Optimal path selection method and apparatus

Abstract

The application provides an optimal path selection method and device, and relates to the technical field of communication. The method comprises the following steps: when an optimal path from a source network node to a destination network node through a plurality of intermediate network nodes is determined, a first vector set is constructed based on a preset network topology graph; a target intersection region is determined from the preset network topology graph based on a first vector representation between the source network node and the destination network node, the first vector set, and a second vector set symmetrical to the first vector set; relevant information of a network node pair including the target network node is removed from a network topology graph evaluation matrix corresponding to the preset network topology graph; and the optimal path is determined from the target intersection region based on the updated network topology graph evaluation matrix. In this way, the network topology graph evaluation matrix corresponding to the preset network topology graph is compressed, and the optimal path is selected based on the updated network topology graph evaluation matrix, so that the selection efficiency of the optimal path can be effectively improved.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to an optimal path selection method and apparatus. Background Technology

[0002] In business transmission scenarios, the choice of transmission path affects the quality of business transmission. To ensure the quality of business transmission, it is usually necessary to select an optimal path from the source node to the destination node based on the business transmission requirements.

[0003] After selecting the optimal path, bandwidth and wavelength can be allocated to each segment of the optimal path based on constraints such as bandwidth utilization and wavelength consistency. This allows for service transmission based on the bandwidth and wavelength of each segment. Therefore, efficiently selecting the optimal path is crucial. Summary of the Invention

[0004] This application provides an optimal path selection method and apparatus, which can efficiently determine the optimal path, thereby improving the efficiency of optimal path selection.

[0005] This application provides an optimal path selection method, which may include:

[0006] Receive an input optimal path selection request, which is used to request the optimal path from the source network node, through multiple intermediate network nodes in sequence, to the destination network node.

[0007] Based on a preset network topology, a first vector set is constructed. The first vector set includes, in sequence, a first vector representation between the source network node and the destination network node, and multiple second vector representations between two adjacent network nodes among the source network node, the plurality of intermediate network nodes, and the destination network node.

[0008] Based on the first vector representation, the first vector set, and a second vector set that is symmetric to the first vector set with respect to the first vector representation, the target intersection region is determined from the preset network topology graph;

[0009] From the network topology evaluation matrix corresponding to the preset network topology map, remove the relevant information of network node pairs including the target network node to obtain the updated network topology evaluation matrix. The target network node is a node located outside the target intersection region. The network topology evaluation matrix includes the relevant information of all network node pairs with direct link relationships in the preset network topology map. The relevant information includes the identifier and evaluation value of each network node in the network node pair, and the identifier and evaluation value of the direct link.

[0010] The optimal path is determined from the target intersection region based on the updated network topology evaluation matrix.

[0011] According to an embodiment of this application, an optimal path selection method is provided, wherein determining a target intersection region from a preset network topology map based on a first vector representation, a first vector set, and a second vector set symmetric to the first vector set about the first vector representation includes:

[0012] From the preset network topology diagram, determine the first region shared by the first vector set and the second vector set;

[0013] From the preset network topology diagram, determine the second region formed by the first vector representation and the second vector set;

[0014] The target intersection region is determined by the intersection of the first region and the second region.

[0015] According to an embodiment of this application, an optimal path selection method is provided, wherein determining the optimal path from the target intersection region based on the updated network topology graph evaluation matrix includes:

[0016] From the target intersection region, determine multiple candidate paths including the source network node, the multiple intermediate network nodes, and the destination network node;

[0017] Based on the updated network topology evaluation matrix, determine the path evaluation value corresponding to each candidate path;

[0018] The candidate path corresponding to the maximum path evaluation value is determined as the optimal path.

[0019] According to an embodiment of this application, an optimal path selection method is provided, wherein determining the path evaluation value corresponding to each candidate path based on the updated network topology evaluation matrix includes:

[0020] For each candidate path, the evaluation values ​​of each network node included in the candidate path and the evaluation values ​​of each segment of the candidate path are found from the updated network topology evaluation matrix.

[0021] Based on the evaluation values ​​of each network node and each path segment, the path evaluation value corresponding to the candidate path is determined.

[0022] According to an embodiment of this application, an optimal path selection method is provided, wherein determining the path evaluation value corresponding to the candidate path based on the evaluation values ​​of each network node and the evaluation values ​​of each path segment includes:

[0023] Based on the evaluation values ​​of each network node and the number of network nodes included in the candidate path, a first average evaluation value corresponding to the candidate path is determined.

[0024] Based on the evaluation values ​​of each path segment and the number of path segments included in the candidate path, a second average evaluation value corresponding to the candidate path is determined.

[0025] The sum of the first average evaluation value and the second average evaluation value is determined as the path evaluation value corresponding to the candidate path.

[0026] According to an embodiment of this application, an optimal path selection method is provided, the method further includes:

[0027] Based on the preset network topology map, a corresponding network topology map matrix is ​​constructed. The network topology map matrix includes the initial information of all network node pairs with direct link relationships in the preset network topology map. The initial information includes the identifier of each network node in the network node pair, the identifier of the direct link, and the distance of the direct link. Each network node has multiple node parameters and multiple link parameters.

[0028] Based on the subjective analytic hierarchy process (AHP) and the objective entropy weight method (EWM), the weights of each node parameter and each link parameter among the multiple node parameters are determined.

[0029] For each pair of network nodes in the network topology graph matrix, the evaluation value of the network node is determined based on multiple node parameters of the network node in the pair and the weight of each node parameter. The evaluation value of the direct link is determined based on multiple link parameters of the network node and the weight of each link parameter.

[0030] The evaluation values ​​of the network nodes and the evaluation values ​​of the direct links in each network node pair are added to the initial relevant information of each network node, and the distance of the direct links is removed from the added relevant information to obtain the network topology evaluation matrix.

[0031] According to an embodiment of this application, an optimal path selection method is provided, wherein determining the weight of each node parameter among the plurality of node parameters based on the subjective analytic hierarchy process (AHP) and the objective entropy weight method (EWM) includes:

[0032] For each node parameter, a first weight corresponding to the node parameter is determined based on AHP, and a second weight corresponding to the node parameter is determined based on EWM;

[0033] The average of the first weight and the second weight is determined as the weight of the node parameter.

[0034] This application embodiment also provides an optimal path selection device, which may include:

[0035] The receiving unit is used to receive an input optimal path selection request, which requests the optimal path from the source network node, through multiple intermediate network nodes, to the destination network node.

[0036] The first construction unit is used to construct a first vector set based on a preset network topology diagram. The first vector set includes, in sequence, a first vector representation between the source network node and the destination network node, and multiple second vector representations between two adjacent network nodes among the source network node, the plurality of intermediate network nodes, and the destination network node.

[0037] The first processing unit is configured to determine a target intersection region from the preset network topology graph based on the first vector representation, the first vector set, and a second vector set that is symmetric to the first vector set about the first vector representation.

[0038] The elimination unit is used to eliminate relevant information of network node pairs including target network nodes from the network topology evaluation matrix corresponding to the preset network topology map, so as to obtain an updated network topology evaluation matrix. The target network node is a node located outside the target intersection region. The network topology evaluation matrix includes relevant information of all network node pairs with direct link relationships in the preset network topology map. The relevant information includes the identifier and evaluation value of each network node in the network node pair, and the identifier and evaluation value of the direct link.

[0039] The second processing unit is used to determine the optimal path from the target intersection region based on the updated network topology evaluation matrix.

[0040] According to an embodiment of this application, an optimal path selection device is provided, wherein the first processing unit is specifically used for:

[0041] From the preset network topology diagram, determine a first region shared by the first vector set and the second vector set; from the preset network topology diagram, determine a second region formed by the first vector representation and the second vector set; and determine the target intersection region by finding the intersection region of the first region and the second region.

[0042] According to an embodiment of this application, an optimal path selection device is provided, wherein the second processing unit is specifically used for:

[0043] From the target intersection region, multiple candidate paths are determined, including the source network node, the multiple intermediate network nodes, and the destination network node; based on the updated network topology graph evaluation matrix, the path evaluation value corresponding to each candidate path is determined; the candidate path corresponding to the maximum path evaluation value is determined as the optimal path.

[0044] According to an embodiment of this application, an optimal path selection device is provided, wherein the second processing unit is specifically used for:

[0045] For each candidate path, the evaluation values ​​of each network node included in the candidate path and the evaluation values ​​of each segment of the candidate path are found from the updated network topology evaluation matrix; based on the evaluation values ​​of each network node and the evaluation values ​​of each segment of the candidate path, the path evaluation value corresponding to the candidate path is determined.

[0046] According to an embodiment of this application, an optimal path selection device is provided, wherein the second processing unit is specifically used for:

[0047] Based on the evaluation values ​​of each network node and the number of network nodes included in the candidate path, a first average evaluation value corresponding to the candidate path is determined; based on the evaluation values ​​of each segment path and the number of segment paths included in the candidate path, a second average evaluation value corresponding to the candidate path is determined; the sum of the first average evaluation value and the second average evaluation value is determined as the path evaluation value corresponding to the candidate path.

[0048] According to an embodiment of this application, an optimal path selection device is provided, which further includes a second construction unit, a third processing unit, a fourth processing unit, and a fifth processing unit.

[0049] The second construction unit is used to construct a corresponding network topology matrix based on the preset network topology map. The network topology matrix includes the initial information of all network node pairs with direct link relationships in the preset network topology map. The initial information includes the identifier of each network node in the network node pair, the identifier of the direct link, and the distance of the direct link. Each network node has multiple node parameters and multiple link parameters.

[0050] The third processing unit is used to determine the weight of each node parameter among the multiple node parameters and the weight of each link parameter among the multiple link parameters based on the subjective analytic hierarchy process (AHP) and the objective entropy weight method (EWM).

[0051] The fourth processing unit is used to determine the evaluation value of each network node pair in the network topology graph matrix based on multiple node parameters and weights of each node parameter, and to determine the evaluation value of the direct link based on multiple link parameters and weights of each link parameter.

[0052] The fifth processing unit is used to supplement the evaluation values ​​of the network nodes and the evaluation values ​​of the direct links in each network node pair into the initial relevant information of each network node, and remove the distance of the direct links from the supplemented relevant information to obtain the network topology evaluation matrix.

[0053] According to an embodiment of this application, an optimal path selection device is provided, wherein the third processing unit is specifically used for:

[0054] For each node parameter, a first weight is determined based on AHP, and a second weight is determined based on EWM; the average of the first weight and the second weight is determined as the weight of the node parameter.

[0055] This application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the optimal path selection method as described above.

[0056] This application also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the optimal path selection method as described above.

[0057] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the optimal path selection method as described above.

[0058] This application provides an optimal path selection method and apparatus. When determining the optimal path from a source network node, passing through multiple intermediate network nodes to reach a destination network node, a first vector set is first constructed based on a preset network topology graph. Based on the first vector representation between the source network node and the destination node, the first vector set, and a second vector set symmetric to the first vector set about the first vector representation, a target intersection region is determined from the preset network topology graph. Then, from the network topology graph evaluation matrix corresponding to the preset network topology graph, information related to network node pairs including the target network node is removed. Finally, based on the updated network topology graph evaluation matrix, the optimal path is determined from the target intersection region. This method effectively improves the efficiency of optimal path selection by compressing the network topology graph evaluation matrix corresponding to the preset network topology graph through the target intersection region and selecting the optimal path based on the updated network topology graph evaluation matrix. Attached Figure Description

[0059] To more clearly illustrate the technical solutions in this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0060] Figure 1 A flowchart illustrating an optimal path selection method provided in an embodiment of this application;

[0061] Figure 2 This application provides a schematic diagram of a preset network topology.

[0062] Figure 3 A network topology diagram with intermediate network nodes marked is provided for an embodiment of this application;

[0063] Figure 4 An embodiment of this application provides a first vector representation. Network topology diagram;

[0064] Figure 5 A network topology diagram with routing areas marked is provided for an embodiment of this application;

[0065] Figure 6 A network topology diagram with target intersection regions marked, provided as an embodiment of this application;

[0066] Figure 7 A schematic diagram of a network topology marked with the optimal path is provided for an embodiment of this application;

[0067] Figure 8A flowchart illustrating a method for constructing a network topology graph evaluation matrix provided in an embodiment of this application;

[0068] Figure 9 This is a schematic diagram of the structure of an optimal path selection device provided in an embodiment of this application;

[0069] Figure 10 This is a schematic diagram of the physical structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0070] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0071] In the embodiments of this application, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone, where A and B can be singular or plural. In the textual description of this application, the character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0072] The technical solutions provided in this application can be applied to service transmission scenarios. In service transmission scenarios, the choice of transmission path affects the service transmission effect. To ensure the service transmission effect, it is usually necessary to select an optimal path from the source node to the destination node according to the service transmission requirements.

[0073] After selecting the optimal path, bandwidth and wavelength can be allocated to each segment of the optimal path based on constraints such as bandwidth utilization and wavelength consistency. This allows for service transmission based on the bandwidth and wavelength of each segment. Therefore, efficiently selecting the optimal path is crucial.

[0074] To efficiently select the optimal path and thus improve the efficiency of optimal path selection, this application provides an optimal path selection method. The following specific embodiments will describe the optimal path selection method provided by this application in detail. It is understood that these specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0075] Example 1

[0076] Figure 1 This is a flowchart illustrating an optimal path selection method provided in an embodiment of this application. This optimal path selection method can be executed by software and / or hardware devices. For an example, please refer to [link to example]. Figure 1 As shown, the optimal path selection method may include:

[0077] S101. Receive the input optimal path selection request. The optimal path selection request is used to request the optimal path from the source network node, through multiple intermediate network nodes in sequence, to the destination network node.

[0078] In this context, the source network node can be understood as the starting node of service transmission in the network, the destination network node can be the ending node of service transmission, and the intermediate network node can be understood as a node that assists the source network node in service transmission. In this embodiment, it can play a role in assisting in compressing the network topology.

[0079] S102. Based on the preset network topology, construct a first vector set, which includes, in sequence, a first vector representation between the source network node and the destination network node, and, among the source network node, multiple intermediate network nodes, and the destination network node, multiple second vector representations between two adjacent network nodes.

[0080] The preset network topology diagram can be pre-built, which is a network structure diagram that includes network nodes with direct or indirect link relationships, constructed based on the link relationships between all network nodes in the network.

[0081] For example, assuming the network includes 16 network nodes, a preset network topology diagram corresponding to these 16 network nodes can be constructed based on the link relationships between them. See also [example diagram]. Figure 2 As shown, Figure 2 This is a schematic diagram of a preset network topology provided in an embodiment of this application, combined with... Figure 2 It can be seen that there is a direct link between network node 1 and network node 2, a direct link between network node 2 and network node 9, an indirect link between network node 1 and network node 6, and a direct link between network node 6 and network node 15, etc.

[0082] For example, in this embodiment of the application, it is assumed that the source network node is denoted as n. s The destination network node is denoted as n. t Therefore, when constructing the first vector set, the source network node n can be determined separately. s to destination network node n t The first vector representation between them can be denoted as: Source network node n s The second vector representation between the first intermediate network node and the first intermediate network node can be denoted as... intermediate node n i To intermediate node n j The second vector between them is represented as From the last intermediate node to the destination network node n t The second vector between them is represented as Correspondingly, the first vector set V can be constructed using the following formula 1:

[0083]

[0084] Combination Figure 2 The shown preset network topology assumes that the optimal path selection request is for a path starting from network node 1, passing through network nodes 9 and 14 in sequence, and reaching network node 16. Here, network node 1 is the source network node n. s Network nodes 9 and 14 are intermediate network nodes. Network node 9 can be denoted as intermediate network node n1, and network node 14 can be denoted as intermediate network node n2. Network node 16 is the destination network node n. t For example, see Figure 3 As shown, Figure 3 A network topology diagram with intermediate network nodes provided in this application embodiment can be represented by the first vector set V constructed by the following formula 2:

[0085]

[0086] Among them, in formula 2 This represents the first vector representation between source network node 1 and network node 16. For example, see [link to example]. Figure 4 As shown, Figure 4 An embodiment of this application provides a first vector representation. Network topology diagram, The second vector represents the distance between source network node 1 and network node 9. The second vector represents the data between network nodes 9 and 14. The second vector representation represents the distance between network node 14 and network node 16.

[0087] After constructing the first vector set, the following step S103 can be executed:

[0088] S103. Based on the first vector representation, the first vector set, and the second vector set that is symmetric to the first vector set about the first vector representation, determine the target intersection region from the preset network topology diagram.

[0089] For example, in the embodiments of this application, when determining the target intersection region from a preset network topology diagram based on a first vector representation, a first vector set, and a second vector set symmetrical to the first vector set about the first vector representation, a first region common to the first vector set and the second vector set can be determined from the preset network topology diagram; a second region composed of the first vector representation and the second vector set can be determined from the preset network topology diagram; and the intersection region of the first region and the second region can be used to determine the target intersection region.

[0090] Based on the description in S102 above, for example, in an embodiment of this application, assume a first vector set Then the second vector set U corresponding to the first vector set can be represented by the following formula 3:

[0091]

[0092] in, Indicates the source network node n s to destination network node n t The first vector representation between about Symmetric vector representation, Indicates the source network node n s The second vector representation between the first intermediate network node and the first intermediate network node about Symmetric vector representation, Indicates the intermediate node n i To intermediate node n j The second vector representation between about Symmetric vector representation, This represents the distance from the last intermediate node to the destination network node n. t The second vector representation between about Symmetric vector representation.

[0093] For example, in this embodiment of the application, it is assumed that the first region common to the first vector set and the second vector set determined from the preset network topology diagram can be denoted as T1, the second region formed by the first vector representation and the second vector set determined from the preset network topology diagram can be denoted as T2, and the target intersection region of the first region and the second region can be denoted as T, which can be represented by the following formula 4:

[0094]

[0095] Among them, Λ k Indicates the intermediate node n i To intermediate node n j The second vector representation between and The area that constitutes.

[0096] Combination Figure 2 The preset network topology shown assumes that the optimal path selection request is used to request an optimal path starting from network node 1, passing through network nodes 9 and 14 in sequence, and reaching network node 16, based on the first vector representation between the source network node 1 and network node 16. The second vector representation between source network node 1 and network node 9 The second vector representation between network node 9 and network node 14 The second vector representation between network node 14 and network node 16 The divided routing areas can be found in [reference]. Figure 5 As shown, Figure 5 This application provides a network topology diagram with routed areas marked. Using the aforementioned method for determining the target intersection area, the corresponding determined target intersection area T can be found in [reference needed]. Figure 6 As shown, Figure 6 This application provides a network topology diagram with a target intersection region marked, wherein the target intersection region includes network node 1, network node 2, network node 3, network node 8, network node 9, network node 12, network node 13, network node 14, network node 15, and network node 16.

[0097] It is understood that, in the embodiments of this application, the target intersection region is determined from the preset network topology map by using the first vector representation, the first vector set, and the second vector set symmetrical to the first vector set. This allows the routing calculation area to be restricted by the target intersection region, thereby effectively improving the selection efficiency of the optimal path while ensuring the success rate of the optimal path selection.

[0098] After determining the target intersection region through S103 above, the network topology evaluation matrix corresponding to the preset network topology map can be compressed through the target intersection region, that is, the following S104 is executed:

[0099] S104. From the network topology evaluation matrix corresponding to the preset network topology map, remove the relevant information of network node pairs including the target network node to obtain the updated network topology evaluation matrix. The target network node is the node outside the target intersection region. The network topology evaluation matrix includes the relevant information of all network node pairs with direct link relationships in the preset network topology map. The relevant information includes the identifier and evaluation value of each network node in the network node pair, and the identifier and evaluation value of the direct link.

[0100] For example, in this embodiment of the application, it is assumed that the preset network topology diagram includes m network nodes, wherein the first network node in the preset network topology diagram can be denoted as n1, the second network node can be denoted as n2, the third network node can be denoted as n3, ..., the i-th network node can be denoted as n i The j-th network node can be denoted as n. j The m-th network node can be denoted as n. m There is a direct link l1 between the first network node n1 and the second network node n2, and a direct link l2 between the first network node n1 and the third network node n3. The i-th network node n i With the j-th network node n j There is a direct link l k The (m-1)th network node n m-1 With the m-th network node n m There is a direct link l t Where m represents the number of network nodes in the preset network topology diagram, and t represents the number of direct links in the preset network topology diagram. Therefore, in this embodiment, the network topology evaluation matrix G' corresponding to the preset network topology diagram can be represented by the following formula 5:

[0101]

[0102] In this context, the first network node n1 and the second network node n2 can be considered a network node pair with a direct link relationship. The relevant information for this pair includes the identifier n1 of the first network node, the identifier n2 of the second network node, the evaluation value en1 of the first network node n1, the evaluation value en2 of the second network node n2, the identifier l1 of the direct link between the first network node n1 and the second network node n2, and the evaluation value el1 of the direct link l1. Furthermore, the first network node n1 and the third network node n3 can also be considered a network node pair, where the i-th network node n... i With the j-th network node n j It can also be viewed as a pair of network nodes, where the (m-1)th network node can be denoted as n. m-1 With the m-th network node n m It can also be viewed as a peer-to-peer network node.

[0103] It is understood that in the embodiments of this application, the network topology evaluation matrix G' is pre-constructed based on a preset network topology, and its specific construction method will be described in detail later, but will not be explained here.

[0104] For example, when removing information related to network node pairs containing the target network node from the network topology evaluation matrix, assuming the first network node n1 is a node outside the target intersection region, i.e., the target network node, then the network node pair containing the first network node n1 and its related information are removed from the network topology evaluation matrix. Assuming that the network topology evaluation matrix G' shown in Formula 5 contains only the network node pairs consisting of the first network node n1 and the second network node n2, and the first network node n1 and the third network node n3, then deleting the first and second row elements of G' yields the updated network topology evaluation matrix, which can be denoted as G. c This allows for the compression of the network topology evaluation matrix, which in turn enables subsequent optimal path selection based on the updated evaluation matrix, effectively improving the efficiency of optimal path selection.

[0105] After compressing the network topology evaluation matrix to obtain the updated network topology evaluation matrix, the following step S105 can be executed:

[0106] S105. Based on the updated network topology evaluation matrix, determine the optimal path from the target intersection region.

[0107] For example, in the embodiments of this application, when determining the optimal path from the target intersection region based on the updated network topology graph evaluation matrix, multiple candidate paths including the source network node, multiple intermediate network nodes and the destination network node can be determined from the intersection region first; and the path evaluation value corresponding to each candidate path can be determined based on the updated network topology graph evaluation matrix; and the candidate path corresponding to the maximum path evaluation value can be determined as the final optimal path, thereby obtaining the optimal path.

[0108] Generally, a higher path evaluation score indicates a better path, while a lower path evaluation score indicates a worse path.

[0109] For example, in this embodiment of the application, when determining the path evaluation value corresponding to each candidate path based on the updated network topology graph evaluation matrix, for each candidate path, the evaluation values ​​of each network node included in the candidate path and the evaluation values ​​of each segment of the candidate path can be found from the updated network topology graph evaluation matrix; then, based on the evaluation values ​​of each network node and the evaluation values ​​of each segment of the path, the path evaluation value corresponding to the candidate path is determined.

[0110] One of the paths is the direct link between two network nodes in the updated network topology evaluation matrix.

[0111] It is understandable that each of the above candidate paths includes multiple path segments, and the two endpoints of each path segment are two different network nodes. Thus, for each candidate path, there will be a node sequence and a link sequence. For example, the node sequence and link sequence corresponding to a candidate path can be represented by the following formula 6:

[0112]

[0113] Where Rs represents the node sequence and link sequence corresponding to a candidate path, (ns i ) 1×p This represents the sequence of nodes corresponding to the candidate paths, (ls) j ) 1×q Let p represent the link sequence corresponding to the candidate path, p represent the number of network nodes in the candidate path, and q represent the number of links of the network nodes in the candidate path.

[0114] For example, when determining the path evaluation value corresponding to a candidate path based on the evaluation values ​​of each network node and each path segment, a first average evaluation value corresponding to the candidate path can be determined based on the evaluation values ​​of each network node and the number of network nodes included in the candidate path; and a second average evaluation value corresponding to the candidate path can be determined based on the evaluation values ​​of each path segment and the number of path segments included in the candidate path; then the sum of the first average evaluation value and the second average evaluation value is determined as the path evaluation value Eva corresponding to the candidate path. Rs The specific process can be represented by the following formula 7:

[0115]

[0116] Combining Formula 7, after determining the path evaluation value corresponding to each candidate path, the candidate path corresponding to the maximum path evaluation value can be determined as the final optimal path. In this way, according to constraints such as bandwidth utilization and wavelength consistency, the corresponding bandwidth and wavelength can be allocated to each segment of the optimal path, thereby enabling service transmission based on the bandwidth and wavelength of each segment of the path.

[0117] For example, combined Figure 6 The example shown, using the relevant descriptions of S104 and S105 above, can be derived from... Figure 6 The optimal path is determined within the target intersection region shown. For example, see [link to example]. Figure 7 As shown, Figure 7 This is a schematic diagram of a network topology diagram with an optimal path provided in an embodiment of this application. It can be seen that the optimal path is the path that starts from the source network node 1, passes through network node 3, network node 9 and network node 13 in sequence, and reaches the destination network node 14.

[0118] As can be seen, in this embodiment, when determining the optimal path from the source network node through multiple intermediate network nodes to the destination network node, a first vector set can be constructed based on a preset network topology graph. Based on the first vector representation between the source and destination nodes, the first vector set, and a second vector set symmetrical to the first vector set, a target intersection region is determined from the preset network topology graph. Then, from the network topology graph evaluation matrix corresponding to the preset network topology graph, information related to network node pairs including the target network node is removed to obtain an updated network topology graph evaluation matrix. Finally, based on the updated network topology graph evaluation matrix, the optimal path is determined from the target intersection region. This compression of the network topology graph evaluation matrix corresponding to the preset network topology graph through the target intersection region, followed by optimal path selection based on the updated network topology graph evaluation matrix, effectively improves the efficiency of optimal path selection.

[0119] Based on the above Figure 1 The illustrated embodiment, for ease of understanding of the method for constructing the preset network topology diagram and the corresponding network topology evaluation matrix, is an example; see also [example of example]. Figure 8 As shown, Figure 8 This application provides a flowchart illustrating a method for constructing a network topology graph evaluation matrix, which may include:

[0120] S801. Based on the preset network topology map, construct the corresponding network topology map matrix.

[0121] The network topology matrix includes initial information about all network node pairs with direct link relationships in the preset network topology. The initial information includes the identifier of each network node in the network node pair, the identifier of the direct link, and the distance of the direct link. Each network node has multiple node parameters and multiple link parameters.

[0122] For example, in this embodiment of the application, it is still assumed that the preset network topology diagram includes m network nodes, wherein the first network node in the preset network topology diagram can be denoted as n1, the second network node can be denoted as n2, the third network node can be denoted as n2, ..., the i-th network node can be denoted as n i The j-th network node can be denoted as n. j The m-th network node can be denoted as n. m There is a direct link l1 between the first network node n1 and the second network node n2, and a direct link l2 between the first network node n1 and the third network node n2. The i-th network node n i With the j-th network node n j There is a direct link l k The (m-1)th network node n m-1With the m-th network node n m There is a direct link l t Then the network topology graph matrix G can be represented by the following formula 8:

[0123]

[0124] In the network topology matrix G shown in Formula 8 above, ld1 represents the link distance of the direct link l1 between the first network node n1 and the second network node n2, and ld2 represents the link distance of the direct link l2 between the first network node n1 and the third network node n3. k Represents the i-th network node n i With the j-th network node n j direct link l k Link distance, ld t This represents the (m-1)th network node n. m-1 With the m-th network node n m There is a direct link l t Link distance.

[0125] For example, in the embodiments of this application, for each network node, its corresponding multiple node parameters may include the network node's load capacity, single-wavelength rate, connectivity, and computing power; the corresponding multiple link parameters may include link distance, bandwidth utilization, and link failure rate, which can be set according to actual needs. Here, the embodiments of this application are only used as an example of a network node including four node parameters and three link parameters for illustration, but it does not mean that the embodiments of this application are limited to this.

[0126] For example, in this embodiment of the application, the node parameter matrix P corresponding to m network nodes n This can be expressed by the following formula 9:

[0127]

[0128] Where lc1 represents the load capacity of the first network node n1, swr1 represents the single-wavelength rate of the first network node n1, con1 represents the connectivity of the first network node n1, and cp1 represents the computing power of the first network node n1; lc2 represents the load capacity of the second network node n2, swr2 represents the single-wavelength rate of the second network node n2, con2 represents the connectivity of the second network node n2, and cp2 represents the computing power of the second network node n2; lc m Represents the m-th network node n m The load capacity of Swr m Represents the m-th network node n m single-wave rate, con mRepresents the m-th network node n m connectivity, cp m Represents the m-th network node n m Its computing power.

[0129] For example, in an embodiment of this application, the link parameter matrix P1 corresponding to t link parameters can be represented by the following formula 10:

[0130]

[0131] Where ld1 represents the link distance of the first direct link l1, bur1 represents the bandwidth utilization of the first direct link l1, and lfr1 represents the link failure rate of the first direct link l1; ld2 represents the link distance of the second direct link l2, bur2 represents the bandwidth utilization of the second direct link l2, and lfr2 represents the link failure rate of the second direct link l2; ld t Represents the t-th direct link l t Link distance, bur t Represents the t-th direct link l t bandwidth utilization, lfr t Represents the t-th direct link l t The link failure rate.

[0132] After determining the multiple node parameters and multiple link parameters corresponding to each network node, the following S802 can be executed:

[0133] S802. Based on the subjective analytic hierarchy process (AHP) and the objective entropy weight method (EWM), determine the weights of each node parameter among multiple node parameters and the weights of each link parameter among multiple link parameters.

[0134] For example, in an embodiment of this application, the weight matrix W of multiple node parameters corresponding to a network node n This can be expressed by the following formula 11:

[0135] Wn={a1,a2,a3,a4} Formula 11

[0136] Where a1 represents the weight of load capacity among multiple node parameters, a2 represents the weight of single-wave rate among multiple node parameters, a3 represents the weight of connectivity among multiple node parameters, and a4 represents the weight of computing power among multiple node parameters.

[0137] For example, in this embodiment of the application, the weight matrix W of multiple link parameters corresponding to the network node l This can be expressed by the following formula 12:

[0138] Wl={b1,b2,b3} Formula 12

[0139] Where b1 represents the weight of link distance among multiple link parameters, b2 represents the weight of bandwidth utilization among multiple link parameters, and b3 represents the weight of link failure rate among multiple link parameters.

[0140] For example, in the embodiments of this application, when determining the weight of each node parameter among multiple node parameters based on the subjective analytic hierarchy process (AHP) and the objective entropy weight method (EWM), for each node parameter, a first weight is determined based on AHP, and a second weight is determined based on EWM. The average of the first weight and the second weight is determined as the weight of the node parameter. In this way, by combining the subjective analytic hierarchy process (AHP) and the objective entropy weight method (EWM) to jointly determine the weight of the node parameter, the accuracy of the evaluation of the node parameter can be further improved.

[0141] When determining the first weight corresponding to a node parameter based on AHP, a judgment matrix for that node parameter can be constructed first, and the corresponding weight vector can be calculated. Then, a consistency check is performed on the judgment matrix and the weight vector. If the judgment matrix and the weight vector are inconsistent, the previously constructed judgment matrix is ​​revised, and the corresponding weight vector is recalculated. A consistency check is then performed on the revised judgment matrix and the recalculated weight vector. If the judgment matrix and the weight vector are consistent, they are sorted by level, and a consistency check is performed on the sorted results. If the sorted results are consistent, the first weight corresponding to the node parameter is obtained. If the sorted results are inconsistent, the previously constructed judgment matrix is ​​revised, and the above steps are repeated until the sorted results are consistent, thereby obtaining the first weight corresponding to the node parameter.

[0142] When determining the second weight corresponding to the node parameters based on EWM, the node parameters can first be normalized, and the information entropy of the normalized data can be calculated. Then, the information utility value can be calculated based on the information entropy, and the redundant information entropy can be calculated based on the information utility value, thereby obtaining the second weight corresponding to the node parameters.

[0143] When calculating the weights of the node parameters of a network node, namely the weight a1 of load capacity, the weight a2 of single-wavelength rate, the weight of connectivity, and the weight a4 of computing power, the weight of the i-th weight among these four weights can be expressed by the following formula 13:

[0144]

[0145] Among them, a i This represents the i-th weight among the four weights of the node parameters, wen i wn′ represents the second weight of the node parameters determined by the Objective Entropy Weight Method (EWM). i This represents the first weight of the node parameters determined based on the subjective analytic hierarchy process (AHP).

[0146] Combining Formula 13 above, the weight of each node parameter among the multiple node parameters of a network node can be calculated. The following will describe in detail how to calculate the weight of each link parameter among the multiple link parameters of a network node.

[0147] For example, in the embodiments of this application, when determining the weight of each link parameter among multiple link parameters based on the subjective analytic hierarchy process (AHP) and the objective entropy weight method (EWM), for each link parameter, a third weight is determined based on AHP, and a fourth weight is determined based on EWM. The average of the third and fourth weights is determined as the weight of the link parameter. In this way, by combining the subjective analytic hierarchy process (AHP) and the objective entropy weight method (EWM) to jointly determine the weight of the link parameter, the accuracy of the evaluation of the link parameter can be further improved.

[0148] When determining the third weight corresponding to the link parameters based on AHP, its specific implementation is similar to the method for determining the first weight corresponding to the node parameters based on AHP described above. Please refer to the relevant description of determining the first weight corresponding to the node parameters based on AHP described above; therefore, this application embodiment will not repeat it here. Similarly, when determining the fourth weight corresponding to the link parameters based on EWM, its specific implementation is similar to the method for determining the second weight corresponding to the node parameters based on EWM described above. Please refer to the relevant description of determining the second weight corresponding to the node parameters based on EWM described above; therefore, this application embodiment will not repeat it here.

[0149] When calculating the weights of the link parameters of a network node, namely the weight b1 of link distance, the weight b2 of bandwidth utilization, and the weight b3 of link failure rate, the weight of the j-th weight among these three weights can be expressed by the following formula 14:

[0150]

[0151] Among them, b j This represents the j-th weight among the four weights of the link parameters, wel. j This represents the fourth weight of the link parameters determined based on the Objective Entropy Weight Method (EWM), wl j 'Indicates the third weight of the link parameters determined based on the subjective analytic hierarchy process (AHP).

[0152] Combining Formula 14 above, the weight of each link parameter among the multiple link parameters of a network node can be calculated.

[0153] By employing a topology compression method based on vector methods, and ensuring that the routing calculation results have a solution, the optimal routing calculation method is executed in combination with subjective and objective multi-factor evaluation, balancing the efficiency of routing calculation time with the optimality of routing calculation results.

[0154] S803. For each pair of network nodes in the network topology graph matrix, determine the evaluation value of the network node based on the multiple node parameters of the network node in the pair and the weight of each node parameter, and determine the evaluation value of the direct link based on the multiple link parameters of the network node and the weight of each link parameter.

[0155] For example, to determine the i-th network node n i Taking the evaluation value as an example, it can be calculated using the following formula 15:

[0156] en i =a1lc′ i +a2swr′ i +a3con′ i +a4cp′ i Formula 15

[0157] Among them, en i Represents the i-th network node n i The evaluation value, lc′ i For the i-th network node n i load capacity lc i Data after data standardization, swr′ i For the i-th network node n i single-wave rate swr i Data after data standardization, con′ i For the i-th network node n i connectivity con i Data after data standardization, cp′ i For the i-th network node n i computing power cp i Data after data standardization.

[0158] For example, to determine the evaluation value of the j-th direct link, it can be calculated using the following formula 16:

[0159] el j =b1ld′ j +b2bur′ j +b3lfr′ j Formula 16

[0160] Among them, el j Let ld′ represent the evaluation value of the j-th direct link. j The link distance ld of the j-th direct linkj Data after data standardization, bur′ j Let bur be the bandwidth utilization of the j-th direct link. j Data after data standardization, lfr′ j The link failure rate lfr of the j-th direct link j Data after data standardization.

[0161] After combining the subjective Analytic Hierarchy Process (AHP) and the objective Entropy Weight Method (EWM) to jointly determine the evaluation values ​​of each network node to the network node and the evaluation values ​​of direct links, the following S804 can be executed:

[0162] S804. Add the evaluation values ​​of each network node to the network node in the middle and the evaluation values ​​of the direct links to the initial relevant information of each network node, and remove the distance of the direct links from the supplemented relevant information to obtain the network topology evaluation matrix.

[0163] Taking the network topology graph matrix G shown in Formula 8 above as an example, the evaluation values ​​of each network node and the evaluation values ​​of direct links are added to the initial relevant information of each network node, and the distance of direct links is removed from the added relevant information. The network topology graph evaluation matrix can be represented by Formula 5 above:

[0164]

[0165] As can be seen, in this embodiment, when determining the network topology evaluation matrix, the subjective analytic hierarchy process (AHP) and the objective entropy weight method (EWM) are used to jointly determine the weights of each node parameter among multiple node parameters and the weights of each link parameter among multiple link parameters. For each pair of network nodes in the network topology matrix, the evaluation value of the network node is determined based on the multiple node parameters and the weights of each node parameter in the pair, and the evaluation value of the direct link is determined based on the multiple link parameters and the weights of each link parameter in the pair. This can effectively improve the accuracy of the evaluation of node parameters and link parameters. Then, the evaluation values ​​of the network nodes in each pair and the evaluation values ​​of the direct links are added to the initial relevant information of each network node, and the distance of the direct link is removed from the added relevant information to obtain the network topology evaluation matrix. This improves the accuracy of the obtained network topology evaluation matrix, so that when selecting the optimal path based on the network topology evaluation matrix, both the efficiency of routing calculation time and the optimality of routing calculation results can be considered.

[0166] The optimal path selection device provided in this application is described below. The optimal path selection device described below can be referred to in correspondence with the optimal path selection method described above.

[0167] Figure 9This is a schematic diagram of an optimal path selection device provided in an embodiment of this application. For example, please refer to [link to example]. Figure 9 As shown, the optimal path selection device 90 may include:

[0168] The receiving unit 901 is used to receive the input optimal path selection request, which is used to request the optimal path from the source network node, through multiple intermediate network nodes in sequence, to the destination network node.

[0169] The first construction unit 902 is used to construct a first vector set based on a preset network topology diagram. The first vector set includes, in sequence, a first vector representation between the source network node and the destination network node, and, among the source network node, multiple intermediate network nodes, and the destination network node, multiple second vector representations between two adjacent network nodes.

[0170] The first processing unit 903 is used to determine the target intersection region from a preset network topology diagram based on a first vector representation, a first vector set, and a second vector set that is symmetric to the first vector set about the first vector representation.

[0171] The elimination unit 904 is used to eliminate the relevant information of network node pairs including the target network node from the network topology evaluation matrix corresponding to the preset network topology map, so as to obtain an updated network topology evaluation matrix. The target network node is a node located outside the target intersection region. The network topology evaluation matrix includes the relevant information of all network node pairs with direct link relationships in the preset network topology map. The relevant information includes the identifier and evaluation value of each network node in the network node pair, and the identifier and evaluation value of the direct link.

[0172] The second processing unit 905 is used to determine the optimal path from the target intersection region based on the updated network topology evaluation matrix.

[0173] For example, in an embodiment of this application, the first processing unit 903 is specifically used for:

[0174] From the preset network topology diagram, determine the first region shared by the first vector set and the second vector set; from the preset network topology diagram, determine the second region formed by the first vector representation and the second vector set; determine the target intersection region by the intersection region of the first region and the second region.

[0175] For example, in an embodiment of this application, the second processing unit 905 is specifically used for:

[0176] From the target intersection region, identify multiple candidate paths, including source network nodes, multiple intermediate network nodes, and destination network nodes; based on the updated network topology graph evaluation matrix, determine the path evaluation value corresponding to each candidate path; and determine the candidate path corresponding to the maximum path evaluation value as the optimal path.

[0177] For example, in an embodiment of this application, the second processing unit 905 is specifically used for:

[0178] For each candidate path, the evaluation values ​​of each network node included in the candidate path and the evaluation values ​​of each segment of the candidate path are found from the updated network topology evaluation matrix. Based on the evaluation values ​​of each network node and the evaluation values ​​of each segment of the candidate path, the path evaluation value corresponding to the candidate path is determined.

[0179] For example, in an embodiment of this application, the second processing unit 905 is specifically used for:

[0180] Based on the evaluation values ​​of each network node and the number of network nodes included in the candidate path, a first average evaluation value corresponding to the candidate path is determined; based on the evaluation values ​​of each segment path and the number of segment paths included in the candidate path, a second average evaluation value corresponding to the candidate path is determined; the sum of the first average evaluation value and the second average evaluation value is determined as the path evaluation value corresponding to the candidate path.

[0181] For example, in an embodiment of this application, the optimal path selection device 90 further includes a second construction unit, a third processing unit, a fourth processing unit, and a fifth processing unit.

[0182] The second construction unit is used to construct a corresponding network topology matrix based on a preset network topology map. The network topology matrix includes the initial information of all network node pairs with direct link relationships in the preset network topology map. The initial information includes the identifier of each network node in the network node pair, the identifier of the direct link, and the distance of the direct link. Each network node has multiple node parameters and multiple link parameters.

[0183] The third processing unit is used to determine the weights of each node parameter among multiple node parameters and the weights of each link parameter among multiple link parameters, based on the subjective analytic hierarchy process (AHP) and the objective entropy weight method (EWM).

[0184] The fourth processing unit is used to determine the evaluation value of each network node pair in the network topology graph matrix based on multiple node parameters and weights of each node parameter, and to determine the evaluation value of the direct link based on multiple link parameters and weights of each link parameter.

[0185] The fifth processing unit is used to supplement the initial relevant information of each network node with the evaluation values ​​of the network nodes in the middle and the evaluation values ​​of the direct links, and to remove the distance of the direct links from the supplemented relevant information to obtain the network topology evaluation matrix.

[0186] For example, in an embodiment of this application, the third processing unit is specifically used for:

[0187] For each node parameter, the first weight corresponding to the node parameter is determined based on AHP, and the second weight corresponding to the node parameter is determined based on EWM; the average of the first weight and the second weight is determined as the weight of the node parameter.

[0188] The optimal path selection device 90 provided in this application embodiment can execute the technical solution of the optimal path selection method in any of the above embodiments. Its implementation principle and beneficial effects are similar to those of the optimal path selection method. Please refer to the implementation principle and beneficial effects of the optimal path selection method. It will not be repeated here.

[0189] Figure 10 This is a schematic diagram of the physical structure of an electronic device provided in an embodiment of this application, such as... Figure 10As shown, the electronic device may include: a processor 1010, a communication interface 1020, a memory 1030, and a communication bus 1040, wherein the processor 1010, the communication interface 1020, and the memory 1030 communicate with each other through the communication bus 1040. The processor 1010 can call logical instructions in the memory 1030 to execute an optimal path selection method. This method includes: receiving an input optimal path selection request, the optimal path selection request being used to request an optimal path starting from a source network node, sequentially passing through multiple intermediate network nodes to reach a destination network node; constructing a first vector set based on a preset network topology map, the first vector set sequentially including a first vector representation between the source network node and the destination network node, and multiple second vector representations between adjacent network nodes among the source network node, multiple intermediate network nodes, and the destination network node; and based on the first vector representation, the first vector set, and related information... The first vector represents a symmetric set of second vectors. A target intersection region is determined from the preset network topology graph. From the network topology graph evaluation matrix corresponding to the preset network topology graph, information related to network node pairs including the target network node is removed to obtain an updated network topology graph evaluation matrix. The target network node is a node located outside the target intersection region. The network topology graph evaluation matrix includes information related to all network node pairs with direct link relationships in the preset network topology graph. This information includes the identifier and evaluation value of each network node in the network node pair, and the identifier and evaluation value of the direct link. Based on the updated network topology graph evaluation matrix, the optimal path is determined from the target intersection region.

[0190] Furthermore, the logical instructions in the aforementioned memory 1030 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0191] On the other hand, this application also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the optimal path selection method provided by the above methods. The method includes: receiving an input optimal path selection request, the optimal path selection request being used to request an optimal path from a source network node, sequentially passing through multiple intermediate network nodes to a destination network node; constructing a first vector set based on a preset network topology map, the first vector set sequentially including a first vector representation between the source network node and the destination network node, and multiple vector representations between adjacent network nodes in the source network node, multiple intermediate network nodes, and the destination network node. The second vector representation; based on the first vector representation, the first vector set, and the second vector set symmetric to the first vector set with respect to the first vector representation, the target intersection region is determined from the preset network topology graph; from the network topology graph evaluation matrix corresponding to the preset network topology graph, relevant information of network node pairs including the target network node is removed, resulting in an updated network topology graph evaluation matrix, where the target network node is a node outside the target intersection region, and the network topology graph evaluation matrix includes relevant information of all network node pairs with direct link relationships in the preset network topology graph, including the identifier and evaluation value of each network node in the network node pair, and the identifier and evaluation value of the direct link; based on the updated network topology graph evaluation matrix, the optimal path is determined from the target intersection region.

[0192] Furthermore, this application also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the optimal path selection method provided by the methods described above. The method includes: receiving an input optimal path selection request, the optimal path selection request being used to request an optimal path from a source network node, sequentially passing through multiple intermediate network nodes to a destination network node; constructing a first vector set based on a preset network topology graph, the first vector set sequentially including a first vector representation between the source network node and the destination network node, and multiple second vector representations between adjacent network nodes among the source network node, multiple intermediate network nodes, and the destination network node; and based on the first vector representation... A first vector set and a second vector set symmetric to the first vector set about the first vector representation are used to determine the target intersection region from a preset network topology graph. From the network topology graph evaluation matrix corresponding to the preset network topology graph, information related to network node pairs including the target network node is removed to obtain an updated network topology graph evaluation matrix. The target network node is a node located outside the target intersection region. The network topology graph evaluation matrix includes information related to all network node pairs with direct link relationships in the preset network topology graph, including the identifier and evaluation value of each network node in the network node pair, and the identifier and evaluation value of the direct link. Based on the updated network topology graph evaluation matrix, the optimal path is determined from the target intersection region.

[0193] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected based on actual needs to achieve the purpose of this embodiment. Those skilled in the art can understand and implement this without any creative effort.

[0194] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0195] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. An optimal path selection method, characterized in that, include: Receive an input optimal path selection request, which is used to request the optimal path from the source network node, through multiple intermediate network nodes in sequence, to the destination network node. Based on a preset network topology, a first vector set is constructed. The first vector set includes, in sequence, a first vector representation between the source network node and the destination network node, and multiple second vector representations between two adjacent network nodes among the source network node, the plurality of intermediate network nodes, and the destination network node. Based on the first vector representation, the first vector set, and a second vector set that is symmetric to the first vector set with respect to the first vector representation, the target intersection region is determined from the preset network topology graph; From the network topology evaluation matrix corresponding to the preset network topology map, remove the relevant information of network node pairs including the target network node to obtain the updated network topology evaluation matrix. The target network node is a node located outside the target intersection region. The network topology evaluation matrix includes the relevant information of all network node pairs with direct link relationships in the preset network topology map. The relevant information includes the identifier and evaluation value of each network node in the network node pair, and the identifier and evaluation value of the direct link. The optimal path is determined from the target intersection region based on the updated network topology evaluation matrix.

2. The optimal path selection method according to claim 1, characterized in that, The step of determining the target intersection region from the preset network topology graph based on the first vector representation, the first vector set, and a second vector set symmetric to the first vector set with respect to the first vector representation includes: From the preset network topology diagram, determine the first region shared by the first vector set and the second vector set; From the preset network topology diagram, determine the second region formed by the first vector representation and the second vector set; The target intersection region is determined by the intersection of the first region and the second region.

3. The optimal path selection method according to claim 1, characterized in that, Determining the optimal path from the target intersection region based on the updated network topology evaluation matrix includes: From the target intersection region, determine multiple candidate paths including the source network node, the multiple intermediate network nodes, and the destination network node; Based on the updated network topology evaluation matrix, determine the path evaluation value corresponding to each candidate path; The candidate path corresponding to the maximum path evaluation value is determined as the optimal path.

4. The optimal path selection method according to claim 3, characterized in that, The step of determining the path evaluation value corresponding to each candidate path based on the updated network topology evaluation matrix includes: For each candidate path, the evaluation values ​​of each network node included in the candidate path and the evaluation values ​​of each segment of the candidate path are found from the updated network topology evaluation matrix. Based on the evaluation values ​​of each network node and each path segment, the path evaluation value corresponding to the candidate path is determined.

5. The optimal path selection method according to claim 4, characterized in that, The step of determining the path evaluation value corresponding to the candidate path based on the evaluation values ​​of each network node and the evaluation values ​​of each path segment includes: Based on the evaluation values ​​of each network node and the number of network nodes included in the candidate path, a first average evaluation value corresponding to the candidate path is determined. Based on the evaluation values ​​of each path segment and the number of path segments included in the candidate path, a second average evaluation value corresponding to the candidate path is determined. The sum of the first average evaluation value and the second average evaluation value is determined as the path evaluation value corresponding to the candidate path.

6. The optimal path selection method according to any one of claims 1-5, characterized in that, The method further includes: Based on the preset network topology map, a corresponding network topology map matrix is ​​constructed. The network topology map matrix includes the initial information of all network node pairs with direct link relationships in the preset network topology map. The initial information includes the identifier of each network node in the network node pair, the identifier of the direct link, and the distance of the direct link. Each network node has multiple node parameters and multiple link parameters. Based on the subjective analytic hierarchy process (AHP) and the objective entropy weight method (EWM), the weights of each node parameter and each link parameter among the multiple node parameters are determined. For each pair of network nodes in the network topology graph matrix, the evaluation value of the network node is determined based on multiple node parameters of the network node in the pair and the weight of each node parameter. The evaluation value of the direct link is determined based on multiple link parameters of the network node and the weight of each link parameter. The evaluation values ​​of the network nodes and the evaluation values ​​of the direct links in each network node pair are added to the initial relevant information of each network node, and the distance of the direct links is removed from the added relevant information to obtain the network topology evaluation matrix.

7. The optimal path selection method according to claim 6, characterized in that, The determination of the weight of each node parameter among the multiple node parameters, based on the subjective analytic hierarchy process (AHP) and the objective entropy weight method (EWM), includes: For each node parameter, a first weight corresponding to the node parameter is determined based on AHP, and a second weight corresponding to the node parameter is determined based on EWM; The average of the first weight and the second weight is determined as the weight of the node parameter.

8. An optimal path selection device, characterized in that, include: The receiving unit is used to receive an input optimal path selection request, which requests the optimal path from the source network node, through multiple intermediate network nodes, to the destination network node. The first construction unit is used to construct a first vector set based on a preset network topology diagram. The first vector set includes, in sequence, a first vector representation between the source network node and the destination network node, and multiple second vector representations between two adjacent network nodes among the source network node, the plurality of intermediate network nodes, and the destination network node. The first processing unit is configured to determine a target intersection region from the preset network topology graph based on the first vector representation, the first vector set, and a second vector set that is symmetric to the first vector set about the first vector representation. The elimination unit is used to eliminate relevant information of network node pairs including target network nodes from the network topology evaluation matrix corresponding to the preset network topology map, so as to obtain an updated network topology evaluation matrix. The target network node is a node located outside the target intersection region. The network topology evaluation matrix includes relevant information of all network node pairs with direct link relationships in the preset network topology map. The relevant information includes the identifier and evaluation value of each network node in the network node pair, and the identifier and evaluation value of the direct link. The second processing unit is used to determine the optimal path from the target intersection region based on the updated network topology evaluation matrix.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the optimal path selection method as described in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the optimal path selection method as described in any one of claims 1 to 7.

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