S32. Set a temporary collection ,from Select an element ,Bundle Join a temporary collection , the temporary collection The capacity is set to , according to the breadth-first strategy from the adjacency matrix Find the element with Connected and nearest elements ,like , then the element Join a temporary collection ,make , and then find the element Repeat the above steps for the next closest element until Or until all are found; if , then from the temporary collection Select an element in Repeat the above steps using the breadth-first strategy until Or no temporary collection could be found. Elements connected to the elements in the temporary set > ,but = Temporary collection ;in, , , For the gallery The collection in For the gallery The elements in For temporary collection The capacity, For elements The number of elements in ;

[0036] Repeat the above step S32 until the atlas is completed. Traversal of the elements in ;

[0037] S33. Obtain a small graph with high cohesion and a capacity related to the gateway capacity through step S32. , calculate the small graph The gateway location;

[0038] S34, Order = - ,like , then repeat steps S32-S33, otherwise the atlas segmentation is completed.

[0039] A dual-mode network planning system based on graph theory partitioning includes a dual-mode network planning method based on graph theory partitioning as described above.

[0040] In the above technical solution of the present invention, the dual-mode network planning method based on graph segmentation includes the following steps: data preprocessing, screening out the first area and the second area of ​​the dual-mode network; constructing a graph model, constructing a graph model for the first area, and obtaining a graph set containing multiple connected graphs; graph segmentation, segmenting the graph set containing multiple connected graphs into multiple small graphs with high cohesion and capacity sizes related to the gateway capacity size, and deploying at least one gateway for each small graph; post-processing, merging the areas in the graph segmentation results into adjacent areas, thereby optimizing the dual-mode network structure. The present invention solves the existing dual-mode network planning and gateway site selection problems, as well as the technical problem of how to improve network performance.

[0041] In the present invention, the k-means clustering method is used in the data preprocessing stage to transform the clustering problem into a network flow problem, so as to perform screening calculations through the minimum cost flow algorithm of graph theory; in the graph segmentation stage, a greedy strategy is adopted, combined with the adjacency matrix, and each step of decomposition selects a small graph from the iteration that contains the largest number of vertices, high cohesion and a capacity closest to the gateway capacity, so that the decomposed network structure is more superior, the number of gateways used is small, and the cost is low.

[0042] In the present invention, the dual-mode network is accurately divided into several sub-networks through the segmentation algorithm in graph theory, which helps to more reasonably allocate network resources, such as channels, bandwidth and transmission power, thereby improving resource utilization.

[0043] In the present invention, the divided sub-networks are relatively independent, which reduces the degree of coupling between them, helps to reduce the risk of fault propagation, and improves the stability and reliability of the network. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying any creative work.

[0045] Figure 1 A schematic diagram of a dual-mode network planning method based on graph theory partitioning according to an embodiment of the present invention.

[0046] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with the implementation methods and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0047] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0048] It should be noted that all directional indications (such as up, down, etc.) in the embodiments of the present invention are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0049] In addition, in the present invention, the descriptions such as "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" or "second" may explicitly or implicitly include at least one of the features.

[0050] Furthermore, the technical solutions between the various embodiments of the present invention may be combined with each other, but this must be based on the fact that they can be implemented by ordinary technicians in the field. When the combination of technical solutions is mutually contradictory or cannot be implemented, it should be deemed that such combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0051] See also Figure 1 According to one aspect of the present invention, the present invention provides a dual-mode network planning method based on graph theory partitioning, wherein the dual-mode network planning method based on graph theory partitioning comprises the following steps:

[0052] S1, data preprocessing, screening out the first area and the second area of ​​the dual-mode network;

[0053] S2, constructing a graph model, constructing a graph model for the first region, and obtaining a graph set including a plurality of connected graphs;

[0054] S3, graph segmentation, segmenting the graph set containing multiple connected graphs into multiple small graphs with high cohesion and capacity related to the gateway capacity, and deploying at least one gateway for each small graph;

[0055] S4, post-processing, merges the regions in the graph segmentation results into adjacent regions, thereby optimizing the dual-mode network structure.

[0056] Specifically, in this embodiment, the data preprocessing in step S1 is specifically as follows:

[0057] S11. Get the maximum number of devices that can be connected to a gateway, that is, the gateway capacity ;

[0058] S12, filter out the number of devices in each area in the entire dual-mode network to select the first area set , the second area set and the third station area set ;

[0059] S13, for the first area Each station area is segmented based on the size-constrained clustering method, that is, the number of samples in the class is increased on the basis of k-means and is not greater than the gateway capacity. The constraints of the fourth station set are obtained and the Fifth District Collection , then the third station area set and the Fifth District Collection For the planned regional set, the second regional set and the fourth district set A collection of regions that require further processing.

[0060] Specifically, in this embodiment, the gateway capacity The value is 1000, which is not specifically limited in the present invention and can be set according to actual needs.

[0061] Specifically, in this embodiment, the step S12 is specifically:

[0062] Collect statistics on the equipment data in each substation in the entire dual-mode network and filter out the equipment whose number is greater than the gateway capacity. +10 first zone set , The number of devices is less than the gateway capacity -10 second zone set And the third district set of the remaining districts .

[0063] Specifically, in this embodiment, the present invention increases the number of samples of the class based on k-means by no more than the gateway capacity. The k-mean clustering problem can be transformed into a network flow problem in graph theory, and can be calculated using the minimum cost flow algorithm.

[0064] Specifically, in this embodiment, step S13 performs the following operations on the first station area set: Each station area is segmented based on the size-constrained clustering method, specifically:

[0065] Determine the number of clusters , Taiwan District Collection The first area set , among which, the area collection The number of devices in , then the number of clusters ;

[0066] Determining the size of the clusters ,in, ,like , then the size of a class is ,the remaining The size of the class is ,otherwise The size of each class is ; Where mod is the remainder function;

[0067] Solved by the minimum cost flow algorithm The capacity does not exceed The class of ; where the capacity is The class filter is the fourth zone set , the capacity is Class screening for the fifth zone set .

[0068] Specifically, in this embodiment, step S13 determines the third station area set and the Fifth District Collection After the planned area set, it also includes:

[0069] Determine the third zone set and the Fifth District Collection is the planned area set T;

[0070] Calculate the gateway location of the area set T; the gateway location is located at the confidence of the area, that is, the place with the most dense devices; the gateway location is:

[0071] ;

[0072] in, For Region All points within The square of the distance, The smallest position is the gateway position. , For Region Any two points, For Region The number of elements in .

[0073] Specifically, in this embodiment, the step S2 constructs a graph model, specifically:

[0074] S21, the second station area set and the fourth district set A collection of regions that need further processing , the region collection The n elements in are regarded as the vertices of the graph, and the region set Conduct traversal;

[0075] S22. After the traversal is completed, a graph set containing multiple connected graphs is obtained. ;

[0076] S23. Filter out the atlas The number of devices in the gateway is less than the gateway capacity Gallery , Gallery is a set of planned regions, and the atlas is calculated The gateway location;

[0077] S24. Filter out the atlas The number of devices in the gateway is greater than or equal to the gateway capacity Gallery , Gallery A collection of regions that require further processing.

[0078] Specifically, in this embodiment, step S21 performs a region set To traverse, specifically:

[0079] Choose an element , use the graph breadth-first algorithm to traverse the region set , combining the wireless radio frequency and elements in the dual-mode network Directly or indirectly connected vertices Add to collection , using the adjacency matrix Storage elements With Vertex The connection relationship and distance of; where 1≤i≤n, , The number of devices in ;

[0080] make = - ,like , then repeat the previous step, otherwise, end the traversal.

[0081] Specifically, in this embodiment, , , for the atlas Split into high cohesion, that is, the vertices in the graph are closely adjacent and the capacity is close to the gateway capacity There are multiple small graphs, and each small graph deploys a gateway. This network structure is the optimal network structure, and the number of gateways used is small and the cost is low. However, the time complexity of the optimal solution to this problem is exponential. Therefore, the present invention adopts a greedy algorithm strategy to segment the graph set containing multiple connected graphs to determine the optimal solution.

[0082] Specifically, in this embodiment, the step S3 of graph segmentation is specifically as follows:

[0083] S31. Settings , is the small graph with the largest number of vertices in the iteration;

[0084] S32. Set a temporary collection ,from Select an element ,Bundle Join a temporary collection , the temporary collection The capacity is set to , according to the breadth-first strategy from the adjacency matrix Find the element with Connected and nearest elements ,like , then the element Join a temporary collection ,make , and then find the element Repeat the above steps for the next closest element until Or until all are found; if , then from the temporary collection Select an element in Repeat the above steps using the breadth-first strategy, where: ≠ , until Or no temporary collection could be found. Elements connected to the elements in the temporary set > ,but = Temporary collection ;in, , , For the gallery The collection in For the gallery The elements in For temporary collection The capacity, For elements The number of elements in ;

[0085] Repeat the above step S32 until the atlas is completed. Traversal of the elements in ;

[0086] S33. Obtain a small graph with high cohesion and a capacity related to the gateway capacity through step S32. , calculate the small graph The gateway location;

[0087] S34, Order = - ,like , then repeat steps S32-S33, otherwise the atlas segmentation is completed.

[0088] Specifically, in this embodiment, the regions in the segmentation results are merged to obtain an optimized dual-mode network structure; the present invention adopts a dual-mode collaborative working mechanism to enable different communication technologies to complement each other and work together, which helps to improve the overall performance of the network and meet the needs of various application scenarios; and the dual-mode network planning method based on graph theory segmentation described in the present invention is suitable for dual-mode networks of different scales, different structures and different needs. For example, if the station cannot be connected via wireless radio frequency, it can be considered to add a relay to connect with slight modifications.

[0089] According to another aspect of the present invention, the present invention provides a dual-mode network planning system based on graph theory partitioning, wherein the dual-mode network planning system based on graph theory partitioning includes a dual-mode network planning method based on graph theory partitioning as described above.

[0090] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. All equivalent structural changes made using the contents of the present invention's specification and drawings, or directly / indirectly applied in other related technical fields, are included in the patent protection scope of the present invention.

Claims

1. A dual-mode network planning method based on graph theory segmentation, characterized in that: The following steps are involved: S1, data preprocessing, screening out the first area and the second area of ​​the dual-mode network; the step S1 data preprocessing is specifically as follows: S11. Get the maximum number of devices that can be connected to a gateway, that is, the gateway capacity ; S12, filter out the number of devices in each area in the entire dual-mode network to select the first area set , the second area set and the third station area set ; S13, for the first area Each station area is segmented based on the size-constrained clustering method, that is, the number of samples in the class is increased on the basis of k-means and is not greater than the gateway capacity. The constraints of the fourth station set are obtained and the Fifth District Collection , then the third station area set and the Fifth District Collection For the planned regional set, the second regional set and the fourth district set A collection of regions that require further processing; S2, constructing a graph model, constructing a graph model for the first region, and obtaining a graph set including a plurality of connected graphs; S3, graph segmentation, segmenting the graph set containing multiple connected graphs into multiple small graphs with high cohesion and capacity related to the gateway capacity, and deploying at least one gateway for each small graph; S4, post-processing, merges the regions in the graph segmentation results into adjacent regions, thereby optimizing the dual-mode network structure.

2. According to claim 1, a dual-mode network planning method based on graph theory segmentation is characterized in that: The step S12 is specifically: Collect statistics on the equipment data in each substation in the entire dual-mode network and filter out the equipment whose number is greater than the gateway capacity. +10 first zone set , The number of devices is less than the gateway capacity -10 second zone set And the third district set of the remaining districts .

3. According to the dual-mode network planning method based on graph theory segmentation according to claim 1, it is characterized in that: The step S13 performs a Each station area is segmented based on the size-constrained clustering method, specifically: Determine the number of clusters , Taiwan District Collection The first area set , among which, the area The number of devices in , then the number of clusters ; Determining the size of the clusters ,in, ,like , then the size of a class is ,the remaining The size of the class is ,otherwise The size of each class is ; Where mod is the remainder function; Solved by the minimum cost flow algorithm The capacity does not exceed The class of ; where the capacity is The class filter is the fourth zone set , the capacity is Class screening for the fifth zone set .

4. A dual-mode network planning method based on graph partitioning according to claim 3, characterized in that: The step S13 determines the third zone set and the Fifth District Collection After the planned area set, it also includes: Determine the third zone set and the Fifth District Collection is the planned area set T; Calculate the gateway position of the region set T, the gateway position is: ； in, For Region All points within The sum of the squares of the distances, The smallest position is the gateway position. , For Region Any two points, For Region The number of elements in .

5. The dual-mode network planning method based on graph partitioning according to claim 1 is characterized in that: The step S2 constructs a graph model, specifically: S21, the second station area set and the fourth district set A collection of regions that need further processing , the region collection The n elements in are regarded as the vertices of the graph, and the region set Conduct traversal; S22. After the traversal is completed, a graph set containing multiple connected graphs is obtained. ; S23. Filter out the atlas The number of devices in the gateway is less than the gateway capacity Gallery , Gallery For the planned area set, determine the atlas The gateway location; S24. Filter out the atlas The number of devices in the gateway is greater than or equal to the gateway capacity Gallery , Gallery A collection of regions that require further processing.

6. A dual-mode network planning method based on graph theory segmentation according to claim 5, characterized in that: The step S21 sets the area To traverse, specifically: Choose an element , use the graph breadth-first algorithm to traverse the region set , combining the wireless radio frequency and elements in the dual-mode network Directly or indirectly connected vertices Add to collection , using the adjacency matrix Storage elements With Vertex The connection relationship and distance; make = - ,like , then repeat the previous step, otherwise, end the traversal.

7. A dual-mode network planning method based on graph partitioning according to any one of claims 1 to 6, characterized in that: The step S3 uses a greedy algorithm to segment the graph set containing multiple connected graphs.

8. A dual-mode network planning method based on graph partitioning according to claim 5, characterized in that: The step S3 of graph segmentation is specifically as follows: S31. Settings = , is the small graph with the largest number of vertices in the iteration; S32. Set a temporary collection ,from Select an element ,Bundle Join a temporary collection , the temporary collection The capacity is set to , according to the breadth-first strategy from the adjacency matrix Find the element with Connected and nearest elements ,like , then the element Join a temporary collection ,make , and then find the element Repeat the above steps for the next closest element until Or until all are found; if , then from the temporary collection Select an element in Repeat the above steps using the breadth-first strategy until Or no temporary collection could be found. Elements connected to the elements in the temporary set > ,but = Temporary collection ;in, , , For the gallery The collection in For the gallery The elements in For temporary collection The capacity, For elements The number of elements in ; Repeat the above step S32 until the atlas is completed. Traversal of the elements in ; S33. Obtain a small graph with high cohesion and a capacity related to the gateway capacity through step S32. , calculate the small graph The gateway location; S34, Order = - ,like , then repeat steps S32-S33, otherwise the atlas segmentation is completed.

9. A dual-mode network planning system based on graph partitioning, characterized in that: The dual-mode network planning system based on graph theory partitioning includes a dual-mode network planning method based on graph theory partitioning as described in any one of claims 1-8.

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